sample survey of eccd centres in kenya - mukui and mwaniki december 1995
DESCRIPTION
Early Childhood Care and Development (ECCD) centres, commonly referred to as pre-schools, have emerged as alternatives to traditional ways of child-rearing. Early childhood education in Kenya is carried out on a partnership basis, including Government, local authorities, parents and local communities, voluntary organizations, religious bodies and private institutions. The expansion of pre-school education underscores its important role as an alternative to traditional ways of bringing up children, and of preparing children for primary school education. The ECCD survey was carried out in May 1995 on a sample of 17 districts/urban centres representing urban, pastoralist, and other rural areas, and covered 906 ECCD centres nationally. The survey collected information on enrolment, size and structure of teaching and nonteaching staff, centre’s financial data, child feeding, health surveillance at the centres, and inventory of centre’s facilities.TRANSCRIPT
A
REPORT OF THE
SAMPLE SURVEY OF EARLY CHILDHOOD CARE AND
DEVELOPMENT CENTRES
by
John Thinguri Mukui
and
Jotham A. Mwaniki Prepared for the World Bank and the Ministry of Education,
Nairobi, Kenya
December 1995
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ACKNOWLEDGEMENTS We thank all the individuals in Government, World Bank, and nongovernmental organizations who were helpful in providing ideas and support that facilitated the design and implementation of the survey. The study team held fruitful discussions on conceptual issues with Mrs Mary Njoroge (Ministry of Education headquarters), Mrs Margaret Kabiru (NACECE), Mrs Anne Njenga (NACECE), and some DICECE officers. The fieldwork was ably supervised by district/municipality education offices, mainly the DICECE personnel. The survey would not have succeeded without the cooperation of headteachers of the responding pre-schools. The team received useful technical advice on statistical and programming issues from Jimmie Katabwa (Central Bureau of Statistics) and Leonard Obidha (Ministry of Planning and National Development). The work was carried out under the general guidance of Mrs Mary Njoroge (Ministry of Education headquarters).
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TABLE OF CONTENTS CHAPTER 1: INTRODUCTION ........................................................................................................................... 1
BACKGROUND ................................................................................................................................................... 1 STATEMENT OF THE PROBLEM ................................................................................................................ 1 OBJECTIVES OF THE SAMPLE SURVEY OF ECCD CENTRES ........................................................ 2
CHAPTER 2: STRUCTURE OF EARLY CHILDHOOD CARE AND EDUCATION IN KENYA ... 4 DEVELOPMENT AND STRUCTURE OF PRE-SCHOOL INSTITUTIONS ..................................... 4 REVIEW OF PREVIOUS STUDIES ............................................................................................................... 5 REVIEW OF OFFICIAL STATISTICS ON PRE-SCHOOL EDUCATION ......................................... 8
CHAPTER 3: CONCEPTS AND DEFINITIONS USED IN THE ECCD SURVEY ............................. 10 CHAPTER 4: SAMPLE DESIGN AND IMPLEMENTATION .................................................................. 13
SAMPLE DESIGN .............................................................................................................................................. 13 ESTIMATION PROCEDURES ...................................................................................................................... 15
CHAPTER 5: SURVEY DESCRIPTION AND ORGANIZATION ........................................................... 18 DEVELOPMENT OF THE SURVEY INSTRUMENTS .......................................................................... 18 PRE-TEST ............................................................................................................................................................. 18 SURVEY ORGANIZATION ........................................................................................................................... 19 FIELDWORK ...................................................................................................................................................... 20 DATA EDIT AND PROCESSING ................................................................................................................ 21
CHAPTER 6: ESTIMATION OF POPULATION AGE 3-6 YEARS BY DISTRICT/MUNICIPALITY ............................................................................................................................... 24
ALTERNATIVE METHODOLOGIES OF PROJECTING POPULATION AGE 3-6 YEARS ..... 24 LIMITATIONS OF POPULATION DATA ................................................................................................. 25 ESTIMATES OF POPULATION AGE GROUP 3-6 YEARS ................................................................. 26
CHAPTER 7: PROFILES OF PRE-SCHOOLS ................................................................................................ 28 RESPONSE RATES ........................................................................................................................................... 28 GROWTH IN ESTABLISHMENT OF PRE-SCHOOLS .......................................................................... 28 PRE-SCHOOLS BY TYPE OF NEIGHBOURHOOD ............................................................................. 29 PRE-SCHOOLS BY OWNERSHIP ................................................................................................................ 29 PRE-SCHOOLS BY TYPE OF SERVICES OFFERED ............................................................................ 29 REGISTRATION ................................................................................................................................................ 29 MANAGEMENT OF PRE-SCHOOLS ......................................................................................................... 30 PRE-SCHOOLS BY ATTACHMENT TO A PRIMARY SCHOOL ....................................................... 31 SUPERVISION OF PRE-SCHOOLS ............................................................................................................. 32
CHAPTER 8: ENROLMENT IN PRE-SCHOOLS .......................................................................................... 33 ENROLMENT SIZE BY SPONSOR ............................................................................................................. 33 PRE-SCHOOL ENROLMENT RATIOS BY SEX ..................................................................................... 33 ANALYSIS OF PRE-SCHOOL FEES ........................................................................................................... 34
CHAPTER 9: PROFILES OF PRE-SCHOOL PERSONNEL ...................................................................... 36 PRE-SCHOOL EMPLOYEES ......................................................................................................................... 36 TEACHERS’ EDUCATION AND TRAINING.......................................................................................... 37 TEACHERS’ TEACHING EXPERIENCE .................................................................................................. 38 PUPIL-TEACHER RATIOS ............................................................................................................................. 38
CHAPTER 10: FINANCING OF PRE-SCHOOLS ......................................................................................... 39 GRANTS/AID ..................................................................................................................................................... 39 OPERATING COSTS ........................................................................................................................................ 39 CURRENT MARKET VALUE ........................................................................................................................ 40 BANK ACCOUNTS ........................................................................................................................................... 41
CHAPTER 11: FEEDING AND HEALTH INTERVENTIONS ................................................................ 42 FEEDING ............................................................................................................................................................. 42 HEALTH ............................................................................................................................................................... 43
CHAPTER 12: INVENTORY OF PRE-SCHOOL FACILITIES ................................................................. 45
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PRE-SCHOOL PREMISES ............................................................................................................................... 45 SCHOOL BUILDING MATERIALS ............................................................................................................. 45 WATER AND SANITATION ......................................................................................................................... 46 SOURCE OF CLASSROOM LIGHTING .................................................................................................... 47
CHAPTER 13: OVERVIEW, CONCLUSIONS AND RECOMMENDATIONS .................................... 48 OVERVIEW ......................................................................................................................................................... 48 SUMMARY OF SURVEY FINDINGS .......................................................................................................... 50 RECOMMENDATIONS ................................................................................................................................... 51
ANNEX 1: CODES FOR ECCD SURVEY OPEN-ENDED QUESTIONS ............................................ 53 ANNEX 2: TERMS OF REFERENCE ............................................................................................................... 54 ANNEX 3: THE EXTENT TO WHICH THE QUESTIONNAIRE MEETS THE TERMS OF REFERENCE ............................................................................................................................................................ 58 ANNEX 4: SELECTED REFERENCES ........................................................................................................... 61 ANNEX 5: STATISTICAL APPENDIX TABLES ........................................................................................... 63 ANNEX 7: ENUMERATORS’ REFERENCE MANUAL ........................................................................... 139 ANNEX 8: SURVEY QUESTIONNAIRE ...................................................................................................... 168 ANNEX 9: REPORT OF THE PROJECT IMPLEMENTATION PLAN: MONITORING AND EVALUATION COMPONENT ........................................................................................................................ 186
SECTION 1: INTRODUCTION ................................................................................................................... 189 SECTION 2: THE MONITORING COMPONENT ............................................................................... 192 SECTION 3: EVALUATION COMPONENT .......................................................................................... 194 SECTION 4: CLIENT CONSULTATION ................................................................................................. 207 SECTION 5: SPECIAL STUDIES ................................................................................................................. 212
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CHAPTER 1: INTRODUCTION BACKGROUND 1.1. Traditional ways of bringing up children have been affected by the rapid political, social and economic changes that have taken place in Kenya since independence. The society has therefore been forced to look for alternative ways of taking care of its young children. 1.2. Against this scenario, Early Childhood Care and Development (ECCD) centres, commonly referred to as pre-schools, have emerged as alternatives to traditional ways of child-rearing. In addition to preparing children for formal education, these centres play a custodial and socialization role in the absence of active families’ involvement in bringing up their young children. 1.3. Early childhood education in Kenya is carried out on a partnership basis. The joint efforts of the Government, local authorities, parents and local communities, voluntary organizations, religious bodies and private institutions have contributed to rapid expansion of pre-school education. A survey carried out in 1969 showed that there were 200,000 children enrolled in 4,800 centres in the country with 5,000 teachers, most of whom were untrained. In 1973, the enrolment had risen to nearly 300,000 under the care of 6,326 teachers; and to 400,000 children in 8,000 pre-schools under the care of about 10,000 teachers in 1979. By 1994, the enrolment had expanded to an estimated 951,997 children attending 19,083 centres, with a teaching force of 27,829. The expansion of pre-school education underscores its important role as an alternative to traditional ways of bringing up children, and of preparing children for primary school education. STATEMENT OF THE PROBLEM 1.4. Because of the fundamental role played by these centres in early childhood care and development, and their centrality as a foundation for formal education, the centres have been the subject of several studies. The main areas of interest include: their number and structure, types and quality of services offered, and the size and quality of their teaching force and other caregivers. 1.5. Current and reliable information is therefore required to formulate sound policies on the development and management of early childhood care and development. In Kenya, interest in such information has increased in recent years. Various Government bodies, institutions and organizations have become aware that the starting point in planning for ECCD centres is the collection of comprehensive statistics about their actual size and structure in terms of facilities, enrolment, teaching staff, etc. 1.6. Certain statistics on the subject are collected. It is however recognized that these statistics are inadequate and have some gaps that need to be filled. Existing data on the number of centres caring for the under 6 year-olds, the services offered, and the number and training levels of the caregivers are not comprehensive enough to provide a complete picture of the pre-school education system. The data have been collected on an ad hoc basis by researchers and consultants on behalf of the institutions involved in the care and development of young children. In addition, most of the data were obtained through small scale investigations covering only targeted districts, and were primarily for research and project evaluation purposes. 1.7. The Ministry of Education compiles statistics submitted by District Educational Officers (DEO) on number of pre-schools, child enrolment, and number of teachers in the pre-schools. The DEOs collect these statistics through their field officers such as DICECE and Zonal Officers. These statistics give good estimates on the number of pre-schools, enrolments and numbers of teachers in these institutions. 1.8. Nevertheless, there are data gaps on early childhood education regarding number of institutions, enrolment, teaching force, types of services provided, ownership and sponsorship, fees structure,
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physical facilities and other types of investments, and health and nutritional status of children. Some major gaps and weaknesses of these statistics are:
a) No facility-based and financial data are submitted from the districts.
b) The response rate is not known as a district is assumed to base its summary statistics on a complete count of all pre-school centres.
c) The data disseminated do not always include age of children, which is a very important variable in analysing education statistics.
d) The reported statistics on pre-schools are not compiled on the basis of any official guidelines, as exemplified by the following cases: (i) there is no standard definition of an ECCD centre; (ii) although pre-school statistics refer to numbers of “trained” and “untrained” teachers, there is no standard classification scheme of pre-school teachers, and such categorisation is therefore at the discretion of the field officers who compile the statistics; and (iii) unlike statistics on primary and secondary schools which are based on a single reference period (March of the index year), there is no standard reference reporting date for statistics of pre-schools. The wide annual variations in the statistics on pre-schools are therefore likely to be a statistical illusion due to lack of guidelines in compiling the statistics.
e) Reported enrolment data behave in an erratic manner, where they show oscillating trends for some districts and municipalities, e.g. some district figures ending with “5” or “0” for consecutive years, which is certainly suspect.
1.9. There is therefore need for reliable and comprehensive database on pre-school education. In this regard, the Ministry of Education commissioned several studies of these centres in May 1995 so as to provide a comprehensive database. This report presents the findings of one of the studies, which involved conducting a sample survey of ECCD centres in 10 rural districts and 7 municipalities. OBJECTIVES OF THE SAMPLE SURVEY OF ECCD CENTRES 1.10. The main objectives of the survey were to:
a) Provide baseline data for planning and policy formulation of early childhood care and development;
(b) Provide a profile of the services offered by these centres; (c) Show trends in child enrolments, teachers and other child caregivers; (d) Provide profiles of teachers and other caregivers; (e) Provide data on healthcare and nutrition services available to children in the centres; (f) Assess the physical facilities accessible to children enrolled in the centres; and (g) Provide a framework for designing a computerized database management system for
monitoring early childhood care and development. 1.11. The survey covered 906 ECCD centres nationally. It was conducted on a sample of 17 districts/urban centres representing urban, pastoralist, and other rural areas. The main urban areas were represented by Nairobi and Mombasa, while other urban areas were represented by Kisumu, Thika, Nakuru, Kitale and Eldoret. Rural areas were grouped into two zones, i.e. pastoralist and other rural. Pastoralist districts were represented by Narok and Garissa. The other rural districts - selected so as to include every
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province and broad agro-ecological zones - were Nyandarua, Uasin Gishu, Kericho, Kakamega, Nakuru, Machakos, Kisumu, and Kilifi districts. 1.12. The questionnaire for this survey was divided into seven (7) main sections. The sections sought information on: (i) identification and basic information about the ECCD centre; (ii) child enrolment data; (iii) size and structure of the teaching and nonteaching staff; (iv) centre’s financing; (v) children feeding practices; (vi) nature of health surveillance/ interventions at the centre; and (vii) inventory of centre’s facilities. Section 8, which sought views on problems which the ECCD centre encounters and suggested solutions, was not analyzed.
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CHAPTER 2: STRUCTURE OF EARLY CHILDHOOD CARE AND EDUCATION IN KENYA
DEVELOPMENT AND STRUCTURE OF PRE-SCHOOL INSTITUTIONS 2.1. The first pre-schools in Kenya began to emerge in the 1940s. They were established in urban areas to cater for European and later, Asian children. These pre-schools were well provided for, and were aimed at providing basic education for the children. The institutions were modelled after the British pre-schools of the period. 2.2. Pre-schools for African children were introduced in the large agricultural plantations and African neighbourhoods in major towns in the 1950s. The pre-schools fulfilled a custodial function. In some of the centres, basic health services and supplementary feeding were provided. A large number of children’s centres were opened during the emergency period (1953-1959), particularly in those areas most involved in the struggle for freedom. These centres provided custodial care and sometimes supplementary feeding. Children also engaged in singing and dancing at the centres. 2.3. Prior to the transfer of pre-school functions from the Ministry of Culture and Social Services to the Ministry of Education in 1980, pre-school education was looked upon as a social service rather than an educational programme (Alice Owano, et al, The State of Pre-School Education in Kenya, 1986). For example, during 1960-1966 it was under the Ministry of Home Affairs; and under the Ministry of Culture and Social Services during 1966-1979. The Ministry of Education started being involved in pre-school education as early as 1970, when, jointly with the Bernard Van Leer Foundation, the ten-year pre-school project was started at the Kenya Institute of Education. The main objective of the project was to improve the quality of pre-school education through development of training models, curriculum, and other support materials for use by the children, teachers and trainers. Eventually, the Government transferred the responsibility for early childhood education from the Ministry of Culture and Social Services to the Ministry of Education in 1980. 2.4. In 1982, a national seminar was held to discuss the experiences and outcomes of the Pre-School Education Project. One of the recommendations from the seminar was the establishment of a national centre for early childhood education and a network of sub-centres at the district level. The Ministry responded to this recommendation by setting up the National Centre for Early Childhood Education (NACECE) in 1984 and its sub-centres, the District Centres for Early Childhood Education (DICECE) beginning in 1985. 2.5. The current pre-school programme is administered through three sections in the Ministry of Education, namely, (a) the pre-schools section at the Ministry’s headquarters, which handles administrative matters related to registration of pre-schools, coordination with donors and NGOs, and inter-sectoral liaison pertaining to children’s protection, care, health and nutrition; (b) the National Centre for Early Childhood Education (NACECE), which is responsible of caregivers and teachers and development of the curriculum; and (c) the Ministry’s inspectorate department which is responsible for the maintenance and monitoring of standards of the pre-schools program. The DICECE staffs are accountable to the District Education Officers (in the case of districts) or Municipal Education Officers (in the case of municipalities) for their day-to-day operations. 2.6. The functions of NACECE include (a) training of trainers, (b) development and dissemination of the curriculum for pre-school programmes, (c) undertaking and coordinating research on early childhood care and education, and (d) offering services to external and internal partners and facilitating interaction between agencies and sponsors. 2.7. The Government has established DICECE in every district in the country. The DICECE are categorized into fully-fledged and associate DICECE. The fully-fledged DICECE offer the two-year residential in-service training for pre-school teachers while the associate DICECE do not. The fully-fledged DICECE trains teachers from their districts as well as those from neighbouring districts, i.e. catchment districts. The
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associate DICECE carry out all the DICECE activities in their districts except residential training of teachers. A DICECE has the following functions: (a) training of pre-school teachers and other personnel at the district level, (b) development of localized curriculum including songs, stories, poems, riddles and plays using vernacular languages of the catchments areas, (c) coordinating district-based research, (d) conducting awareness programmes to parents, local leaders and teachers, and (e) supervising and inspecting pre-school programmes in the districts. 2.8. The provision of early childhood care and education services is carried out on a partnership basis. Government involvement in early childhood care and development includes extension and provision of maternal and child healthcare services, feeding programmes, provision of the curriculum, and training and supervision of pre-school teachers. In the establishment of DICECE, the Government has received support from external partners, mainly, UNICEF, the Aga Khan Foundation (AKF) and the Bernard Van Leer Foundation (BVLF). The BVLF has since 1984 been supporting all the activities of NACECE. UNICEF, in addition to the DICECE programme, has been supporting area-based programmes through the Child Survival and Development (CSD) programme in the so-called UNICEF districts. The Aga Khan Foundation has since 1986 supported the training of teachers, community mobilization and the development of local curriculum materials in Garissa, Nyeri, Kilifi, and Kericho. Other partners include parents and the local community, local authorities, religious organizations, individuals, and companies/estates. 2.9. At the policy level, Government’s concern with pre-school education followed the report of the Presidential Working Party on Education and Manpower Training for Next Decade and Beyond (the Kamunge report of 1988), which was the first commission in post-independent Kenya to make reference to pre-school education. The Government’s Sessional Paper No 6 of 1988, which was the official response to the Kamunge report, outlined the objectives of pre-school education as enabling the child to (a) develop physical skills, a wide vocabulary, language and learn to classify; (b) develop the concept of numbers and be able to solve simple problems; (c) be aware of temporal and spatial relationships; (d) acquire a general knowledge about the physical, biological and social world around them; (e) express ideas in words, in pictures and through a variety of other matters; and (f) develop and appreciate other people’s needs and views. REVIEW OF PREVIOUS STUDIES 2.10. Various studies have been undertaken on the under-six year old covering different geographical areas and subjects matter. This section will attempt to briefly review a few of the most recent studies which have relied on field data collection as the basis of their findings and conclusions. 2.11. The first study was conducted in Baringo, Nakuru and Siaya districts, to find out (a) the services provided for the pre-school child, (b) the quality of the services provided, (c) attitudes of parents to these services, and (d) how the child benefits from the services provided (see Alice Owano, et al, The State of Pre-School Education in Kenya, 1986). The three districts were selected to represent certain features of Kenyan socioeconomic life. Siaya district represented moderately developed rural area where the population was sedentary, agricultural, and with a fairly developed formal education system. Nakuru represented new settlement and various types of plantations including forestry and cash crop farming; while Baringo represented sparsely populated pastoral communities with a relatively less developed formal education sector. 2.12. The study focused on pre-school and health facilities, pre-school classrooms and teachers, pre-school children (both in- and out-of-school) and their parents/guardians, and officers in charge of health institutions. The sample consisted of 235 in-school children, 148 out-of-school children, 192 parents/guardians of in-school-children, 157 parents/guardians of out-of-school children, 19 pre-schools, 27 pre-school teachers, 12 health institutions, and 12 officers in charge of health institutions. Although the study argues that Baringo, Nakuru and Siaya were selected to give as close a national picture as possible, the number of districts selected (3) and the total number of pre-schools (19) were too few to give a national representation. 2.13. Some of the important findings of the study were that: (a) the quality of facilities and services
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in the pre-schools, including the state of classrooms and furniture, were very low; (b) more than half of the teachers had Certificate of Primary Education or below, and 44% had no pre-school training; and (c) most teachers and parents considered pre-school education as a preparation for Primary Standard One. The observations and tests administered to the in-school and out-of-school children revealed very little differences in the performance of the two groups on 84.6% of the test items. However, major differences were recorded on “counting from one to ten” and “saying all letters of the alphabet correctly”; with in-school children scoring a mean of 64 and 31 per cent, respectively, while out-of-school children scored 32 and 5 per cent, respectively. The researchers concluded that “the two tasks were the weakest in the whole set, even for the in-school children. This is significant considering that most schools did very little else besides drilling children on numbers and the alphabet.” 2.14. An evaluation of NACECE-DICECE programme was conducted in 1987 (Ministry of Education and Bernard Van Leer Foundation, Evaluation of NACECE-DICECE Programme, August 1987). The population covered by the evaluation was the then 15 DICECE districts and their catchments districts. The DICECE districts were stratified by (a) whether “old” (established in 1985) or “new” (established in 1986), (b) sponsors, and (c) whether pastoral or settled agriculture. The districts selected were Kakamega/Bungoma, Kwale/Taita Taveta, Machakos/Kitui, Baringo/Samburu, Kericho/Nandi, Murang’a/Kiambu, Kisumu/Siaya and Garissa. After the sample selection based on above criteria, Embu and Narok DICECE were subjectively added to the sample. Embu was added to take advantage of the pre-school teachers’ panels in Embu formed in 1987, while Narok was added because of the district-based research which was collecting information in Narok on child rearing practices, and child health and nutrition status in the Maasai community. 2.15. The evaluation focused on the following aspects of the NACECE/DICECE programme: organization and management, finance and resources, community involvement, training and awareness, curriculum development, and research and development. The main respondents for the evaluation were all DICECE trainers, a sample of pre-school teachers, headteachers of primary schools, Primary Standard One teachers, and community leaders. Different questionnaires were used to collect data from pre-school teachers, Primary Standard One teachers, and trainers of pre-school teachers. The evaluators were also required to observe and report on the pre-school facilities. 2.16. Some of the main findings of the evaluation were that (a) teachers’ salaries by parents and local communities were low and often irregularly paid; (b) in many pre-schools, ingredients and the utensils used in the feeding programmes were kept in unhygienic conditions; and (c) some pre-school teachers lacked the laid-down entry academic qualifications of the DICECE programme. However, questions like “types of facilities and condition of maintenance and cleanliness” (i.e. classrooms, toilets, furniture, compound, playground, etc) may be highly subjective and therefore prone to enumerator bias unless the exercise is carried out by one interviewer. 2.17. The Aga Khan Foundation (AKF) DICECE programme covering Garissa, Kilifi, Kericho and Nyeri, was evaluated in 1990 (National Centre for Early Childhood Education and Aga Khan Foundation, Evaluation Report of the Aga Khan Foundation Sponsored DICECE, June 1990). The AKF selected the districts for support for varied reasons. Garissa district DICECE and its catchment district (Wajir) was selected because it (a) had a very low pre-school attendance (3.3%) due to the nomadic nature of the population; and (b) most of the inhabitants profess the Islamic faith. The DICECE team was therefore required to design programmes which would harmonise religious teaching and secular education. Just as in Garissa, the Kilifi DICECE was supposed to harmonise religious teaching and secular education. In Kericho, the DICECE team was required to undertake studies on the life patterns of the pre-school children that are born and brought up in the tea estates. Nyeri district was selected to find out how the district had managed to reduce child mortality very considerably despite low pre-school enrolment (then estimated at 20%) compared to other districts of similar economic potential. It was hoped that a comprehensive documentation of these experiences would be very useful in assisting other districts striving to bring down child mortality rates. 2.18. The main purpose of the evaluation was to find out how effectively the NACECE/DICECE
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programmes had been implemented in the Aga Khan Foundation-sponsored DICECE, and make recommendations for improving the programme. The evaluation addressed the areas of training, curriculum development (localised and integration of secular and Islamic education), development and welfare of the pre-school child, community linkages in pre-school education, and research and evaluation activities in the DICECE programmes. Data were collected from DICECE trainers, pre-school teachers, Primary Standard One teachers, parents/ community, sponsors, NACECE staff, education officers, school inspectors, and pre-school centres. The data collection exercise used questionnaires, interview schedules, and observation schedules. 2.19. The evaluation had important findings and recommendations e.g. (a) lack of training facilities limited the number of trainees they can admit each year; and (b) emphasis on formal education as a stepping stone to Primary Standard One entry contributes to lessened emphasis on health and feeding programmes mounted by the schools. The evaluation was, however, undertaken by NACECE/DICECE staff without active assistance of independent consultants, which might raise questions of objectivity during the data collection process and in interpretation of the results. In addition, the evaluation did not solicit information on early childhood education enrolment at the district level for the four districts and their catchment areas. 2.20. An evaluation of early childhood care and education on eleven UNICEF-supported districts was conducted in 1992 (National Centre for Early Childhood Education and UNICEF, Early Childhood Care and Education in Kenya: A Report of an Evaluation of UNICEF-Sponsored Districts, November 1992). The evaluation covered six fully-fledged DICECE (Baringo, Meru, Murang’a, Kakamega, Kisumu and Kwale) and all UNICEF-supported area-based programme districts under the UNICEF’s Child Survival and Development (CSD) programme (Nairobi, Kitui, Baringo, Kisumu, Embu, South Nyanza, Kwale and Mombasa districts). 2.21. The evaluation focused on training and awareness; feeding programmes; growth monitoring and promotion; administration and inter-sectoral collaboration of parents, local authorities, sponsors and the Government; and costs and resources of pre-school education. Statistics on pre-school enrolment, number of pre-schools, and number of trained and untrained teachers used in the evaluation report were collected in the regular data collection exercise but not during the evaluation. 2.22. The evaluation reported that the main achievements of the Early Childhood Care and Education programme in the study areas included growth in terms of personnel, institutions and enrolment; and increased community awareness and mobilization. The major constraints to the programme were reported as (a) payment of teachers’ salaries, which were low and often irregular in community-sponsored pre-schools; (b) the quality and sustainability of community-based feeding programmes and other aspects of growth monitoring and promotion; and (c) children aged below three years were not adequately catered for in the programme. 2.23. An evaluation of early childhood care and education of the Samburu District Community-Based Early Childhood Care and Education Project (1990-1993) was undertaken in December 1993, with professional and financial support of the Bernard Van Leer Foundation (National Centre for Early Childhood Education, Report of the Samburu Community-Based Early Childhood Care and Education Project 1990-1993, December 1993). The evaluation covered a sample of facilities managed by the project and did not therefore provide independent estimates of the district’s pre-school enrolment. 2.24. The studies highlighted above have played an important role in providing some insights into the status of pre-school education. However, the evaluations were mainly done with specific purposes e.g. to serve the interests of a particular sponsor. The studies are limited on the degree to which the results could be generalized as to represent the whole of Kenya. The studies also vary considerably in scope, coverage, and time of investigation. First, the methods used in selecting districts and pre-schools vary from objective to subjective/purposeful selection. Secondly, the respondents differed from study to study. Third, the period when data were collected was different for each study. In addition, some of the research personnel were from the NACECE/DICECE, which might limit the degree of objectivity in data collection and in
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interpretation of the research findings. The evaluations also used the official statistics on pre-school enrolment compiled by the Ministry of Education as inputs to the evaluations, but did not attempt to collect basic enrolment data during the evaluation process. REVIEW OF OFFICIAL STATISTICS ON PRE-SCHOOL EDUCATION 2.25. To compile statistics on early childhood care and development, District Education Offices use DICECE and Zonal Officers to collect data on enrolment, teaching force and number of pre-schools. A district only submits annual summary figures for the district’s early childhood education’s enrolment broken down by sex of child; teaching force by whether trained or untrained; and number of pre-schools. 2.26. The reported enrolment for 1994 was 951,997, with male enrolment (485,352) being marginally higher than that of female children (466,645). A rough estimate based on official enrolment statistics and the population in the 3-6 year age group gives a national gross enrolment ratio of about 35%. 2.27. Although the reported statistics on early childhood care and development serve some purposes, they have many gaps and discrepancies. For example, there are no facility-based data submitted from the districts, making it impossible to verify any queries due to the nonexistence of primary data at the Ministry’s headquarters. Also, the data disseminated do not always include age of the children, and are not therefore limited to those children between 3 and 6 years attending early childhood education centres. The estimates therefore refer to gross rather than net enrolment. 2.28. There are also several discrepancies in the enrolment figures compiled annually by the Ministry of Education. Text Table 1 and Statistical Appendix Tables 1 to 5 show reported enrolments by sex for reference years 1990-94, while comparison of 1993 and 1994 pre-school statistics are given in Statistical Appendix 6. Three possible errors are evident from the data:
(a) There are various cases of same reported enrolment for two or three years in succession. This was true for Mombasa (1991 and 1992), Kilifi (1991 and 1992; 1993 and 1994), Machakos (1993 and 1994), Thika municipality (1991 and 1992), Nyandarua (1990 and 1991), Uasin Gishu (1990 and 1991), Eldoret municipality (1990, 1991 and 1992), Kitale municipality (1990, 1991 and 1992), Kisumu municipality (1991 and 1992), and Narok (1993 and 1994).
(b) Some reported enrolments behave in an erratic manner. In the case of Nairobi, reported
enrolment rose from 34,536 in 1990 to 45,497 in 1993 and dropped to 35,935 in 1994. Nakuru district’s reported enrolment had a higher noise than Nairobi.
(c) The total reported enrolment in Narok for reference years 1990-94 all end with “5”, which is
certainly suspect.
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Text Table 1: Reported Enrolment in Pre-Schools, 1990-94 DISTRICT 1990 1991 1992 1993 1994 Nairobi 34,536 35,476 42,987 45,497 35,935Mombasa 17,850 25,690 25,690 25,256 25,306Kilifi 19,699 21,167 21,167 21,566 21,566Machakos 65,008 63,597 33,293 35,737 35,737Thika Municipality 2,280 2,509 2,509 2,982 2,717Nyandarua 19,947 19,947 20,245 24,292 24,885Nakuru 36,236 35,763 33,833 38,033 37,007Nakuru Municipality 5,495 7,849 8,357 8,607 9,547Uasin Gishu 18,106 18,106 18,906 16,624 15,521Eldoret Municipality 4,369 4,369 4,369 6,181 4,738Kitale Municipality 3,063 3,063 3,063 2,175 5,549Kericho 40,082 44,730 44,750 17,996 20,072Kisumu 16,868 21,444 22,316 23,170 21,015Kisumu Municipality 5,825 6,893 6,893 8,530 9,638Narok 14,335 14,885 15,855 15,455 15,455Kakamega 51,704 60,752 40,873 39,344 42,434Garissa 1,529 3,120 3,120 1,923 3,494
Note: In the table, the data for Machakos/Makueni for the period 1990-91, Kericho/Bomet (1990-92), and Kakamega/Vihiga (1990-91) are reported under Machakos, Kericho and Kakamega, respectively.
2.29. Further analysis of reported enrolment reveals more discrepancies. In the case of Kwale, for example, the estimated growth rates of enrolment, number of trained teachers, number of untrained teachers, and number of pre-schools during 1993-94 at 37.6%, 44.1%, -31.8%, and 24.9%, respectively, appear too high to have occurred within one year. In the case of Kajiado, reported enrolment, teachers and number of pre-schools for 1992 all end with “0” which is highly unlikely. 2.30. The reported statistics on pre-schools are not compiled on the basis of any official guidelines. For example, there is no standard definition of an ECCD centre. Turkana district includes feeding centres within reported statistics on pre-schools. This gives a high reported enrolment rate compared with arable areas of the country where such feeding may not be necessary. Secondly, although pre-school statistics refer to number of “trained” and “untrained” teachers, there is no standard classification scheme of pre-school teachers, and such categorisation is therefore at the discretion of the field officers who compile the statistics. 2.31. Thirdly, unlike statistics on primary and secondary schools which are based on a single reference period (March of the index year), there is no standard reference reporting date/month for statistics of pre-schools. It is obvious that centres are likely to enrol more children at the beginning of the year, and reported data which do not have a common reference date are likely to display a lot of “noise”. In the case of Nairobi, most of the children under ECCD centres run by the City Council vanish in July after they are enrolled for Primary Standard One for the following year, thereby displaying wide variations in statistics depending on the date the statistics are compiled. The wide annual variations in the statistics on pre-schools are likely to be a statistical illusion due to lack of guidelines in compiling the statistics.
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CHAPTER 3: CONCEPTS AND DEFINITIONS USED IN THE ECCD SURVEY 3.1. The ECCD sample survey used a questionnaire and enumerators’ reference manual to collect the requisite data. In an effort to reduce enumerator variance, i.e. collect comparable data in respect of every responding centre, important variables and concepts were defined and included in the enumerators’ reference manual. Below are some of the concepts used as a guide in data collection. Further details are to be found in the enumerators’ reference manual. 3.2. ECCD Centre: The unit of analysis of the survey shall be the ECCD centre. This is a place where a group of children aged under-6 years are under the care of an adult. The centre could be a classroom attached to a primary school, a church, a social or special hall, a garage, backyard, someone’s house, or under a tree. Some of the common labels used to define ECCD centres include “day-care centres”, “crèche”, “nursery schools”, “day nurseries”, “kindergartens”, “play schools”, “play-groups”, “pre-primary units”, “duksi/madrassa” and Montessori schools. For the purpose of the survey, both duksi/madrassa and Montessori are types of service. The different types of centres are discussed below: - In a rural setting, nursery schools normally refer to programmes for children under-six years while
the normal rational age in urban centres is below four years. Nursery schools are also known as day nurseries and play groups.
- Kindergarten is a German term which refers to education programmes for young children similar to
those offered in nursery schools. - Day-care centres normally refer to centres which offer programmes for children who are under three
years of age. - Crèche refers to institutions which mainly provide care to young children aged between six months
and three years while mothers are away or at work. - Pre-primary units provide education and care to children aged 5-6 years and are normally attached to
a primary school where children gain direct entry to Primary Standard One. Such children may or may not have previously attended nursery school education.
- Pre-school is the conventional term for programmes of young children between 0 and 6 years, and
encompasses all types of ECCD centres. 3.3. Ownership: In this survey, ownership is categorized as either private or public. A private ECCD centre is one which is owned by an individual or private firm while a public ECCD centre is one which is owned by the community and could also be getting support from other sponsors. 3.4. Management of the centre: The management of an ECCD centre refers to a person or persons who carry out the day-to-day administration of the centre. A committee could be elected or appointed by the community or its owners to manage the centre. For ECCD centres attached to a primary school, a headteacher of the parent primary school could be managing the centre. The headteacher of the centre could also be managing the centre. Other managers could be religious leaders, individuals, companies, etc. 3.5. School Committee: A school committee consists of members elected by parents and is charged with the responsibility of running the school. Some of the functions of such a committee are: organizing and collecting of funds and fees, matters pertaining to staff recruitment and discipline, and payment of staff salaries/wages. Usually, a pre-school attached to a primary school is served by the same committee as the primary school. However, an ECCD centre which is not attached to a primary school assumes autonomy and is expected to have its own independent school committee.
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3.6. Sponsorship: A sponsor is taken to be a community, company, organization, or individual, who contributes in cash, kind or time, for the welfare of the institution without expectations of direct personal benefit. The sponsor takes interest in the quality of the centre’s services and is therefore expected to monitor its progress. Sponsorship includes contributions by parents/guardians over and above compulsory fees fixed by the community or sponsor, but excludes contributions to private pre-schools by their proprietors. For the purpose of the survey, a sponsor contributes part or full payments for regular/operating costs of the centre e.g. teachers’ salaries, other workers’ remuneration, school feeding, etc. Sponsors include local authorities (County/ Municipal/ Town/ Urban councils), central Government, religious organizations, community/parents, private company, plantations/estates and other companies, and NGOs. 3.7. Type of neighbourhood: The sample of ECCD centres will be located in urban slums or urban non-slum, and rural plantation or rural settled agriculture or rural pastoralist. A slum is an informal, unplanned and overcrowded settlement, with (a) structures of temporary material, (b) poor sanitation (e.g. sewerage, water supply), (c) poor basic infrastructure e.g. access roads and health facilities, and (d) inhabited by low income households. Among major urban centres, Nairobi has the greatest concentration of slum populations. The oldest and the largest slums, which are on Government land, such as Korogocho-Kariobangi and Mathare, have some of the poorest conditions. A number of slums developed later in the west of the city, mainly Dagoretti (e.g. Kawangware, Riruta and Kangemi), while the more recent slum areas settled to the north are Garba, Githurai and Kahawa. 3.8. Supervision/Inspection: Whereas local communities are mainly responsible for the establishment and running of schools, the responsibility of supervision and inspection of schools and colleges is vested in the office of the Chief Inspector of Schools. At the district level, the school inspectors, Zonal Inspectors (formerly known as assistant primary school inspectors), and DICECE staff undertake inspection of pre-schools among their other responsibilities. Nursery School Supervisors employed by local authorities also undertake supervision and inspection of pre-schools. In some areas, supervision is done jointly by the various supervisory teams. 3.9. Attachment/Linking to a Primary School: An attached ECCD centre shares the same compound with a mother primary school, and may or may not have its own headteacher. A linked ECCD centre is not in the same compound with a primary school, but is recognized by the primary school to which it is linked as a “feeder” for the purpose of Primary Standard One intake. A headteacher of a primary school attached to a pre-school normally assumes the overall responsibility of the welfare and development of both the pre-school and the primary school. A headteacher of a pre-school which is linked to a primary school assumes the overall responsibility for the centre, but would be expected to be answerable to the headteacher of the linking primary school for professional and administrative support. 3.10. Teacher Training: From independence through 1970, candidates with primary school terminal examination certificate constituted the majority of trainees in teacher training colleges. After successfully completing their two-year training courses, the trainees were graded as primary school teachers grade 3 (P3). Holders of Kenya Junior Secondary Examination (KJSE) certificate, sat after completing Secondary Form II, were trained for two years as primary school teachers grade 2 (P2), while holders of Ordinary level school certificate or its equivalent were trained for two years as primary school teachers grade 1 (P1). Holders of Ordinary level school certificate or its equivalent were trained for three years as secondary school teachers grade 1 (S1), while holders of higher school certificate or its equivalent were trained for one year as S1 teachers. P4 teacher training certificate holders were trained for two years and were drawn from primary school leavers who either did not have the terminal examination certificate or had not completed the primary school cycle. 3.11. ECCD-specific training: Training of ECCD teachers is carried out by DICECE trainers. The teachers undergo a two-year in-service course consisting of six residential sessions, alternated by five field experience sessions. The residential sessions are conducted during school holidays in April, August and December. During the residential sessions, the trainees are exposed to various skills and knowledge on early
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childhood care and education and are expected to practise these skills in their schools during the term time. The trainers continuously monitor the teachers during the field experience to ensure that the teachers are able to put into practice what they have learned. Other organizations that provide or facilitate training of ECCD teachers include Kindergarten Headmistresses Association, National Youth Service, Montessori, and Presbyterian Church of East Africa (PCEA). 3.12. Disability: A disability is a limitation in an individual’s ability to perform an activity in a manner that is considered to be normal. Impairment is an abnormality in the structure or function of a part of the body or mind. Disabilities are caused by impairments, which are in turn caused by diseases, injuries or congenital (inborn) or peri-natal conditions. Disabilities reported in the survey of ECCD centres should have had duration of at least six months. Disabilities can be: Difficulties in seeing (visual defects)
Includes all people who have difficulty in seeing and the completely blind
Difficulties in hearing Includes all people who have difficulty in hearing and the completely deaf Difficulties in speaking
Includes all people who have difficulty in speaking and those who have complete loss of speech, excluding stammerers/ stutterers (with difficulties in pronouncing words beginning with certain letters such as B, D, G, K and V) e.g. those who skip letter K
Difficulties in moving Includes all people who have difficulty moving their limbs and trunk, or moving from place to place
Mental retardation Includes conditions which affect a person’s ability to learn, to acquire knowledge and to adapt to environment which other people of the same age and within the same environment are able to cope with
3.13. Immunization: The objectives of the Kenya Expanded Programme on Immunization (KEPI) is to ensure that all children are vaccinated against measles, polio, tuberculosis, tetanus, diphtheria and pertussis, by the first birthday. Primary healthcare facilities are widespread in all the districts to ensure delivery of quality immunization services throughout the country. At the age of one, a fully-immunized child should have received Bacille Calmette-Guerin (BCG) against tuberculosis and polio I at birth, polio I/II/III, and DPT I/ II/III (against diphtheria, pertussis and tetanus). Oral polio vaccine is given four times beginning at birth (polio 0), at 6 weeks (polio 1), at 10 weeks (polio 2), and at 14 weeks (polio 3). DPT is given three times, at 6 weeks, at 10 weeks and 14 weeks; and measles at nine months. A “booster” immunization of Polio and DPT is given after 5 years. According to the recommended immunization timetable, children entering ECCD centres should all have been fully immunized. KEPI provides immunization cards for each child on which a record of the immunizations is entered. 3.14. Child Growth Monitoring: Growth Monitoring and Promotion (GMP) ensure early detection of children’s development, health and nutritional problems. In GMP, children’s weight and height are taken against the age of the child and the results plotted on a graph. One of the greatest successes of GMP is its ability to detect malnutrition at its earliest stages, which helps to avert problems at lower cost. 3.15. School Feeding: The main objective of the school feeding activities is to provide food supplements to pre-primary and primary-school children in order to help improve their health and nutritional status and provide them the energy to participate in school, particularly in food-deficit areas. Pre-school centres have been used to provide supplementary feeding to improve the nutritional status of children and prevent malnutrition. Since the 1950s many pre-schools, for example, in central Kenya and former African estates in Nairobi were started as feeding centres which also provided some custodial care to children. In the arid and semi-arid areas and the poorer sections of the urban community, a number of organizations provide feeding programmes in the pre-school centres.
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CHAPTER 4: SAMPLE DESIGN AND IMPLEMENTATION SAMPLE DESIGN 4.1. The initial requirement was to select 800 centres from all the districts of Kenya, representing (i) major urban areas of Nairobi, Mombasa, Kisumu and Nakuru; (ii) other urban areas of Thika, Kitale and Eldoret; (iii) pastoral areas; (iv) settled agriculture; and (v) plantation agriculture. Selection of centres in urban areas was to be designed in such a way as to include centres from slum areas. 4.2. This initial sample design was slightly modified. First, the sample size was increased from 800 to 900 centres, so as to allow for nonresponse. Secondly, it was decided to select a purposeful sample of 10 rural districts in addition to pre-selected major and other urban centres, namely, Nairobi, Mombasa, Kisumu, Nakuru, Eldoret, Kitale and Thika. Selection of the 10 districts was to be made in such a manner to at least include centres representative of pastoral, plantation and settled agriculture. Selection of Districts 4.3. To allow inclusion of districts representing various types of agricultural settlements, it was decided to group the districts into agro-ecological zones. The agro-ecological zoning served as a proxy for main agricultural activities carried out within a district e.g. pastoral, plantation, and settled agriculture. Classification of the districts into broad agro-ecological zones was made using the Farm Management Handbook (Ministry of Agriculture, 1983). The Farm Management Handbook divides Kenya, excluding the whole of North Eastern province and Isiolo and Marsabit districts of Eastern province, into 50 possible agro-ecological zones. Since information in the Farm Management Handbook shows that no district is composed of only one agro-ecological zone, a district was classified on the basis of the most dominant agro-ecological zone. The following distribution was arrived at: AGRO-ECOLOGICAL ZONE
DISTRICTS
Upper Highland Nyandarua Lower Highland Kisii, Bungoma, Meru, Kericho, Laikipia, Nakuru, NyeriUpper Midland Kakamega, Nandi, Trans Nzoia, Uasin Gishu, Kiambu, Murang’a, Kirinyaga Lower Midland South Nyanza, Kisumu, Siaya, Busia, Embu, Machakos, Kitui, West Pokot, Keiyo
Marakwet, Narok Lowland and Inner Lowland Kwale, Kilifi, Taita Taveta, Lamu, Tana River, Baringo, Samburu, Kajiado 4.4. Other considerations made in arriving at the selection of districts was knowledge of main activities that are carried out within a district e.g. pastoralism or plantation. For ease of sample administration, it was decided to include districts in which the major and other urban centres are located (other than Nairobi and Mombasa), and to consider provincial representation and the total number of districts in each agro-ecological zone. Taking these limitations into account, the following 10 districts were selected: AGRO-ECOLOGICAL ZONE DISTRICTS Upper Highland NyandaruaLower Highland Kericho (also representing plantations), Nakuru Upper Midland Kakamega, Uasin Gishu, KiambuLower Midland Kisumu, Machakos Lowland KilifiLower Midland Narok (also representing pastoral) 4.5. The initial selection did not include North Eastern province because it is not covered in the Farm Management Handbook. It was therefore decided to replace one of the selected districts with a district in North Eastern Province. Since Upper Midland was well represented in the initial sample, Kiambu district was replaced by Garissa district.
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Sample Selection 4.6. The first activity in the sample selection exercise was creation of a sampling frame. Since no listing of ECCD centres was available at the Ministry of Education headquarters in Nairobi, the DICECE officers were instructed to submit a listing of ECCD centres in their districts showing the following information: name of ECCD centre, Division and Zone in which the centre is situated, sponsor, and address. However, the lists submitted by the DICECE officers did not give details as to whether a centre was located in an urban slum, other urban, rural pastoralist, rural plantation or rural settled agricultural areas. It was therefore decided to treat neighbourhood/location of an ECCD centre as a characteristic to be investigated. 4.7. The total number of ECCD centres included in the lists from the districts/municipalities was 6,009. Upon receipt of the lists, the first step was to organize the district/municipality lists by reported sponsor. The groupings by sponsor were then treated as strata for the purpose of sample design. The use of the term “strata” below will refer to classification of ECCD centres by sponsor. 4.8. The second step was to distribute the recommended sample of 900 ECCD centres among the districts. This was done by distributing the 900 ECCD centres to each district by its proportion to the total number of ECCD centres in the lists from all the study areas, i.e.
ni = 900*Ni/ΣNi where
ni is the sample size of ECCD centres in district i Ni is the total number of ECCD centres in district i, and ΣN is the total number of ECCD centres in all 17 districts/urban centres, in this case 6,009 centres.
4.9. In the case of Machakos, for example, the sample of 137 was arrived at as 916 ÷ 6009 x 900, where 916 was the total number of ECCD centres in the list submitted by Machakos district, 6,009 was the total number of ECCD centres in all the lists submitted by all districts/municipalities covered in the study, and 900 is the total sample size. This was repeated for each district. 4.10. The third step was to split the total district sample into the various strata. Distribution was also made proportionate to the size of each stratum. For example, in the case of Machakos, estimation of the sample of parents/community ECCD centres was arrived at as 781 ÷ 916 x 137. The results are shown in Statistical Appendix Table 7 against “n”. 4.11. Some characteristics of the centres e.g. enrolment size, management and supervision, were expected to be dissimilar across different sponsors (strata). Therefore, stratification of the ECCD centres within a district was carried out in order to make the centres under each type of sponsorship internally homogeneous. In this way, stratification was expected to introduce a gain in precision in the district/municipality estimates of the various characteristics of the ECCD centres. 4.12. Having stratified the ECCD centres by sponsor, the centres were numbered sequentially within a district starting from community-sponsored centres, then local authority, religious organizations, private, and finally other sponsors. The required sample was generated by use of systematic selection, instead of a true random selection. In a systematic selection procedure, let the district’s population size be N and the desired sample size be n. The sampling interval (k) is N/n (an integer), and the probability of selection is 1/k. The random start number (r), which was generated using random number tables, ranged from 1 to k. The sample of ECCD centres was systematically selected from a random start at the district/municipality level. The systematic sample generated by taking every kth centre after a random start from 1 to k is equivalent to a proportionate stratified random sample since the centres in each stratum were not ordered in some way. 4.13. However, the random sample for Garissa district was rejected by field personnel due to perceived insecurity in some of the areas far from Garissa town. The consultants agreed with the World Bank and the Ministry of Education to cover only Central Division, but covered more centres in the Division (15) than the
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entire sample previously selected for the whole of Garissa district (9). ESTIMATION PROCEDURES Blanks and Nonresponse 4.14. There are various sources of errors/bias in a sample survey. Errors could be introduced by misreporting, lack of data, enumerator or respondent bias, nonresponse, and in data entry. This section deals with nonresponse and its effects on sample weights. In the survey of ECCD centres, nonresponse was introduced through refusals, failure to locate a centre, and closures. Although it is difficult to rule out inclusion in the frame (N) of some centres which had been closed before the frame was constructed (i.e. out of scope) since closure dates were not known, it was decided to treat the sample frame (N) as a true report of the number of ECCD centres in June 1995. Therefore closures, refusals and failure to locate, were summed as nonresponse (r). 4.15. Filled survey and census questionnaires may contain blanks or missing values attributable to lack of data or a question that was not asked. Blanks and nonresponse splits the original population (N) into two subclasses, M non-blank members and B blanks and nonresponse, i.e. N=M+B. The presence of blanks and nonresponse introduces variation in the size of the sample. This variation is a function of the proportion m=M/N. However, the selection interval (k) and selection fraction (1/k) do not change since the blanks and nonresponse were identified after the original sample had been selected. Weighting 4.16. In each sample, each element had an equal chance of selection. Therefore each element has the weight of 1 in the sample total, and F=1/f in the population total, where f is the selection fraction. As stated above, the term “stratum” refers to classification of ECCD centres by sponsor. The basic weights, before adjustment for nonresponse, are the reciprocals of the probabilities of selection, i.e.
wij=mij/nij where
wij is the weight in district i stratum j; mij is the total number of ECCD centres in district i stratum j; and nij is the sample size in district i stratum j.
4.17. In producing survey estimates, the basic weights were adjusted for nonresponse to arrive at final adjusted weight, which is the product of the basic weight and a nonresponse adjustment factor. The procedure of calculating the nonresponse (nr) factor for each district was as follows:
nrij = nij/iij where
nrij = Nonresponse adjustment factor for district i stratum j; nij = Total number of originally selected ECCD centres in district i stratum j; iij = Number of ECCD centres which responded in district i stratum j.
The adjusted stratum and district weights are waij = wij * nrij = (mij/nij)*(nij/iij)=mij/iij and wai = mi/ii, respectively, i.e. the total number of ECCD centres in district i divided by the number of centres which responded. 4.18. As detailed above, proportionate sampling procedure was used in order to ensure that the ECCD sample was representative of the different types or categories of centres. Use of proportionate stratified sample ensured that the sampling fraction in each stratum was equal to the sampling fraction for the universe
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(i.e. the total number of centres in the selected districts and municipalities), except for Garissa1. This procedure also ensured a self-weighting sample and that all strata in each district were represented in the total sample in the ratios of the strata in the universe. 4.19. The estimated weights refer to 1995, since the sampling frame was constructed using the list of ECCD centres supplied by DICECE staff for 1995. A review of the Ministry of Education’s annual data on the number of pre-schools show that there has been substantial growth in the provision of Early Childhood Care and Development in the last decade, while some pre-schools have also closed during the same period. It was therefore decided not to use 1995 sample weights to gross-up 1990-1994 enrolment. 4.20. Reliability of the sample results could be derived from sampling errors or from comparisons with enrolment figures compiled annually by the Ministry of Education. Statistical Appendix Tables 2 to 4 shows reported enrolments by sex for reference years 1990-94. However, as shown in Chapter 2, there are possible errors e.g. (a) there are various cases of same enrolment figures reported for two or three consecutive years; and (b) year-on-year changes in reported enrolments behave in a sporadic manner for some districts/municipalities. In view of the above observations, it was decided not to use reported enrolment figures as a check on the reliability of the weighted enrolments derived from the survey. Limitations of the Sampling Frame 4.21. At the beginning of the study, the consultants were provided with a summary of the total number of ECCD centres in each district for reference period 1994. However, the district field staff later forwarded the ECCD centres arranged by name and sponsor. Comparison of the district and municipality totals from the two lists revealed some discrepancies, as shown in Statistical Appendix Table 8. The disparities between the two lists, especially where the number of centres dropped significantly between 1994 and 1995, means that the 1995 list might have some omissions. Such omissions, which are not necessarily uniformly distributed among the strata, would affect both the district weight allocated and the relative weights allocated to each stratum in the district. 4.22. Intuitively centres which were likely to be omitted from the sample frame in the urban areas were recently established, small, private, and operating from a residential building. In the rural areas, it was likely to be the recently established, community-sponsored centres, which may have registered with the Community Development Officers but had not yet registered with the Ministry of Education. Other possible reasons for omission were centres operating under the umbrella of a large company, in a church, or under a tree. The exclusion of such centres from the sample frame is therefore not likely to introduce significant errors in enrolments computed from the survey data. 4.23. During the development of the survey instruments (questionnaire, enumerators’ reference manual), it was necessary to define major concepts, such as sponsor. The search revealed that there was no commonly-accepted definition of “sponsor”. The classification of ECCD centres by sponsor was further complicated by joint sponsorship e.g. by community and local authority. The consultants fear that it is possible for a centre drawn from the local authority stratum to be re-classified under the community stratum during the enumeration. Such re-classification would make the weight allocated to each stratum different from the true weight. 4.24. The list of ECCD centres submitted by the district staff did not categorize the centres by type of neighbourhood i.e. urban slum, other urban, rural pastoralist, rural plantations, and rural settled agriculture. 4.25. The definition of an urban centre used in the ECCD survey differs from that used by the Central Bureau of Statistics (CBS). The CBS defines an urban centre as a built-up and compact human settlement
1. Rounding of the strata sample to the nearest integer introduces slight departures in the values
of actual sampling fractions. However, this trivial departure is usually ignored (see L. Kish, Survey Sampling, John Wiley & Sons, New York, 1965).
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with a population of at least 2,000 people. On the basis of this definition, 148 centres were classified as urban based on the 1989 Population Census (see Kenya Population Census, 1989: Volume II, Central Bureau of Statistics). In the ECCD survey, only Nairobi, Mombasa, Kisumu, Nakuru, Eldoret, Thika and Kitale are classified as urban. As shown in Statistical Appendix Table 9, this classification omits 40 urban centres in the selected rural districts which were reported as having 2,000 or more persons in 1989. As a result of this limited definition of an urban centre, the rural sample will also contain urban ECCD centres from omitted urban centres e.g. Malindi, Machakos, Naivasha, Nyahururu, Kericho and Kakamega towns. 4.26. Further, the extent of urban areas in Kenya is based on administrative boundaries regardless of the nature of the population within and outside the areas adjacent to the boundary. There have been boundary extensions of various urban areas, which have introduced into urban centres populations that are basically rural on the basis of their socioeconomic characteristics. Data from the 1979 census show that the population of Machakos “Old Town” (the area which is basically urban) was 9,645 against a total or 84,320 in the extended Machakos town. Inclusions of rural populations are also evident in other towns e.g. Meru and Kakamega. It can therefore be concluded that failure to define as urban ECCD centres in urban areas of Kakamega, Kericho, Machakos and Kilifi may not adversely affect the representativeness of the urban and rural samples in the ECCD survey. 4.27. The urban areas which reported populations of over 50,000 in the 1989 population census were Nairobi (1,324,750), Mombasa (461,753), Kisumu (192,733), Nakuru (163,927), Machakos (116,293), Eldoret (111,882), Meru (94,947), Nyeri (91,258), Kakamega (58,862), Thika (57,603), and Kitale (56,218). Using population figures, the urban areas covered in the survey were split into (a) major urban: Nairobi and Mombasa, and (b) other urban: Kisumu, Nakuru, Eldoret, Thika and Kitale. The urban areas covered in the survey are the only urban local authorities entrusted with undertaking functions with respect to education within their areas of jurisdiction as per Legal Notice No 50 of 1970, made under the Education Act, cap 211 of the Laws of Kenya. 4.28. The size of the sample at the national level was rather small, and the resulting estimates from the sample might be expected to have wide confidence limits, and no attempt was therefore made to provide estimates at the national level. However, some survey results e.g. enrolment and teachers, were estimated at the district/municipality level where the sampling fraction was around 15%.
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CHAPTER 5: SURVEY DESCRIPTION AND ORGANIZATION
DEVELOPMENT OF THE SURVEY INSTRUMENTS
5.1. The Terms of Reference gave a list of 28 variables to be investigated, and 11 outputs to be covered by the sample survey. Therefore, the first activity in the development of the questionnaire and the enumerators’ reference manual was a review of the literature on early child care and development, and interviewing of relevant personnel in NACECE, Ministry of Education headquarters, and some DICECEs. 5.2. The ECCD survey questionnaire is composed of seven sections with 61 questions. Section 1 of the questionnaire collects each centre’s identification particulars, and seeks basic information in the form of sponsorship, management, structure of school committees, and supervision. Section 2 seeks enrolment data and fees structure. Section 3 seeks information on staff and staff turnover. Section 4 seeks financial data mainly on operating and capital costs. Section 5 seeks information on school feeding. Section 6 seeks information on health interventions and number of children with major disabilities; and Section 7 attempts to capture inventory of facilities. 5.3. After the questionnaire was drafted, it was circulated to all interested parties in the Ministry of Education and the project office within the World Bank. As a result of the comments received and insights gained from the pre-tests, the final version of the questionnaire was drawn up. After the questionnaire was developed, the consultants prepared a checklist to illustrate how the questionnaire responded to the issues in the Terms of Reference. A copy of the questionnaire is given in Annex 8, while the checklist is given as Annex 3 to this report. 5.4. In respect to the institutional arrangements at the ECCD centres, it was agreed between the consultants and the client that the approach was first to establish whether a certain institutional arrangement exists, followed by an assessment of whether that arrangement is functional. For example, Question 111 solicits information on whether the centre has a parents/school committee, while Question 113 is on when the parents/school committee last met. Question 114 is on whether the centre is attached to a primary school, while Question 115 wants to understand the nature of the relationship with the primary school by asking whether the headteacher of the pre-school attends staff meetings of the primary school. A similar approach was taken with respect to a centre’s supervision. 5.5. An enumerators’ reference manual was designed to guide interviewers in the data collection exercise. The manual explains the roles of supervisors and enumerators, and the flow and control of questionnaires to and from the field. The manual described the concepts used in the survey and the procedures followed in filling each section of the survey questionnaire. A copy of the manual is given as Annex 7 to this report.
PRE-TEST
5.6. It is difficult to execute a survey without sufficient knowledge of the subject matter, the universe it is to cover, the way respondents would react to questions, and the answers they are likely to give. In terms of survey design, it is difficult to know how long the administration of the questionnaire would take and the number of interviewers required without conducting trial interviews to provide guidance on these issues and other aspects of field logistics. It was for these reasons that a small pre-test was conducted. 5.7. Pre-tests were conducted within Kiambu municipality in six ECCD centres selected by the DICECE officer, and representing different sponsors, namely, community, local authority, private, and plantation. The aim was to test the survey questionnaire so that any defects could be rectified before the main survey. Other objectives included testing the efficiency of the field planning, and to give useful training to the field staff. The results of the pre-tests were used to refine the survey instruments. Based on the findings of the pre-test,
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some parts of the questionnaire and enumerators’ reference manual were revised. The findings also assisted in knowing how long the administration of the questionnaire would take, the number of interviewers required, and in planning other field logistics. 5.8. The findings of the pre-test led to amendment of the questionnaire, and deletion of two variables which were itemized in the Terms of Reference, namely, the registration number of the ECCD centre and the responding centre’s catchment population age 3-6 years. Although all pre-schools in the pre-test were reported as registered, none of the centres reported as knowing its registration number. The question on registration number was therefore deleted for fear that it would affect cooperation of respondents and the quality of data collected. Secondly, all headteachers interviewed were unable to give reliable figures on the catchments population aged 3-6 years, since a number of ECCD centres were serving the same catchments area. The question was deleted, and the estimates of the target age-group were to be derived at the district level from projected population aged 3-6 years. 5.9. The Terms of Reference also referred to capital costs of the school facility split into building materials, land, furniture and equipment, and an indication of whether the cost of labour was contributed by the community. However, the pre-test showed that centres do not normally keep records on costs of construction materials and the donors who contributed various resources to put up the centre. In addition, construction of some centres took many years to complete, and adjustment for price changes would have to be made to arrive at current values. The final version of the questionnaire settled down to estimates of current market value. This approach raises the issue of the realism of the respondents’ estimates, since they were teachers and not land valuers.
SURVEY ORGANIZATION
5.10. The sample survey of ECCD was coordinated by the Ministry of Education. The District Education Officers and most of the DICECE field personnel were involved in coordination and supervision at the district level. The use of DICECE officers assisted by (a) giving authority to the survey and thus ensuring cooperation of the respondents, and (b) reducing the time taken to locate a centre because they were familiar with the locations of the selected centres. In all, data collection activities involved about 100 enumerators and 17 main supervisors. 5.11. Recruitment of interviewers took place at either the DEOs or DICECE offices in the selected districts and municipalities. In the recruitment of interviewers, preference was given to residents of particular districts in which the survey was to be conducted. This reduced transport and accommodation costs, but of more importance, having a local interviewer avoided undue suspicion and hostility to the survey. Most of the enumerators were university graduates recruited on part-time basis from their respective districts and municipalities. 5.12. Training of supervisors and enumerators for Nairobi was completed on 21 June 1995, and the trained enumerators conducted mock interviews on 22 June, 1995. Training of supervisors and enumerators for Machakos district was completed on 26 June 1995, and data collection started on 27 June 1995. Training for other districts and municipalities (except enumerators for Kilifi, Kakamega, Uasin Gishu and Kisumu municipality) was completed on 29 June 1995, while training for the remaining areas was conducted in early July 1995. 5.13. At the end of each training session, the interviewers and field supervisors were given enumerators’ reference manuals, survey questionnaires, list of selected ECCD centres, and a letter of introduction as official interviewers. Enumerators were instructed to return completed, blank and incomplete questionnaires to their respective supervisors who were to check them for completeness.
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FIELDWORK
5.14. The actual data collection started earlier for Nairobi and Machakos district. Data collection for other selected districts and municipalities followed later. The field operations were to take five working days. Given the tight schedule, each enumerator was expected to collect information from 2 ECCD centres each day for rural districts, and 3 centres per day for urban centres. 5.15. The fieldwork did not run smoothly as planned. Due to problems related to distance between centres, transport, and difficulties in locating centres, each enumerator could on average cover one centre per day. There were a number of problems that affected the length of the fieldwork as outlined in the survey budget and work-plan. The time taken to collect data proved inadequate and the survey took on average about one month instead of the planned one week of 5 days. One of the problems that affected the enumeration period, particularly in urban areas, was the time taken to locate an ECCD centre. Difficulties in locating centres were contributed by the following factors, among others: (a) In some districts/municipalities, the sample frame was defective. In one urban area, it took an
enumerator four days trying to locate an ECCD centre, only to find out that the centre was closed in 1983.
(b) During training, the enumerators were instructed to ensure that they interview the correct centre.
The centre was to be identified through the use of the following particulars: Division, Zone and the exact name of the centre. There were isolated instances where the centres’ names had been misspelt, and were only interviewed after confirmation from DICECE records that the names had been misspelt.
(c) Some centres had shifted premises, especially in urban areas. It was first necessary to confirm with
the DICECE office so that the centre could be interviewed in its new locality. (d) Other centres were difficult to locate since they operated from hidden premises e.g. a room in a
residential building, without any external intimation of its locality (e.g. a signboard). 5.16. There was also commonality of names. When centres with the same name are located in one education zone, they are normally identified through a suffix to the names, e.g. Kamuyu “A”, “B” and “C” in Timboroa Zone, Ainabkoi Division, Uasin Gishu district. This type of suffixing was also noted in other districts, e.g. Kisumu, Nyandarua, Kericho and Machakos. Failure to append the suffix, either during preparation of the sample frame or at sample selection stage, brought confusion during field enumeration as the enumerators were not sure which centre to enumerate. This occurred in Machakos district, and the enumerators interviewed all the centres in the same zone bearing the same name. During data edit, it was decided to include three extra centres in Machakos district caused by this anomaly, thereby increasing its sample from 137 to 140. 5.17. There was one case in an urban area where the respondent refused to be interviewed even after the intervention of the DICECE officer. However, respondents in the rural areas were generally more cooperative compared to urban respondents. There were marked geographical differences in enthusiasm to respond, perhaps as a result of perceived benefits that could accrue from the survey. 5.18. The use of random sampling design at the district level resulted with a geographically scattered sample. In some districts such as Machakos, Nakuru, Kilifi and Uasin Gishu, one enumerator was to cover centres which were far apart due to sparse populations and the vastness of the district. In the rural areas, there were some routes that do not have regular public transport. The enumerators therefore covered long distances on foot. This increased the time taken to move from one centre to another, and was a delaying factor especially for centres which operate in the morning only. Call-backs or re-visits were more time-consuming since the centres became more scattered than in the original list assigned to an enumerator.
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5.19. Most of the fieldwork was conducted in July and early August. Although weather did not slow down the enumeration process in many rural districts, enumeration in Nyandarua was slow and had to be postponed in some areas as a result of heavy rains during the enumeration week. 5.20. There was perceived insecurity on the part of the supervisors and enumerators in at least three rural districts. Arrangements were made to provide security and transport to the respondents so as to reach the areas that the enumerators perceived as insecure. In one rural district, two centres were not interviewed since the pre-schools closed for second term holidays before logistical arrangements could be finalized to reach them. 5.21. Some data sought, e.g. enrolment, employment, and finance, referred to previous years. It was therefore necessary for the respondents to refer to past records. The majority of the centres either (a) did not have the records at all, or (b) the available records were not in the centres’ offices, which made re-visits necessary. 5.22. There were two cases of dishonesty on the part of the field personnel. An enumerator reported that a centre known to exist could not be located simply because it was too far from the road served by public transport. Secondly, in another area, when perusing the questionnaires, it was noticed that in three instances, the signatures of the respondents had been forged. Since the extent of the problem was not known, most of the centres in the area were revisited in an effort to determine whether the data for the responding centres should be analyzed. 5.23. Although the meaning of public and private ownership was given in the enumerators’ reference manual and emphasized during training, responses to Question 106 raised suspicions as to whether the enumerators fully understood the differences between the two terms. There were a number of centres that were reported as privately owned when other information in the questionnaire suggested that they were either owned by the community or religious organization i.e. should have been considered publicly-owned. In addition, although enumerators were supposed to probe on supervisor/ inspector of the ECCD centre (e.g. by asking the office/institution the supervisor/ inspector works with), there are chances of respondent error for those ECCD centres that had been supervised. 5.24. In Question 207, the use of the term “registration fee” rather than “admission fee” was confusing to the enumerators since it was not defined in the enumerators’ reference manual. However, this omission was rectified during training of supervisors and enumerators before the fieldwork commenced. 5.25. The Terms of Reference also required enumerators to differentiate centres by type of neighbourhood, i.e. urban slum, urban non-slum, pastoral, plantation, and settled agriculture. Lists of centres submitted during the preparation of the sample frame did not indicate type of neighbourhood. It is therefore possible that the response on the type of neighbourhood could have a large respondent/enumerator bias. For example, an area with agricultural activities located in an urban area could be interpreted as “settled agriculture” by one enumerator and “urban non-slum” by another. Such an error would be difficult to pinpoint if the urban area is located in a rural district e.g. Machakos.
DATA EDIT AND PROCESSING
5.26. One of the serious errors a survey could suffer from is loss of data. This may arise from loss of questionnaires, data storage equipment, or data outputs. To guard against such losses, the survey set up data control mechanisms. After each district’s/municipality’s sample was selected, the names of the centres were compiled by Zone and Division and entered into the computer. A six-digit identification code was assigned against each centre’s name: the first 3 digits represented the district e.g. Kilifi (102), Mombasa (106), Nyandarua (201), etc; and the last three digits represented the centre running sequentially from one (001) in every district. This became the survey’s district-specific checklist and the master sample control list. The list was also given to the respective District Education Officers/Municipal Education Officers and DICECE
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officers. 5.27. During training of enumerators, DICECE officers/survey supervisors were instructed that all questionnaires - completed, incomplete, spoilt and unused - should be returned to Nairobi at the completion of fieldwork. Upon receipt of the questionnaires, they were checked against the survey’s master control list, and the six-digit identification code entered on the top page of every questionnaire. The questionnaires were then filed by district/municipality to avoid loss or misplacement. The respondent’s signature on the Survey Control Form contained in the questionnaire was also checked to detect any possibility of forgery by the field staff. 5.28. The second step was a quick check on the completeness of the survey questionnaires including reasons given for incomplete or blank questionnaires. For cases where the field supervisors failed to give acceptable explanation as to why a questionnaire was incomplete or completely blank, such questionnaires were referred back to the field for further action. 5.29. The third step was to carry out manual editing of the questionnaires before they were cleared for data entry. The editing process involved checking for internal consistency, completeness of responses, and coding of open-ended questions. One check of internal consistency was to ensure that all teachers listed in Question 301 were also listed in Question 302, and each teacher’s unique serial number was carried over from Question 301. The use of the unique serial number allowed stringing of teacher’s particulars from Question 301 with those in Question 302. 5.30. Entries in Question 201 were checked to find out if (a) the age-specific totals agreed with respective year totals; and (b) that the age breakdown for 1995 agreed with that reported in Question 202. If the response to Question 117 was that a centre operated in the open or under a tree, the centre’s responses to Question 702 were checked to ensure that no roof, wall or floor type was reported. 5.31. In answer to Question 403 on total teachers’ salaries, some enumerators were totalling gross monthly pay in Question 301 and multiplying by 12 to obtain the annual figure. This approach was inexact for at least three reasons. First, Question 301 referred to salary in May 1995, while Question 302 referred to reference year 1994. Secondly, some teachers could have been in employment for less than a year. Thirdly, some community schools pay teachers for the months taught, i.e. 9 months. This should have been explained in the enumerators’ reference manual. However, the problem was noticed in Machakos in the first week of the enumeration exercise, and was rectified. The few errors from the omission were rectified during data edit. 5.32. During manual edit, an attempt was made to fill up blanks, i.e. impute missing information using responses from other parts of the questionnaire. For example, if no ECCD-related teaching experience was reported, this was equated to length of employment derived from date of appointment given in Question 301. Questions 108 and 109 sought information on the centre’s main sponsor from the point of view of who contributed most resources to the pre-school, other than compulsory school fees and charges paid by the parents. Only a small percentage of centres reported having received donations in cash or kind from sources other than school fees. Hence, Question 109 was skipped for most of the centres. The responses to Questions 402, 403, 404 and 407 were used to decide on the main sponsor. 5.33. Although most of the questions in the survey questionnaire were pre-coded, there were several questions which were open-ended, e.g. in Questions 301 (sex, main type of work and status of work), 302 (sponsor of ECCD-specific training), and 407 (main anticipated sponsor of planned improvements). It was therefore necessary to convert the responses to numerical codes before data entry commenced. For example, under Question 301, sex was coded to Male=1 and Female=2, while sponsor in Question 407 was coded on the basis of codes given in Question 109. The year of completion of ECCD training under Question 302 required special treatment for those who had not received any training and those who were undergoing training during the survey period. The year of completion for those who had not undergone training was coded “0000”, and the codes for those undergoing training was given the reference year when training is expected to be completed, e.g. 1996. The codes for open-ended questions are shown in Annex 1.
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5.34. Data were entered into the computer using SPSS. After completing data entry, the data entry clerks carried out data validation. However, consistency checks carried out after data validations revealed some errors. In an effort to produce an error-free data file, it was decided to re-check all entries and correct all wrong entries. 5.35. The questionnaire had a few typographical errors which did not affect the fieldwork, but were a nuisance to the data entry personnel. Although the option “other, specify” was given a generic code of “9” in the entire questionnaire, the code used in Question 107 was “6”. During data entry, the category was given either a “6” or “9” depending on the alertness of the data entry clerk. This anomaly was rectified during data validation. 5.36. Over 60 tables were prepared for the ECCD survey basic report. Data analysis was carried out using SPSS, and some data, e.g. estimated population aged 3-6 years and total number of ECCD centres in the lists submitted by the districts/municipalities, were entered extraneously to allow estimation of specific indices such as enrolment ratios.
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CHAPTER 6: ESTIMATION OF POPULATION AGE 3-6 YEARS BY DISTRICT/MUNICIPALITY
6.1. Some of the important indicators in the field of education which require age data are enrolment rates and age-grade mismatch. The gross pre-school enrolment ratio is the total number of children regularly attending pre-school in the current year divided by the total number of children of pre-school age (3-6 years). The net pre-school enrolment ratio is the total number of children of pre-school age (3-6 years) currently attending pre-school divided by the total number of children of pre-school age (3-6 years). The difference between gross and net pre-school enrolment ratios shows the children in pre-school who are not of pre-school age divided by the number of pre-school age children. 6.2. The age/grade mismatch shows the relation between age and school grade. If the children started school older than is normally the case, dropped out of school or repeated some grades in the past, the children will find themselves in grades inappropriate for their age. Other things being equal, age/grade mismatch is expected to be positively correlated with dropout rates (Mukui, 1994a). The age/grade mismatch for children in pre-schools is the ratio of those above pre-school age (i.e. greater than 6 years of age) to total pre-school enrolment. However, age/grade mismatch will not be computed in the ECCD survey since it is a more important statistic for primary and secondary schools due its high correlation with dropout rates. 6.3. One of the outputs expected from the ECCD survey are enrolment ratios for each district/municipality. Since the sample survey was establishment-based, it did not capture children of pre-school age (3-6 years) who were not attending pre-school. Enrolment ratios by district and sex will therefore be derived from estimates of total enrolments as reported by the survey and the estimated population aged 3-6 years in each district/municipality. 6.4. The Terms of Reference required that the population age 3-6 years in the pre-school’s catchments area be estimated by the headteacher of each respective ECCD centre. This approach was attempted during the pre-test but was discarded since it was difficult to precisely define the pre-school’s “catchments area” since the same catchments area was normally being served by more than one pre-school. It would therefore have been difficult to gross up the overall enrolment ratio based on the survey responses. In addition, even if a pre-school was to serve its own catchments area, the responses from the headteachers would be unreliable.
ALTERNATIVE METHODOLOGIES OF PROJECTING POPULATION AGE 3-6 YEARS
6.5. There are two main methods of making population projections: (a) projecting the size of age and sex groups of the population independently using the cohort survival method, (b) projecting using an observed rate of growth. 6.6. Since the population age 3-6 years in 1995 consists of survivors born between 1989 and 1992, population projections could be obtained through the use of cohort survival method by applying model life tables that are believed to represent approximately the mortality of the actual district/municipality population. The life table is a life history of a hypothetical group or cohort as it is diminished gradually by deaths. The record begins at the birth of each member and continues until all have died. Future births are estimated using projected female population in the reproductive age groups and projected age-specific fertility rates. 6.7. The cohort survival method disaggregates the population by sex and age cohorts. The method is based on the relation that a change in population between two points in time is entirely the result of intervening vital events - births, deaths and migration, i.e.
Pt+n = Pt + Births - Deaths + net Migration where;
Pt+n is the projected population at time t+n,
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t is the base period on which the population projections are made, n is the time interval, and Pt is the population at base period t.
To obtain district/municipality population estimates for 1995, it would first be necessary to compute the annual numbers of births occurring during the interval, deaths and net migration. Numbers of births would be calculated from fertility rates and numbers of women in childbearing age. 6.8. The CBS was approached to provide with either (a) tabulations of the 1989 population census which could be used to project the population, or (b) projected populations by age, sex and district. The CBS was in the process of analysing the 1989 Population Census and neither the results of the analysis nor the detailed census data from which to compute fertility and mortality rates and internal migration had been published. 6.9. An alternative source of the requisite data considered was vital registration records at district/municipality levels. This source of data was also not used since the vital registration system in Kenya has three unresolved issues: (a) the coverage is low in most districts; (b) out-of-district occurrences are usually not included in the events for the district of domicile of the mother; and (c) there is a time lag in the processing of vital registration data and are currently available for up to 1987. The cohort survival method could therefore not be used due to lack of readily available vital registration data. 6.10. It was, therefore, decided to compute population projections for reference years 1990-1995 for the age group 3-6 year by district using an observed rate of growth based on the published 1979 and 1989 census data. The methodology used assumed a geometric growth (r) between two numbers, Pt+n and Pt, where
Pt+n = Pt(1+r)n
Pt+n is the projected population at time t+n, t is the base period on which the population projections are made, n is the time interval, Pt is the population at base period t, and r is the crude annual rate of natural increase in population.
6.11. The intercensal annualized rate of growth (r) was derived for each district/municipality using the above function applied on the 1979 and 1989 census data. The projections were carried out using different approaches for different categories of districts/municipalities depending on the availability of published population data. The method assumes that r observed for the period 1979-1989 remains constant over the period 1989-1995. The actual rate of growth is dependent on many factors, and does not have an independent existence.
LIMITATIONS OF POPULATION DATA
6.12. There were several limitations in using the published population data to project current population age 3-6 years. The limitations were mainly (a) subdivision of districts, (b) the degree of disaggregation of age data, especially with respect to data based on the 1979 census, and (c) extension of urban boundaries over time. 6.13. Information on, say, pre-school enrolment provides the numerator in the computation of enrolment ratios, while the denominator is calculated from baseline information on population by district/ municipality for a baseline date and then projected to the reference year. However, the number of districts has increased due to subdivision of existing districts. Since the 1989 Population Census, the first group of districts to be created were Machakos/Makueni, Kakamega/Vihiga, Homa-Bay/Migori, Kericho/Bomet, Kisii/Nyamira, and Meru/Tharaka-Nithi in 1992. The above-mentioned new districts were ratified through the Districts and Provinces Act of 1992. More recent divisions include Meru/Nyambene, Kitui/Mwingi, Bungoma/Mt.
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Elgon, Migori/Kuria, Kiambu/Murang’a/Thika, Narok/Trans Mara, and Homa Bay/Suba. The subdivision of districts has created problems to data systems which assume population parameters e.g. water and sanitation coverage, immunization coverage, and morbidity and mortality statistics from administrative records as percentage of total target population. 6.14. The use of inappropriate population denominators imply that the reported coverage/enrolment ratio is low if the population figure used is more than actual, and vice versa. In the case of the new districts, the population estimates of the “old” districts had not been compiled, while reporting on enrolment is per the new districts. The “old” district therefore shows a lower enrolment ratio than actual, while the new district does not have population parameters and no enrolment ratios are therefore computed. The Central Bureau of Statistics has not provided users with information on population for the new districts, probably because the new districts were created after the 1989 population census. The districts in the ECCD sample survey affected by creation of new districts are Machakos, Narok, Kericho and Kakamega, since the districts’ sample frames of ECCD centres were based on the new districts. The “denominator” problem will also be aggravated by the AIDS scourge before the next population census is undertaken and analyzed. 6.15. There may also be an inherent “numerator” problem in apportioning facility-based data by districts, as data analysis is based on “catchment area” rather than “catchment population”. A pre-school in, say, Nairobi may also serve contiguous districts e.g. Kiambu - the catchment population - while its enrolment is posted to Nairobi - the official catchment area. 6.16. The “numerator” problem has been aggravated by the displacement of people in some parts of the country, mainly Rift Valley province. Information on enrolment based on data from pre-schools might give a false impression of deterioration in the areas where the people have been displaced (due to reduction in the “numerator”), and an improvement in their destination districts. 6.17. The published data with respect to the 1979 population census do not include detailed age data for urban areas other than Nairobi and Mombasa, which were taken as districts for the purpose of the census. However, the effect of extension of urban boundaries has not been taken into account in estimating the population for reference years 1979 and 1989. ESTIMATES OF POPULATION AGE GROUP 3-6 YEARS2 6.18. Since the Central Bureau of Statistics has not compiled data for the newly-created districts, the sampled districts/municipalities were split into three categories for the purpose of compiling the population age group 3-6 years: (a) those that have not been subdivided and do not have both urban and rural components in the sample (Nairobi, Mombasa, Kilifi and Nyandarua); (b) the rural districts that have been subdivided (Machakos, Narok, Kericho, Kakamega and Garissa); and (c) districts which include urban areas in the sample for which detailed age data were not published with respect to the 1979 census (Nakuru, Kisumu, Uasin Gishu, Trans Nzoia and Kiambu). Although Garissa district has not been subdivided, the survey covered only Central division of Garissa district, and the district can therefore be considered as having been subdivided for the purpose of the survey. 6.19. The differences in the levels of disaggregation of population data by age and other demographic factors made it necessary to compute population projections for age group 3-6 years using different approaches for different areas. For example, various demographic factors (e.g. fertility rates and age-selective migration patterns) affect the age distribution of the population. Since these factors affect urban and rural populations differently, the districts with urban areas in the sample (e.g. Nakuru district and Nakuru municipality) will be treated differently from those without an urban area in the sample (e.g. Machakos and Makueni).
2. The population census data was extracted for the age group 3-5 since census data is collected
on the basis of completed years, i.e. age 5 refers to the interval 5 to 6 years.
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6.20. The population aged 3-6 years by sex in respect of Nairobi, Mombasa, Kilifi and Nyandarua districts/municipalities were extracted from the 1979 and 1989 census reports and projections for 1990-1995 made using the 1979-1989 intercensal growth rates for the age group 3-6 years. 6.21. In the case of Machakos, Kericho, Kakamega and Narok, total population by sex for 1979 and 1989 for the “new” districts were compiled on the basis of administrative divisions forming the “new” districts as given in the Government’s District Development Plans, 1994-96. In the case of the “new” Narok district, the sample frame of ECCD centres was based on Mau, Olokurto, and Osupuko divisions, but excluded Kilgoris and Lolgorian divisions. The latter divisions were therefore assumed to comprise the new Trans Mara district. For the purpose of the survey, Garissa Central Division was taken as a “new” district. 6.22. The 1979 and 1989 population estimates for the new districts were compared with those in the respective District Development Plans. The population estimates for Machakos and Kakamega agreed with those contained in the District Development Plans, 1994-96. However, the estimates for the new Kericho district were at variance with those in the District Development Plan. The combined 1979 population census figure for Kericho and Bomet based on the District Development Plans was 715,000 compared to 633,348 given in the 1979 population census report. 6.23. The second step was to compute the proportions of total population by sex in the “new” districts to the “old” districts for both 1979 and 1989. The proportions were applied on the 1979 and 1989 population aged 3-6 years in the “old” district to obtain estimates for both 1979 and 1989 population aged 3-6 in the new district. The projections for 1990-1995 were made using the 1979-1989 intercensal growth rates for the age group 3-6 years. 6.24. Data on the population aged 3-6 years for Kiambu, Nakuru, Uasin Gishu, Trans Nzoia and Kisumu districts, and for Thika, Nakuru, Eldoret, Kitale and Kisumu municipalities were extracted from the 1989 census reports. But this process was not possible in respect of 1979 census data since, in addition to boundary changes, detailed age data for each urban centre were not published. However, since the 1979 census report gave age data by broad age groups, it was decided to apply the respective municipality’s proportion of population aged 0-14 years by sex to the total district population aged 3-6 years in 1979 to derive the 1979 population aged 3-6 years for each urban centre. The population aged 3-6 years in the district, excluding the municipality, was derived as the difference between the district’s 3-6 age-group population from the 1979 census report and the computed 3-6 age-group population for the municipality. Having computed the 1979 population aged 3-6 years for the municipalities and their counterpart rural districts, projections for the period 1990-1995 were made using 1979-1989 intercensal growth rates for each respective area.
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CHAPTER 7: PROFILES OF PRE-SCHOOLS
RESPONSE RATES
7.1. The ECCD survey enumerators were instructed to classify the outcome of the survey interview in the control form as either fully completed, partially completed, centre temporarily closed, centre permanently closed, refusal, centre could not be located, interview postponed, or relevant personnel could not be contacted. In this report, response is defined to include “fully completed” and “partially completed” interview status, and all other interview outcomes were classified as nonresponse. 7.2. Statistical Appendix Table 11 shows that a total of 906 centres were covered, of which 866 were successfully interviewed, representing a 95.6% response rate. High response rates were reported in Thika (100.0%), Nakuru (100.0%), Kitale (100.0%) and Kisumu (100.0%) municipalities; and Nyandarua (100.0%), Narok (100.0%), Kakamega (99.0%), Machakos (98.6%) and Kericho (98.2%) districts. Other urban reported a high response rate (97.2%), followed by rural districts (96.8%) and major urban areas (88.4%). 7.3. Statistical Appendix Table 11 shows that nonresponse, comprising closed, not located and other nonresponse, was a low 4.4% of the pre-schools in the sample. Most nonresponse (4.1%) was attributed to pre-schools which were reported as closed (either permanently or temporarily) and failure of the field personnel to locate a sampled pre-school after repeated attempts. The proportion of centres which were reported as closed/not located was highest in major urban areas (10.9%), followed by rural areas (2.9%) and other urban areas (2.8%). Only 3 (0.3%) out of the 906 sampled pre-schools were reported as other nonresponse. These are two centres in Nakuru district which were not reached due to perceived insecurity in the area in which they are located, and one refusal in Nairobi.
GROWTH IN ESTABLISHMENT OF PRE-SCHOOLS
7.4. Statistical Appendix Table 12 shows increasing growth in the establishment of pre-schools. Only 343 responding pre-schools had been established by 1980. An additional 146 pre-schools were established during the five-year period 1980-1984, 169 during 1985-89 and 193 during 1990-May 1995. A reported 39.6% of the pre-schools were established before 1980, 16.9% during the period 1980-1984, 19.5% during 1985-1989 and 22.3% during January 1990-May 1995, which shows an increasing growth over time. The rates of establishing new pre-schools were higher in major urban and other urban areas than in rural areas, especially from 1990. 7.5. Distribution of pre-schools by sponsorship underscores the partnership role played by different groups in provision of pre-school care and education in Kenya. As shown in Statistical Appendix Table 13, out of the 866 responding pre-schools, 568 (65.6%) were sponsored by parents/community, 106 (12.2%) by religious organizations, 75 (8.7%) by private individuals/company, 16 (1.8%) by plantations/ estates/ other companies, 98 (11.3%) by local authorities, and 3 (0.3%) by nongovernmental organizations. Majority of pre-schools in the two major urban areas of Nairobi and Mombasa were sponsored by religious organizations (36.1%) and private individual/company (27.9%). On the other hand, majority of pre-schools in the rural districts (77.6%) were sponsored by parents and local communities. Pre-schools located in other urban areas were more evenly distributed among the three main sponsors, with community, religious organizations and private individuals/company sponsoring 31.4%, 28.6% and 25.7%, respectively. Although the role of the private sector (excluding pre-schools for workers in plantations/ estates/ other companies) is proportionately low (8.7%), it recorded the highest growth in establishment of pre-schools in major urban and other urban areas (as shown in Statistical Appendix Table 12). Whereas local authorities have not been active in the recent past in establishing new pre-schools, 98 pre-schools (11.3%) were reported as sponsored by local authorities. 7.6. As shown in Statistical Appendix Table 13, in Nairobi, religious organizations (35.2%) and private
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individuals/company (30.7%) were the major sponsors, followed by Nairobi City Council (15.9%) and community (14.8%); while community (29.4%) and religious organizations (38.2%) led in Mombasa municipality. In the rural districts, parents/community (77.6%) sponsored most pre-schools. However, the local authority sponsorship of pre-schools was second after parents/community in Kilifi, Narok, Kakamega, and Kisumu districts. In this report, pre-schools sponsored by plantations/ estates/ other companies and nongovernmental organizations are classified under “other” category.
PRE-SCHOOLS BY TYPE OF NEIGHBOURHOOD
7.7. As shown in Statistical Appendix Table 14, pre-schools in major urban and other urban areas were reported as drawing children mainly from slum and urban non-slum catchments areas, while those located in the rural districts reported the main catchments areas as settled agriculture. About forty per cent of pre-schools in Nairobi were reported as located in urban slums, compared with Mombasa (11.8%). In Nairobi, one centre was reported as located within settled agriculture area in Dagoretti Division. Other urban areas reported a significant proportion of pre-schools as located in urban slums (50.0%); and was particularly high in Kitale (100.0%), Eldoret (87.5%), Kisumu municipality (43.5%) and Thika (42.9%). Other urban areas also reported pre-schools located within settled agriculture and plantations, namely, Thika (1 centre), Nakuru (1 centre) and Eldoret (1 centre). Kilifi, Machakos, Nakuru district and Garissa Central Division reported significant proportions of pre-schools located in urban slum and urban non-slum catchments areas. Pre-schools in pastoral catchment areas were reported in Narok (29.7%), Garissa Central Division (21.4%), Nakuru (2.1%), Kilifi (2.0%), Kericho (1.9%) and Machakos (0.7%).
PRE-SCHOOLS BY OWNERSHIP
7.8. Statistical Appendix Table 14 shows that, in major urban and other urban areas, the distribution of pre-schools between public and private ownership was almost even, except in Thika (which was tilted in favour of private ownership) and Kitale (tilted in favour of public ownership). In the rural districts, public ownership was 93.0% of the total responding pre-schools. However, the statistics in respect of municipalities in the category of “other urban” (e.g. Thika) should be interpreted with caution due to the small sample sizes.
PRE-SCHOOLS BY TYPE OF SERVICES OFFERED
7.9. The survey sought information on the main type of service offered to the children enrolled in the pre-school, and the choices included formal education (840 pre-schools), pure day-care (13 pre-schools), Christian religious teaching (1 pre-school), duksi/madrassa (1 pre-school), Integrated duksi/madrassa (3 pre-schools), and other (8 pre-schools). Statistical Appendix Table 15 shows that almost all pre-schools (97.0%) mainly offer formal education curricula and only 13 pre-schools (1.5%) mainly offer pure day-care service. The day-care centres were in Nairobi (2 centres), Mombasa (1 centre), Machakos (8 centres), Nakuru district (1 centre) and Narok (1 centre). The data therefore suggest that pre-school education is mainly taken as a preparatory stage for entry into primary school. 7.10. However, it is possible for a responding centre to have been offering a different type of service for each grade/class. An estimate of the distribution of pre-school children by types of services received in pre-schools could have been obtained by seeking information on main type of service offered for each grade/ class.
REGISTRATION
7.11. Statistical Appendix Table 16 shows that most of the pre-schools (74.2%) were reported as
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registered, regardless of the registering authority. The proportion of pre-schools reported as registered was highest in other urban areas (85.7%) and major urban areas (85.2%) and slightly lower in the rural districts (71.1%). Among the districts/municipalities, the proportion of registered pre-schools was highest in Thika (100.0%), Machakos (94.9%) and Kericho (92.6%); and lowest in Narok (18.9%), Nakuru district (47.4%) and Garissa Central Division (57.1%). Since a large proportion of pre-schools in most districts/municipalities were reported as registered, thereby making the sub-sample of unregistered pre-schools rather small, it is not possible to give an unqualified conclusion whether there is a relationship between registration status and enrolment size. 7.12. The survey did not specify the formal registering authority in respect of pre-schools. Since pre-schools can be registered by a local authority, a Community Development Officer (CDO) as a self-help project within the umbrella of the Ministry of Culture and Social Services, or by the Ministry of Education, it is not possible to know from the survey findings whom the pre-schools were registered with. In addition, some pre-schools did not consider it necessary to register, e.g. a pre-school in a company/estate for the welfare of the employees’ children reported that registration was not necessary, unless the pre-school intends to enrol from outside of its workforce. Some respondents may also have reported that they were registered when they were not for fear of being penalized, while others may not have known whether the pre-school was registered.
MANAGEMENT OF PRE-SCHOOLS
7.13. Statistical Appendix Table 17 shows that majority of pre-schools in both major urban (68.9%) and other urban areas (55.7%) were managed on a day-to-day basis by the headteacher-employee of the pre-school. However, in the rural areas, a high proportion of pre-schools (46.6%) were managed by the headteacher of primary school, mainly because there was proportionately higher number of attached/linked pre-schools in rural districts compared to major urban and other urban areas. Overall, the survey revealed that most pre-schools were managed by headteacher of primary school (38.5%), closely followed by headteacher-employee of the pre-school (37.8%). Some 154 pre-schools (17.8%) reported that they were managed by a committee, of which 135 were found in rural areas, mostly in Nakuru district (36 centres), Nyandarua (34 centres), Machakos (22 centres), Kakamega (14 centres) and Kericho (13 centres). Only 35 (4.0%) out of the 866 responding pre-schools reported that they were managed on a day-to-day basis by a religious leader. 7.14. As shown in Statistical Appendix Table 18, the proportion of pre-schools which reported as having a management committee was high in rural districts (81.4%), compared with major urban (55.7%) and other urban areas (64.3%). High proportions of pre-schools that reported as having management committees were recorded in Uasin Gishu (95.6%), Nakuru district (93.6%), Nyandarua (92.0%) and Kericho (90.7%); while lowest proportions were recorded in Thika municipality (42.9%), Nairobi (52.3%) and Kisumu municipality (56.5%). 7.15. The composition of pre-school management committees by size and sex is shown in Statistical Appendix Tables 18 and 19. Eleven out of the 17 sampled districts/municipalities reported an average of less than 10 committee members per pre-school. Only Kisumu municipality (14.1 committee members), Kakamega (12.6), Kisumu district (11.1), Kilifi (10.8), Garissa Central Division (10.5) and Kericho (10.0) had average committee size of 10 or more persons. Small average committee sizes were reported in Nakuru municipality (6.7) and Thika (7.7). 7.16. The composition of pre-school committees by gender showed that all districts/municipalities reported a higher average of male members than female members. The difference in the mean number of male and female members was more pronounced in Garissa Central Division (8.8 males, 1.6 females), Narok (7.6 males, 1.5 females), Thika (6.3 males, 1.3 females) and Kericho (8.0 males, 2.0 females). The gender difference was small in Nairobi (5.0 males, 4.6 females), Nakuru municipality (3.6 males, 3.1 females), Kisumu municipality (7.2 males, 6.8 females) and Eldoret (5.0 males, 4.5 females).
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7.17. A different way of looking at representation in the pre-school committees by gender was through the number of “males only” (no females) and “females only” (no males) committees. In the rural districts, only 20 committees were “females only” compared to 47 “males only” committees. Machakos reported 12 “females only” committees while Nyandarua, Kericho, Narok, Kisumu district and Garissa Central Division reported no “females only” committees. Narok reported the highest proportion of “males only” committees, while Eldoret municipality had no “males only” committees. Since most pre-school employees were females, this implies that they operate under male-dominated management committees. 7.18. Statistical Appendix Table 20 shows that, of the 661 pre-schools which reported that they had pre-school committees, 598 (90.5%) last met between January 1995 and the date of interview in July 1995. Only 7 committees (1.1%) had never met, and 4 (0.7%) had last met during or before 1993. It is not possible to give the frequency of the committee meetings since the data were collected only in respect of the last meeting. However, if the date of the last management committee meeting is taken as an indication of parents/community involvement in pre-school’s management, then Machakos district with 98.1% of committees having met in the first half of 1995, Kakamega (95.3%), Nyandarua (94.2%), Kericho (93.9%), Narok (93.8%), Kisumu municipality (92.3%), Uasin Gishu (90.7%) and Kisumu district (90.6%) performed relatively well.
PRE-SCHOOLS BY ATTACHMENT TO A PRIMARY SCHOOL
7.19. The enumerators’ reference manual defined an “attached” pre-school as one “sharing the same compound with a mother primary school, and may or may not have its own headteacher”, while “linked” was a pre-school “not in the same compound with a primary school, but is recognised by the primary school to which it is linked as a ‘feeder’ for the purpose of Primary Standard One intake”. The headteacher of the primary school is expected to take special interest in the quality of services offered by the attached/linked pre-school so that the Primary Standard One intake is of reasonable quality. 7.20. Statistical Appendix Table 21 shows that, of the total 866 responding pre-schools, 533 (61.5%) were attached and 152 (17.6%) were linked, i.e. a total of 685 (79.1%) of the centres had operational arrangements with a primary school. Attachment and linkage arrangements were most prevalent in the rural districts (91.5%) and low in major urban areas (31.1%) and other urban areas (42.9%). The rural districts reported over 90% of pre-schools as either attached or linked, except Nakuru (87.4%), Garissa Central Division (85.7%), Machakos (85.5%) and Narok (83.8%). In major urban areas, 35.3% of Mombasa pre-schools reported attachment/linkage to a primary school, compared with 29.5% in Nairobi. Lack of operational arrangements with a primary school in urban areas may be attributed to prevalence of private pre-schools, and the difficulty of defining a catchments area for a primary school which would encompass a defined set of pre-schools. 7.21. Statistical Appendix Table 22 shows that, of the 533 attached pre-schools, 402 (75.4%) shared the same management committee with the primary school. Garissa Central Division (100.0%), Narok (96.6%), Kilifi (94.4%), Kakamega (91.7%) and Machakos district (89.9%) reported the highest proportions of attached pre-schools which share management committees with a primary school. At the other end, Uasin Gishu (37.5%) and Nyandarua (43.2%) reported very low proportions of attached pre-schools which share management committees with the primary school. The reported numbers of attached pre-schools in major urban and other urban areas were too low to allow unambiguous conclusions on sharing of committees with primary schools. 7.22. The relationship between the attached pre-school and the parent primary school was also measured by whether the headteacher of the pre-school had attended a staff meeting of the primary school during January-July 1995. Statistical Appendix Table 22 shows that 357 (67.0%) of headteachers of pre-schools had attended such meetings during the period January-July 1995. Attendance of a primary school’s staff meeting by the headteacher of the pre-school was high in Narok (100.0%), Kakamega (89.6%), Kilifi (72.2%),
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Kisumu district (71.4%) and Machakos (68.7%); and low in Nakuru district (28.9%) and Nyandarua (34.1%).
SUPERVISION OF PRE-SCHOOLS
7.23. Data on supervision/inspection of pre-schools collected from pre-school headteachers related to (a) whom they considered to be their authorised supervisor/inspector, (b) whether she/he has ever been supervised, (c) date of last supervision/inspection, and (d) who made most supervisory visits between January 1994 and the date of interview. 7.24. Statistical Appendix Table 23 shows that since January 1994, most visits were by supervisors from the central Government (primary school inspector, zonal inspector and DICECE staff) at 38.6% of the responding centres, followed by Nursery School Supervisors employed by local authorities who made supervisory visits to 238 pre-schools i.e. 27.5% of the total responding centres, and by supervisory visits by the headteacher of the attached/linked primary school (13.3%). A total of 119 pre-schools (13.7%) reported that they were not visited at all between January 1994 and the date of interview (circa July 1995). 7.25. Due to accessibility of pre-schools and more efficient transport systems, it would have been expected that more supervisory visits would be made in urban compared to rural areas. However, the data shows no significant difference between the proportions of “no visits” in major urban areas compared to rural districts, with 13.9% for major urban, 5.7% for other urban and 14.5% for the rural districts. There were more supervisory visits by Nursery School Supervisors in the rural areas (34.1%), compared to major urban areas (5.7%) and other urban areas (1.4%). A high proportion of supervisory visits by Nursery School Supervisors in the rural areas was mainly attributable to visits made to centres sponsored by parents/community and local authorities. 7.26. Survey questions are said to be bounded if the recall is based on the period “since my last visit” e.g. the survey question on who made the most supervisory/inspection visits “since January 1994”. Under this definition, the reference periods (last year) used in the survey may lead to serious telescoping (mis-dating) errors. The responses by reference period and the accuracy in telescoping the reference period could depend on the adequacy and accuracy of records in the pre-schools. In addition, the upper bound of the recall period for questions with reference period between a past fixed date (e.g. January 1994) and the date of interview depended on the date of interview, which was not the same in all pre-schools covered in the survey. The latter is expected to affect responses within the same district/municipality and comparison of results by district/ municipality. The responses to questions with bounded recall are therefore likely to be affected by recall loss (forgetting an event that occurred during the reference period), telescoping error (forgetting when an event occurred), and variation in the length of recall period depending on the date of interview. 7.27. The open category “other” contains a significant number of responses. This is mainly because the enumerators’ reference manual did not give clear guidelines on what should have been considered as formal supervision/inspection, but only gave a list of possible supervisors/inspectors. For example, in some districts, Community Development Officers (CDO) visit community pre-schools qua community projects. It is therefore possible that some respondents reported CDOs as supervisors/inspectors under the “other” category.
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CHAPTER 8: ENROLMENT IN PRE-SCHOOLS 8.1. The survey collected information on (a) pre-school enrolment by age and sex as at 31st May of each year for 1990 to 1995, and (b) the breakdown of 31st May 1995 enrolment by age, sex, and grade/class. As shown in Statistical Appendix Table 24, there were many cases of blanks in respect of enrolment data by sex and age for reference years 1990 to 1994. The blanks were either (a) nonresponse for pre-schools which were operational in the reference year, or (b) genuine blanks for pre-schools which had not been established in the reference year, or (c) genuine blanks for pre-schools which had been established but were closed during the reference year. It was decided not to estimate weighted enrolments for the years 1990 to 1994 due to (a) the proportionately low number of responding pre-schools for years 1990-94, and (b) the inappropriateness of the 1995 sample weights to previous years. Data on enrolment also showed that children are placed in different grades/class on the basis of age and/or ability.
ENROLMENT SIZE BY SPONSOR
8.2. As shown in Statistical Appendix Table 25, 30.0% of pre-schools in major urban areas, 40.0% in other urban areas and 37.1% in the rural districts reported enrolments of 40-69 children. The mean enrolment size per pre-school were higher in major urban areas (77.4 children), followed by other urban areas (72.0 children) and lower in the rural areas (56.1 children). This may be attributed to low population densities and lack of transport in the rural areas which makes it difficult for pre-school children to travel long distances, thus contributing to localised small pre-schools. In major urban areas, pre-schools sponsored by religious organisations reported high mean enrolments (90.5 children) compared to community pre-schools (58.3 children). In the rural areas, pre-schools sponsored by religious organizations (47.8 children) and community (54.5 children) reported slightly lower mean enrolment compared to private (59.0 children) and local authorities (59.9 children).
PRE-SCHOOL ENROLMENT RATIOS BY SEX
8.3. The gross pre-school enrolment ratio is the total number of children regularly attending pre-school in the current year divided by the total number of children of pre-school age (3-6 years) for the same year. The enrolment data were collected on children enrolled as at 31st May, for years 1990 to 1995. Prior to the ECCD survey, the Ministry of Education suggested that enrolment as at 31st of May could be taken as the mean for the whole year given past experience in observed dropout rates during the year. Populations aged 3-6 years were estimated for every district/municipality using the available population data from the 1979 and 1989 population censuses and applying the 1979-89 intercensal growth rates to the period 1990-95. 8.4. Statistical Appendix Tables 26 and 27 shows estimated gross enrolment ratios by gender for each of the study areas, based on May 1995 enrolment data from the ECCD survey and 1994 official pre-school statistics, respectively. Gross enrolment ratios based on the survey were generally low in rural areas (36.0%) compared to major urban (44.0%) and other urban areas (47.0%). Nyandarua (54.5%) had a higher gross enrolment ratio than all other districts and municipalities, followed by Mombasa (53.6%) and Kisumu municipality (50.2%), while Narok had the lowest (19.6%). Gross enrolment ratios for boys were higher than for girls in Mombasa, Thika, Eldoret, Kilifi, Nyandarua, Nakuru district, Kericho, Narok, Kakamega and Garissa Central Division. Gross enrolment ratios based on the 1994 official pre-school statistics were higher for boys than for girls in Thika, Kisumu municipality, Kilifi, Machakos and Kericho. Approximate agreement of enrolment ratios based on the ECCD survey and official pre-school statistics may be more of a coincidence rather than a firm proof of accuracy of either dataset since (a) the data refer to different reference years, and (b) the sample frame for the ECCD survey included pre-schools established in early 1995. 8.5. In the case of primary and secondary education, an enrolment ratio can be crudely taken as a
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measure of children who have “ever attended”, say, primary school education since promotion to a higher grade/class is conditional to having completed the immediate lower grade. As an illustration, suppose enrolment is defined in terms of physical space. Take the case of two communities, A and B, each with 100 children aged 3-6 years and physical space for 30 children. If community A enrols children for only one year, the physical space would be occupied by 30 children, and community A would be able to promote 30 pre-school children to Primary Standard One every year. Suppose that community B enrols an equal number from each single-year age cohort. Community B would enrol 10 children for each of the grades, and would only be able to promote 10 children from pre-school to Primary Standard One every year. In both cases, pre-school enrolment ratios would be the same, although community A had more children who have “ever attended” (but for a shorter period) than community B. 8.6. If enrolment data for a particular day can be generalized to the whole year, the numerator in the gross enrolment ratio can be crudely defined as the product of children enrolled per grade/class and the average number of years a child takes in pre-school. The interpretation of gross enrolment ratios estimated from the survey data is therefore different from those estimated for primary and secondary education, due to lack of fixed and compulsory period of attendance in pre-school education, unlike the eight Standards and four Forms that characterize primary and secondary education, respectively. Data on the number of children who have “ever attended” pre-school can be collected through a household-based survey, by, for example, tagging a pre-school care and education module to the CBS’s Welfare Monitoring Survey.
ANALYSIS OF PRE-SCHOOL FEES
8.7. The survey reported wide regional variations in school fees charged per child as shown in Statistical Appendix Table 28. The mean fees per year were highest in major urban areas, followed by other urban areas, and lowest in the rural districts. Mean fees per pre-school child were highest in Nairobi (Shs 4,911), Mombasa (Shs 4,581) and Nakuru municipality (Shs 3,806), and lowest in Kisumu district (Shs 266) and Uasin Gishu (Shs 386). 8.8. The mean fees were multiplied by the weighted enrolment figures to arrive at estimates of total fees paid per year in each respective district/municipality. As shown in Statistical Appendix Table 28, Nairobi pre-schools received the largest outlay of Shs 248.8 million in 1994, followed by Mombasa (Shs 96.4 million). In the rural areas, Kakamega (Shs 39.1 million) led, followed by Nakuru district (Shs 24.0 million), Nyandarua (Shs 22.9 million) and Machakos (20.4 million). 8.9. As shown in Statistical Appendix Table 29, a large proportion of pre-schools in major urban areas (85.3%) charged more than Shs 1,000 per year, while most rural pre-schools (88.5%) charged less than Shs 1,000 per year. The 12 pre-schools in the rural areas which charged Shs 3,000 and over may be due to selection of pre-schools in urban areas within the rural districts. In total, there were 11 pre-schools in which children did not pay fees at all. These were pre-schools sponsored by parents/ community (3), religious organizations (3), private individuals/ company (2) and local authorities (3). 8.10. Although the survey sought data on the total annual fees and levies per child for the year 1994, there were several questionnaires in which the enumerators either gave per-term or per-month charges. During data edit, the per-term figure was multiplied by 3 and the per-month figure by 9, based on total school fees/levies given under sources of operating costs. However, such data edit may not have detected all possible cases. 8.11. Statistical Appendix Table 30 shows the distribution of pre-schools by action taken on children who fail to pay pre-school fees in part or full. A significant proportion (35.7%) of the pre-schools either assists or allows children to continue at the pre-school. However, a large proportion (46.7%) of pre-schools sends away children who fail to pay fees. There were variations reported by districts/ municipalities on action taken. A large proportion of pre-schools in Garissa Central Division (71.4%), Thika (71.4%), Eldoret (62.5%), Mombasa (55.9%) and Narok (51.4%) assists or allows children to continue, while other
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districts/municipalities observed lower proportions of pre-schools that assist or allow children to continue. 8.12. Statistical Appendix Table 31 shows that a large proportion of children were able to complete payment of all school fees. The proportion of children who completed paying all school fees/levies was 87.3% in Eldoret, followed by Nyandarua (83.5%), Nairobi (82.8%), Machakos (82.7%), Mombasa (81.5%), Nakuru district (80.9%), Nakuru municipality (80.4%) and Narok district (80.2%). At the other end, Kisumu district (47.8%), Kitale (55.3%) and Kakamega (56.1%) reported lower proportions of children as having completed payment of fees in 1994. 8.13. However, on the action taken against a child who fails to meet part or whole of centre’s compulsory fees and charges, there may have been some confusion between option 1 (“allowed to continue at the centre”) and option 2 (“sent away from the centre”). Some enumerators could have recorded the option “allowed to continue at the centre” simply because a centre does not send children away during school hours, but only asks for parents to come to the centre. However, if a child is not allowed to continue until its parents pay the compulsory fees, the right option should have been “sent away from the centre”. In addition, it was not possible to report on gender bias in ability/willingness to pay since the data were solicited for all children, without breakdown by sex.
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CHAPTER 9: PROFILES OF PRE-SCHOOL PERSONNEL 9.1. Data collected on pre-schools’ caregivers included (a) particulars of all employees e.g. year of birth, sex, date of appointment, main type of work, whether working full-time or part-time, hours worked per week, and monthly salary; (b) further particulars of each individual teacher on educational attainment, non-ECCD teacher training, ECCD training (programme, duration, sponsor, year of completion) and teaching experience (ECCD-related and non-ECCD related); and (c) teacher turnover. During data processing, persons whose main type of work was reported as administration but whose particulars were recorded in the section on teachers were coded as teachers. However, many respondents did not give reliable data on teacher turnover due to lack of records, and hence data on teacher turnover were not analyzed.
PRE-SCHOOL EMPLOYEES
9.2. As shown in Statistical Appendix Table 32, a total of 1,780 teachers were reported for the 866 responding centres, or an average of 2.1 teachers per centre. There were more teachers employed per centre in major urban areas (3.9) and other urban areas (3.2) than in rural areas (1.6). The average number of teachers per centre was low in Uasin Gishu (1.3), Machakos (1.4), Kericho (1.4) and Kisumu district (1.4). At the other end, Mombasa (4.1) reported the highest average number of teachers per centre, followed by Nakuru municipality (3.9), Nairobi (3.8) and Kitale (3.4). 9.3. A total of 376 nonteaching staffs were employed in all the pre-schools, or an average of 0.4 employees per centre. On average, more nonteaching staff per centre were employed in major urban areas (1.3) and other urban areas (0.9) compared to only 0.2 reported in the rural areas. No nonteaching staffs were employed in any of the 37 pre-schools surveyed in Narok. Nonteaching employees included watchmen, child-minders, gardeners, groundskeeper/groundsman (who maintains the grounds of an estate or park or athletic field) and cleaners. 9.4. Statistical Appendix Table 32 further shows that employment in pre-schools is a female domain. Of the 1,780 teachers, 1,730 (97.2%) were females and only 50 (2.8%) were males. Prevalence of females over males was also reported among nonteaching staff, with a total of 257 (68.4%) female nonteaching staff and 119 (31.6%) male nonteaching staff. Only Kisumu municipality, Machakos and Garissa Central Division reported more male nonteaching staff than females. 9.5. Mean monthly salaries by sex and main type of work (teaching or nonteaching) are shown in Statistical Appendix Table 32. The data do not reveal a clear overall picture of gender bias in teachers’ mean monthly salaries. All districts/municipalities reported more female than male teachers, while Eldoret, Kitale and Kericho district had no male teachers. Average monthly salaries of teaching staff were generally higher than for nonteaching staff, except in Kisumu district (where the ratio of nonteaching to teaching staffs is too small to allow meaningful interpretation). The mean monthly teachers’ salaries were highest in Nairobi (Shs 3,945) and Mombasa (Shs 3,741), and lowest in Nyandarua (Shs 1,083), Kakamega (Shs 1,207), Kitale (Shs 1,236), Kericho (Shs 1,255) and Machakos (Shs 1,287). 9.6. Statistical Appendix Tables 33(a) and 33(b) give the distribution of teachers by various salary groups. Of the 1,780 teachers in the responding pre-schools, data on salaries of 77 teachers were not reported because of (a) pure nonresponse, (b) volunteer teachers without pay, and (c) trainee teachers on practice in the responding pre-school. Teachers’ salaries in the urban areas were concentrated in the relatively high salary groups, while those of rural teachers were concentrated at the bottom. Of the 1,067 teachers in the rural districts whose salaries were reported, 55.5% received Shs 1,000 or less per month, compared with major urban areas (5.7%) and other urban areas (15.5%). The rural districts with the highest proportions of teachers receiving Shs 1,000 or less were Kericho (74.0%), Nyandarua (66.4%), Kakamega (66.3%) and Kisumu district (62.6%). Only 12.7% of the rural teachers were earning over Shs 3,000 at the time of the survey, compared with 46.2% in major urban areas and 14.6% in other urban areas. The reported monthly salaries were generally lower than the official minimum wages prevailing at the time of the ECCD survey.
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TEACHERS’ EDUCATION AND TRAINING
9.7. As shown in Statistical Appendix Tables 34 and 35, majority (60.5%) of the teachers employed in the pre-schools were secondary school leavers or above, while 38.6% were holders of Certificate of Primary Education (CPE) examination or below. In major urban areas, 393 teachers (83.1%) had attained Kenya Certificate of Secondary Examination (KCSE) or above, compared with 68.5% in other urban areas and 49.1% in the rural districts. About 50.4% of pre-school teachers in the rural districts were CPE or below, compared to 29.8% in other urban areas and 15.7% in major urban areas. Nairobi had the highest proportion (88.0%) with secondary or postsecondary education, followed by Nakuru municipality (77.6%), Mombasa (75.2%), Nyandarua (71.2%) and Kitale (70.8%. At the other end, Kilifi (27.7%), Narok (31.7%), Garissa Central Division (37.5%), Machakos (42.1%) and Kisumu district (45.2%) reported the lowest proportions with secondary or postsecondary education. 9.8. Statistical Appendix Table 34 shows that more than half of the teachers had received some form of ECCD-training, with large proportions of trained teachers in major urban areas (70.8%) and other urban areas (63.9%), compared to 49.8% of the rural teaching force. Overall, pre-schools in urban areas recruit teachers with higher academic and ECCD-training compared to the rural districts. 9.9. Analysis of teachers who have received some form of ECCD-training, given in Statistical Appendix Tables 36 and 37, shows that Government institutions (mainly DICECE, Ministry of Culture and Social Services prior to 1984, and National Youth Service) were the largest trainers, and had trained 71.6% of all trained teachers, including those currently undergoing training. In the urban areas, most of those trained by Government had secondary education and above, compared with rural areas where half were CPE and below and the other half had secondary education and above. The Kindergarten Headmistresses Association (KHA) and Montessori programmes mainly train secondary school leavers, and most of their graduates were deployed in the major urban areas. The Government had trained 83.9% of all trained pre-school teachers in the rural areas, compared with 57.0% in major urban areas and 68.5% other urban areas. 9.10. The distribution of teachers by ECCD training and year training completed is shown in Statistical Appendix Table 37. Out of 960 trained teachers who reported year of completion of ECCD-training, 203 had been trained before 1984. In the 10-year period 1985-1994, the total number of trained teachers rose by 602 contributing about 59% of total trained teachers. However, the data on ECCD-specific training may not accurately reflect the relative outputs from the training programmes since the situation at the time of the survey depends on teacher turnover e.g. teachers trained by the Ministry of Culture and Social Services may have left ECCD-teaching due to normal attrition (e.g. deaths), while teachers from other training programmes may have sought employment elsewhere (e.g. joined primary school teaching) depending on quality of training and job availability. In addition, those whose training was not reported are likely to have had no training (if the respondent knew their training backgrounds) or the respondent did not know. 9.11. According to the Ministry of Education, a “trained” teacher should have completed at least one-year training under recognized ECCD-training programmes e.g. DICECE, National Youth Service, PCEA, KHA, Montessori and Islamic Integrated Programme. Statistical Appendix Tables 38 and 39 shows that 56.2% of teachers in major urban areas were trained compared with other urban areas (47.1%) and rural districts (32.8%). The districts/municipalities with the highest proportions of trained teachers were Garissa Central Division (79.2%), Mombasa (58.2%), Nakuru municipality (56.7%) and Nairobi (55.4%); while the lowest were Machakos (19.5%), Nyandarua (24.0%), Eldoret (25.0%), Narok (26.7%) and Kericho (28.6%). 9.12. In most districts/municipalities, the number of teachers estimated from weighted survey data does not differ significantly from the official pre-school statistics submitted by the respective districts/municipalities (Statistical Appendix Table 40). However, estimates of the proportions of trained teachers based on the ECCD sample survey were significantly higher than those based on official pre-school statistics for Nakuru municipality, while the reverse was true in Machakos district.
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TEACHERS’ TEACHING EXPERIENCE
9.13. Each teacher was required to provide information on her/his total teaching experience in (a) early childhood care and education, and (b) other teaching experience. The period of ECCD-related teaching experience is expected to be positively associated with teacher’s skills in subject matter and pedagogy, while high turnover is expected to put heavy demands on training. As shown in Statistical Appendix Table 41, in all districts/municipalities, average teaching experiences were longer in ECCD-related teaching compared to non-ECCD teaching. Average ECCD-related teaching experiences ranged from 3.8 years in Garissa Central Division to 9.2 years in Machakos. The average length of experience in ECCD-related teaching was highest in Machakos (9.2 years), followed by Thika (8.9 years), Kakamega (7.9 years), Kisumu district (7.8 years), Mombasa (7.5 years) and Kisumu municipality (7.1 years). Teachers’ stay in ECCD-related teaching was lowest in Garissa Central Division (3.8 years), Nyandarua (4.3 years), Eldoret (4.4 years) and Narok (5.0 years). 9.14. Average teaching experience within the pre-school was highest in rural districts (5.7 years), followed by major urban areas (4.8 years) and other urban areas (3.9 years). At the district/municipality level, average teaching experience within the pre-school was highest in Machakos (8.6 years), Thika (7.9 years), Kakamega (6.5 years), Kisumu district (5.6 years) and Kilifi (5.6 years); and lowest in Garissa Central Division (2.0 years), Nakuru municipality (2.8 years), Eldoret (3.2 years) and Nyandarua (3.8 years). 9.15. Average non-ECCD teaching experience ranged from 0.0 years in Thika, Kitale and Kilifi to 1.7 years in Nairobi. If ECCD and non-ECCD teaching experiences are added together, Machakos (9.6 years) still had the longest average experience followed by Thika (8.9 years), Kakamega (8.5 years), Kisumu district (8.1 years) and Nairobi (8.0 years). Garissa Central Division (3.9 years), Eldoret (4.6 years), Nyandarua (5.2 years) and Narok (5.7 years) had the shortest average ECCD and non-ECCD teaching experience.
PUPIL-TEACHER RATIOS
9.16. As shown in Statistical Appendix Table 42, estimated pupil-teacher ratios were low in major urban areas (21.7 pupils per teacher), followed by other urban areas (24.9) and rural areas (36.6). At the district/municipality level, Mombasa (20.3 pupils per teacher), Nairobi (22.2), Nakuru municipality (22.5) and Kitale (22.7) reported the lowest pupil-teacher ratios, while Uasin Gishu (43.4), Garissa Central Division (46.8) and Kilifi (46.9) reported the highest average pupil-teacher ratios. All urban areas reported average pupil-teacher ratios lower than those reported in the rural districts, except Kisumu municipality whose ratio (27.8) was slightly higher than that of Narok (27.2), the lowest ratio reported in the rural districts. It can therefore be argued that, depending on main types of service offered at the pre-school, teacher workload is heavier in rural than in urban areas. 9.17. Analysis of pupil-teacher ratios by sponsorship does not provide a clear pattern. As shown in Statistical Appendix Table 43, local authority-sponsored pre-schools in major urban areas reported the lowest average pupil-teacher ratio of 15.5, while pre-schools under the same sponsorship reported the highest ratio of 28.8 in other urban areas. On average, community-sponsored pre-schools in the rural districts commanded a slightly higher workload per teacher compared with non-community sponsored pre-schools.
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CHAPTER 10: FINANCING OF PRE-SCHOOLS 10.1. The survey collected pre-schools’ financial data on (a) grants/aid received in 1994, (b) operating costs in 1994, (c) current market value of the pre-school’s facilities, (d) parents’ participation in centre’s development, and (e) anticipated future improvements. Grants/aid were defined as any donation in cash, materials or labour received by the centre to meet recurrent expenditures or capital costs.
GRANTS/AID
10.2. As shown in Statistical Appendix Table 44, only 71 (8.2%) out of the 866 responding pre-schools reported that they had received any grants/ aid during 1994. The proportion of pre-schools that received any grants/aid was higher in other urban areas (11.4%), followed by rural areas (8.6%) and major urban (4.1%). At the district/municipality level, Narok (10.8%), Nyandarua (12.0%), Machakos (12.3%), Thika (14.3%) and Eldoret (25.0%) all reported more than 10% of their pre-schools as having received any grants/aid during 1994. Kitale (0.0%), Nairobi (2.3%) and Nakuru district (4.2%) reported low proportions of centres that received any grants/aid in 1994, i.e. less than 5%. However, since some pre-schools which reported as not having received any grants/aid recorded financial/material contributions to operating costs from donors, it is possible that the question on grants/aid was not properly understood. For example, a local authority which pays salaries and for utilities could have been excluded from affirmative responses if (a) it owned the pre-school, and/or (b) if the support is considered as a right due to its regularity. 10.3. Analysis of grants/aid received by source and district is given in Statistical Appendix Table 45. Average grants/aid per recipient pre-school in 1994 was highest in other urban areas (Shs 379,343), followed by major urban areas (Shs 54,545) and rural districts (Shs 43,587). The total grants/aid received for each district/municipality can be derived as the product of average grants/aid per recipient pre-school and the number of pre-schools that received grants/aid. Due to the large grants/aid received from a religious organisation by only one centre, Nakuru municipality is reported as receiving the largest grants/aid per recipient pre-school during 1994. However, the sponsor who assisted in most districts was the community (who assisted in 10 districts/municipalities), followed by religious organisations, plantations/ estates/ other companies, and nongovernmental organisations. Although local authorities (e.g. Nairobi City Council) manage several pre-schools and pay teachers’ and other workers’ salaries and some other expenditures, no centre in major urban and other urban areas reported as having received any grants/aid from local authorities in 1994.
OPERATING COSTS
10.4. The respondent was asked to give total centre’s operating costs for 1994 by expenditure item and source of funds. Some enumerators gave total item value without showing breakdown by source, while others gave breakdown by source which did not add up to the reported total operating costs for that line item. The “not specified” source in the Statistical Appendix Tables therefore represents the difference between the reported total operating costs by line item and total amounts identified by source. The “not specified” column should therefore not be confused with “other sources” column. During data processing, community and school levies were lumped up into one category, i.e. community/school levies. 10.5. As shown in Statistical Appendix Table 46(a), the reported annual operating costs per pre-school were highest in major urban areas (Shs 305,203), followed by other urban areas (Shs 137,993) and lowest in rural areas (Shs 31,263) during 1994. Annual operating costs per pre-school ranged from Nairobi (Shs 310,921) and Mombasa (Shs 292,255) to Kisumu district (Shs 19,283) and Machakos (Shs 20,815); and were generally low in the rural areas, ranging from Shs 19,283 in Kisumu district to Shs 55,234 reported in Garissa Central Division.
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10.6. Statistical Appendix Table 46(b) shows that community/school levies contributed to 78.5% of total operating costs in other urban areas, 77.3% in rural areas and 62.1% in major urban areas. The contributions from local authorities ranked second, ranging from 15.9% in rural areas to 9.3% in major urban areas and 7.4% in other urban areas. In every district/municipality, most funds to meet operating costs were borne by parents except in Narok district where the County Council contributed an estimated 60.4% compared with 36.1% from community/school levies. Local authorities’ contributions were most significant in Narok (60.4%), Uasin Gishu (33.6%), Kisumu district (28.9%) and Kilifi (24.1%), and lowest in Nyandarua (0.4%) and Mombasa (4.5%). Contributions by religious organisations were more significant in Nairobi (9.2%), Garissa Central Division (8.3%) and Mombasa (7.9%). Contributions by plantations/ estates/ other companies were relatively high in Thika (13.4%), Nairobi (7.4%), Mombasa (7.4%), Nakuru district (6.7%) and Nakuru municipality (5.9%). Nongovernmental organizations made significant contributions in Garissa Central Division (11.5%). 10.7. Statistical Appendix Table 47(a) shows the annual operating costs by main expenditure item per pre-school for pre-schools that reported operating costs. Reported average operating costs per pre-school were low in rural areas, mainly because some expenditure items such as utilities and transport were minimal or non-existent in some pre-schools. An estimated 75.1% of the operating costs per pre-school in the rural districts were utilised on payment of teachers’ salaries, compared to 56.2% in major urban areas and 51.7% in other urban areas. The second major item of expenditure in most areas was children’s food, followed by other workers’ salaries. In the rural areas, the proportions of teachers’ salaries to total operating costs per pre-school were highest in Narok (94.5%) and Kilifi (89.2%), and lowest in Kakamega (52.8%). Only Narok had no expenditure on food and other workers’ salaries (since there were no nonteaching employees); while Kakamega had the highest share of expenditure on food per pre-school (24.7%) among the rural districts. 10.8. Statistical Appendix Tables 48(a) and 48(b) show that most of the operating costs per child were utilised on payment of personnel, mainly teachers’ salaries. In the rural areas, 76.5% of operating costs per child were expended on teachers’ salaries, compared to 53.9% in other urban areas and 51.3% in major urban areas. In both major urban and other urban areas, the second major item of expenditure in most regions was children’s food, followed by other workers’ salaries, utilities, and teaching materials. In rural areas, proportions of teachers’ salaries to total operating costs per child were highest in Narok (95.6%) and Kilifi (90.0%), and lowest in Uasin Gishu (52.2%) and Kakamega (60.1%). Uasin Gishu had the highest share of food to total operating costs per child (28.3%) among the rural districts. 10.9. The ratio of mean operating costs per child (Statistical Appendix Table 48) to mean fees per child (Statistical Appendix Table 28) was highest in Thika (2.4), followed by Uasin Gishu (2.0), Kisumu district (1.9), Narok (1.5), Mombasa (1.2) and Nakuru district (1.2). Although some of the differences could be due to data quality problems (and amplification of data quality problems by the small values of both numerator and denominator), this implies that, in these areas, children’s fees do not fully meet the cost of running the ECCD centre and either grants/aid would be necessary to meet the shortfalls, or the parents would be asked to shoulder the additional burden.
CURRENT MARKET VALUE
10.10. The current market value of pre-schools, presented in Statistical Appendix Table 49, was highest in major urban areas, followed by other urban areas, and lowest in rural areas. In major urban areas, Mombasa pre-schools had higher current market values than in Nairobi; while Nakuru municipality had the highest followed by Kitale in other urban areas; and Kakamega and Kilifi had the highest, and Kisumu, Machakos, Narok, Uasin Gishu and Nyandarua the lowest among the rural districts. The data for Garissa Central Division are not comparable to other areas since land was reported in area measurement but not in value. The community was the main contributor to pre-schools’ facilities in most districts/municipalities. 10.11. Statistical Appendix Tables 50 and 51 show that pre-schools attached to a primary school reported slightly higher current market values than standalone pre-schools, except in Thika, Nakuru municipality,
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Eldoret and Machakos. The higher average current market values in attached pre-schools could be attributed to (a) inclusion of assets owned by the primary school particularly land, and/or (b) availability and quality of financial records, and/or (c) demand by the primary school that the pre-school meets certain minimum standards of construction. 10.12. Due to valuation problems with respect to land, current market value of pre-schools excluding land were computed, as shown in Statistical Appendix Tables 52 and 53. Comparing Statistical Appendix Tables 49 and 52 shows that land was a major item in the total current market value in most study areas. Land valuation was particularly complicated. For example, in the case of land donated by the central Government, local authority or religious organisation, but where the community paid certain fees or charges, the respondents were unable to put a value on land or to allocate the value by sponsor. Some of them gave the value of the fee/charges paid. 10.13. Current market value on, say, land should be interpreted with caution since the respondents were teachers rather than land valuers. In addition, some respondents reported current market value for a particular facility, and source(s) of funding that were less than the total current market value. As in the case of operating costs, the difference was reported in the Statistical Appendix Tables as “not specified”.
BANK ACCOUNTS
10.14. Statistical Appendix Table 54 shows that 44.6% of the responding pre-schools in major urban areas reported that they owned a bank account, compared with other urban areas (44.3%) and rural districts (13.7%). Within other urban, Nakuru (64.7%) had the highest proportion of centres which owned bank accounts, while Kitale (28.6%) had the lowest. In the rural districts, Nyandarua (40.0%) and Narok (25.0%) reported the highest proportions of pre-schools owning bank accounts, compared with Machakos (4.3%), Kisumu district (4.8%) and Kakamega (5.8%).
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CHAPTER 11: FEEDING AND HEALTH INTERVENTIONS
FEEDING Feeding Arrangements 11.1. The survey collected information on children’s feeding arrangements during their stay in the pre-school. Statistical Appendix Table 55 shows that in 684 pre-schools (79.0%), children feed during their stay in the pre-school. The largest proportions of pre-schools in which no feeding arrangements were reported were in Kisumu district (45.2%), Kisumu municipality (34.8%), Kilifi (34.0%), Uasin Gishu (33.3%), Nakuru district (31.6%) and Kericho (31.5%). In Machakos district, children in 111 pre-schools (80.4%) carry food from home. In the rural areas, children in 355 pre-schools (69.2% of those with feeding arrangements) carry food from home, compared with major urban areas (39.1%) and other urban areas (33.9%). However, the main source of food in major urban areas (51.3%) and other urban areas (46.4%) was from optional or compulsory fees charged by the centre. Feeding under the World Food Programme (WFP) and National School Feeding Council of Kenya was reported by a small proportion of pre-schools, namely, Nairobi (1 centre), Thika (1 centre), Kilifi (4 centres), Machakos (3 centres), Nakuru district (1 centre), Kericho (1 centre), Narok (1 centre) and Garissa Central Division (9 centres). 11.2. Statistical Appendix Table 56 gives a breakdown of pre-schools in each district by the number of times children feed during their stay in the pre-school. Most of the pre-schools (87.7%) had only once-a-day feeding arrangement. In sixty centres (8.8%), children feed twice a day and in 24 centres (3.5%) children feed three times a day. Major urban areas (42.6%) reported the largest number of pre-schools where children feed more than once a day; compared with other urban (10.7%) and the rural districts (5.7%). Districts/ municipalities where some pre-school children feed three times a day were Mombasa, Nairobi, Thika, Nakuru municipality, Kisumu municipality, Uasin Gishu, Nakuru district, Kericho and Kisumu district. 11.3. In most pre-schools, food not carried from home is prepared at the centre. Statistical Appendix Table 57 shows that, of the 265 centres where child feeding is provided at the pre-school, 244 (92.1%) prepare food at the centre. The balance of 21 centres (7.9%) make different feeding arrangements e.g. some pre-schools in Nairobi serve food supplied from central kitchens. 11.4. Statistical Appendix Table 58 shows the main type of fuel used in cooking by the 243 pre-schools which prepare food at the centre. The difference of one centre between Statistical Appendix Tables 57 and 58 was due to a centre in Mombasa which only mixes juice and unpacks biscuits at the centre and hence does not do any cooking. Firewood was reported as the major fuel in rural areas (86.9%); and charcoal in both major urban areas (40.0%) and other urban areas (45.5%). Wood-based fuels (firewood and charcoal) were the main source of cooking fuel in major urban areas (50.8%), other urban areas (81.8%), and the rural districts (97.2%). In major urban areas, use of kerosene, gas and electricity was significant, but less significant in other urban areas and the rural districts. School Milk Programme 11.5. The School Milk Programme was introduced by a Presidential Decree in 1979 with a view to improving the nutrition and health status of school children and to enhancing school participation. The scheme is supposed to cover the entire population of children in public primary schools. However, Statistical Appendix Table 59 shows that some pre-school children, especially in attached pre-schools, have access to the milk. Responses to the survey indicated that special arrangements are made by some primary school headteachers to provide the milk to pre-school children in the attached pre-schools. Similar arrangements also exist in some pre-schools in Machakos district for the benefit of nearby unattached pre-schools. Of the 866 responding pre-schools, only 94 (17.6%) of attached and 4 (1.2%) of unattached pre-schools reported that their children access the milk.
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11.6. It should, however, be noted that data on feeding arrangements cannot be used to draw conclusions on how many children feed during their stay at the pre-school. A response that a pre-school conducts feeding does not imply that all children enrolled at the centre feed during their stay at the pre-school. For example, where levies for child feeding at the centre are optional, it is possible that some of the children do not feed during their stay at the pre-school.
HEALTH Immunization 11.7. Although no pre-school is expected to conduct any immunization, its concerns on whether children are immunized, and actions taken on children who are not fully immunized, would help improve immunization awareness and coverage. To collect data on immunization, pre-school headteachers were asked to supply information on whether they demand child health immunization records when a child seeks admission; number of fully immunized children who were admitted in January 1995; and action taken on a child who seeks admission and is not fully immunized. 11.8. Statistical Appendix Table 60 shows that the proportion of pre-schools that requests for health immunization card was highest in major urban areas (81.1%), followed by other urban areas (75.7%) and rural areas (63.8%). While all the pre-schools in Nakuru and Kitale municipalities reported that they demanded production of a health immunization card, there were wide variations in other areas, ranging from Nairobi (83.0%) to Garissa Central Division (42.9%) and Thika (42.9%). In rural areas, the highest proportion of pre-schools that demanded production of a health immunization card was in Machakos (76.8%), followed by Kericho (75.9%), Kilifi (70.0%) and Uasin Gishu (64.4%). Analysis of pre-schools by request for health immunization card and main pre-school sponsor shows very little variation in most districts/municipalities. 11.9. As shown in Statistical Appendix Table 61, the largest number of pre-schools (58.3%) reported that they would either refuse admission or admit but alert parent or health personnel if a child sought admission when it was not fully immunized. However, a significant 44.7% of pre-schools in the rural districts would admit and take no further action, compared with major urban areas (34.5%) and other urban areas (26.1%). Thika reported 71.4% of pre-schools as not taking any action on a child who seeks admission and is not fully immunized, followed by Nyandarua (62.5%), Garissa Central Division (57.1%), Kisumu district (49.2%) and Kakamega (48.5%). At the other end were Kitale and Nakuru municipalities which reported that all pre-schools take action on children who are not fully immunized on admission. Other Health Interventions 11.10. The survey sought information on whether the pre-school had participated in growth monitoring, vitamin A supplementation, iron supplementation, de-worming, eye check-up, ear check-up, or any other health interventions during the period 1990-1995. As shown in Statistical Appendix Tables 62(a) and 62(b), the most common activity reported in major urban areas (55.7% of pre-schools) was growth monitoring, eye check-up in other urban areas (34.3%) and growth monitoring in the rural districts (16.5%). Growth monitoring was the most significant health intervention in Mombasa (41.2%), Nairobi (61.4%), Kilifi (26.0%), Nyandarua (12.0%), Machakos (15.2%), Uasin Gishu (6.7%), Nakuru district (3.2%), Kericho (18.5%), Narok (16.2%), Kisumu district (40.3%) and Garissa Central Division (35.7%). The relatively better performance in urban areas (e.g. Nairobi) could be partly explained by proximity of pre-schools to health facilities and hence short distances covered by health personnel wishing to access pre-schools. Distance to a Health Facility 11.11. Statistical Appendix Table 63 gives a breakdown of pre-schools by distance to the nearest health facility. Most pre-schools in major urban areas (74.6%) and other urban areas (58.6%) were within two kilometres of a health facility, compared to only 25.4% in the rural areas. Only one pre-school in other urban
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areas was situated more than 10 kilometres from a health facility, compared to 48 pre-schools (7.1%) in the rural areas. The rural districts that reported the highest proportions of pre-schools as lying within 3 kilometres from a health facility were Garissa Central Division (100.0%), Nakuru district (61.1%), Kakamega (60.6%), Kisumu district (58.1%) and Kericho (51.9%). In addition to scarcity of transportation in the rural areas, long distance to a health facility implies difficulties and delays in availing children medical care in case of emergency. Disability 11.12. In the ECCD survey, disability was defined as a limitation in an individual’s ability to perform an activity in a manner that is considered to be normal. The six common disabilities identified by the survey were difficulties in speaking, hearing, seeing, moving legs (lower limbs) or arms (upper limbs), and learning (mental retardation), either in mild or profound form. The definition of disability excluded injuries or conditions of durations of less than six (6) months. 11.13. A national census of disabled persons was conducted as part of the 1989 Population and Housing Census. The census reported that the prevalence of disabilities in the total population was 1.4%, that most of the disabled persons had no education, and that the main disabilities were in the lower limbs, vision, hearing and mental retardation, as reported in the Economic Survey 1991 published by the Central Bureau of Statistics. 11.14. Data on reported disabilities are set out in Statistical Appendix Table 64. Overall, 1,079 disabilities among the 51,915 children were reported, i.e. 2.078%, which is higher than the national prevalence of disabilities (1.4%) for all age-groups reported in the 1989 Population and Housing Census. There were more disabilities reported among boys than girls for every disability, except in Nairobi. The most prevalent disabilities were difficulties in speaking at 256 (155 boys and 101 girls). This was followed by difficulties in hearing (242: 143 boys and 99 girls), mental handicap (204: 122 boys and 82 girls) and seeing (200: 112 boys and 88 girls), while the least were disabilities of the upper limbs i.e. arms (52: 29 boys and 23 girls). The prevalence of disabilities was highest in rural districts (2.487%), compared to other urban areas (2.144%) and major urban areas (0.406%). At the district/municipality level, high prevalence of disabilities among pre-school children was reported in Thika (8.661%), Kisumu district (4.193%), Kilifi (3.807%), Narok (3.599%), Kitale (3.315%) and Kericho (3.145%). The relatively high number of disabilities of the lower limbs reported in Thika is from inclusion of a pre-school which mainly caters for disabled children. 11.15. In data collection, the enumerators were instructed to record disabilities rather than children. Therefore, a child suffering from all six disabilities would be recorded 6 times, first as having difficulties in seeing, second as having difficulties in hearing, third as having difficulties in speaking, etc. A ratio of disability to the total number of children enrolled in pre-schools should be interpreted as the prevalence of that disability. Disability data are also likely to suffer from high respondent bias, due to differences of opinion on the severity of a physical (or mental) condition that would be enumerated as a disability. A high prevalence of a disability in a district/municipality does not therefore necessarily imply that there were relatively more disabled children vis-à-vis other districts/municipalities given (a) that the reporting was on disabilities rather than children, and (b) respondent bias (perhaps including deliberate underreporting). 11.16. The comparability of the reported prevalence of disabilities by district/municipality could be affected by defects in the sample frame. First, if the list of pre-schools submitted by a district/ municipality omitted some special schools that enrol pre-school age children, the defects in the sample frame would under-represent disabilities in the respective study area. Secondly, even if a district/municipality’s sample frame included all special schools that enrol pre-school age children, random (or even systematic) sampling does not guarantee representativeness of disability data. Nyandarua district, for example, had only one pre-school for children with disabilities in the sample frame, whose inclusion would have overstated the district’s average prevalence of disabilities. Stratification by type of school (i.e. whether special or otherwise) would only be efficient if systematic sampling was used and the number of special schools in a sample frame is equal to or exceed the sample selection interval in every district/municipality.
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CHAPTER 12: INVENTORY OF PRE-SCHOOL FACILITIES 12.1. The survey collected data on centre’s facilities or access to facilities, namely, tenure of the space used by the centre, ownership, construction materials of the main building, source of water, toilet facilities, classroom lighting, and children’s transport facilities.
PRE-SCHOOL PREMISES
12.2. The survey sought information on where the pre-school operates from, with the following options: own premises, rented premises, shares classrooms with a primary school to which it is attached, uses church, uses local authority social hall, uses parents/company’s social hall, operates in the open or under a tree, or any other arrangements. As shown in Statistical Appendix Table 65, a significant proportion (57.3%) of the 866 responding pre-schools operate from own or rented premises, or shared premises with primary school (23.8%), from a church (13.4%), or local authority hall or parents/employer hall (3.5%). Major urban areas (15.6%) and other urban areas (18.6%) reported slightly higher proportions of pre-schools which operate from a church compared to rural areas (12.5%). All urban pre-schools operate from such premises except one in Mombasa (reported under “other” category in Statistical Appendix Table 65) which operates from a condemned Government building. Seventeen (17) centres, which are all in the rural districts, had no premises and operate in the open air, and children are therefore subjected to vagaries of weather.
SCHOOL BUILDING MATERIALS
12.3. Distribution of pre-schools (excluding the 17 centres which operate in the open) by types of roofing material is shown in Statistical Appendix Table 66. Overall, 89.8% of the responding pre-schools reported iron/asbestos sheet roofing, with rural areas (93.0%), major urban areas (73.0%) and other urban areas (88.6%). In major and other urban areas, tiles/concrete were the next most common roofing materials, while the second most important roofing material in the rural areas was grass/makuti (roofing mats made from palm leaves). There were relatively more pre-schools with grass/ makuti roofing reported in Kilifi (31.0%), Garissa Central Division (14.3%), Machakos (5.1%), Kisumu district (4.9%) and Kakamega (4.0%). 12.4. As shown in Statistical Appendix Table 67, the most common wall materials used in building the main structure of the responding pre-schools were stone, brick or block (53.2%), followed by mud (25.9%) and wood (17.7%). In major urban areas, the most common types of wall materials were stone, brick or block (82.8%), compared with other urban areas (58.6%) and rural districts (47.2%). However, there were 11 pre-schools with iron sheet walls reported in Nairobi, and 8 mud walls reported in Kisumu municipality. In the rural areas, wood and mud walls contributed to 51.0% of all wall types reported. The proportion of pre-schools with stone, brick or block walls was highest in Mombasa (91.2%), Machakos (80.3%), Nairobi (79.5%) and Garissa Central Division (78.6%). 12.5. Statistical Appendix Table 68 shows that, in major urban areas, most pre-schools (91.8%) had cement, concrete or tile floors, compared with other urban areas (80.0%) and rural areas (46.0%). The largest proportion of earth floors were found in rural areas (51.0%), followed by other urban areas (20.0%) and major urban areas (4.1%). 12.6. Statistical Appendix Table 69 shows a cross-tabulation of pre-schools’ wall and roofing materials. In major urban areas, most pre-schools’ main structures had iron/asbestos sheet roofing combined with stone, brick or block walls; followed by tiles/concrete roofing combined with stone, brick or block walls. In other urban areas, iron/asbestos sheet roofing combined with stone, brick or block walls was the most common. In rural areas, iron/asbestos sheet roofing combined with stone, brick or block walls were the most common and were reported by 45.8% of pre-schools (i.e. 96.5% of 47.5%).
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12.7. The analysis was also done by (a) combining wall, roof and floor types, and (b) introducing indices of permanence (roof, wall) and modernity (floor). A permanent roof was taken to include iron/ asbestos sheet and tiles/concrete roofing, while grass/makuti was taken as temporary. Permanent wall was taken to include stone, brick or block and wood; while mud, iron sheets, grass or reeds wall materials were taken as temporary. Cement, concrete, or tile floor materials were taken as modern; and earth or wood as “not modern”. A pre-school building made of permanent roof, permanent wall and modern floor was assumed to give children the friendliest physical environment compared with the other extreme, i.e. temporary roof/wall and non-modern floor. 12.8. As shown in Statistical Appendix Table 70, in major urban areas, 98 (81.0%) of all pre-schools’ main building were of permanent/modern roof, wall and floor, and no pre-school was at the other extreme, i.e. temporary roof/wall and non-modern floor. In other urban areas, 57.1% of pre-schools were in the permanent/modern roof, wall and floor category while none were in the other extreme (temporary/non-modern wall, roof and floor). In the rural areas, only 228 pre-schools (35.0%) were in the permanent/modern roof, wall and floor category, while 27 (4.1%) were in the category of poorest structures (temporary/non-modern wall, roof and floor). There were 397 (60.9%) pre-schools in the rural districts with combinations of building materials between the two extremes of permanent/modern and temporary/non-modern wall, roof and floor, compared with 23 (19.0%) in major urban areas and 30 (42.9%) in other urban areas. This implies that the physical environment in the rural pre-schools is less friendly compared to the urban areas.
WATER AND SANITATION
Access to Water 12.9. Statistical Appendix Table 71 gives the distribution of pre-schools by source of water used at the pre-school. In major urban areas, majority of the responding pre-schools (91.0%) reported using piped water, compared to other urban areas (78.6%), and rural areas (29.7%). Most pre-schools in the rural districts mainly get their water from stream, river, dam, borehole or well (63.7%). In the rural areas, Garissa Central Division (85.7%), Kilifi (58.0%) and Kericho (40.7%) reported the highest access to piped water; compared to Narok (16.2%), Machakos (17.4%), Uasin Gishu (17.8%) and Kakamega (19.2%). Taking clean water sources to include only protected wells, boreholes, piped water and rain water, an estimated 94.3% of pre-schools in major urban areas had access to clean water sources, compared with other urban areas (88.6%), and rural areas (56.2%). 12.10. During data processing, pre-schools that reported “no-water”, “carry water from home” and “purchase from a commercial seller” were all grouped under “no water” category. The data shows that 32 pre-schools reported that they had no water. Kericho (5.6%), Machakos (6.5%) and Nakuru district (9.5%) reported pre-schools as having “no water”. In urban areas, only Nairobi (4 centres), Mombasa (1 centre) and Kisumu municipality (1 centre) reported pre-schools with “no water”. Given the poor quality of open surface water in Nairobi, the case of centres that draw water from stream, river or dam may need official intervention. Access to Sanitary Means of Excreta Disposal 12.11. The survey collected data on access to toilets by focusing on the type of toilet that pre-school children use, and not the toilets that the pre-school owns, thus putting a clear distinction between ownership and use. As shown in Statistical Appendix Table 72, children in 80.6% of the 866 responding pre-schools had access to pit latrine and 16.7% to flush toilet. At the other extreme, children in 21 pre-schools (2.4%), mostly in the rural areas, did not access any toilet. A large proportion of pre-schools in major urban areas reported flush toilet (67.2%), compared with a moderate proportion of 35.7% in other urban areas, and a low 5.6% in the rural areas. It is possible that flush toilets reported in the rural sample were mostly in urban areas within the rural sample.
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12.12. The Public Health (Drainage and Latrine) Rules, a 1960 subsidiary legislation made under the Public Health Act (cap. 242 of the Laws of Kenya), set outs the definitions and minimum construction standards for various types of excreta disposal facilities e.g. water closets, pail closets and pit-closets. The Sanitation Field Manual for Kenya (1987) gives details of technical specifications for construction of various types of sanitary means of excreta disposal, including the means of excreta disposal that are not considered sanitary from a health standpoint. The sanitary means of excreta disposal include septic tank, ventilated improved pit (VIP) latrine, alternating twin-pit VIP latrine, and pour flush; but excludes aqua privy, bucket latrine systems, and composting latrine. Using these specifications, the proportions of pre-schools in major urban areas with sanitary means of excreta disposal (flush and pit latrines) was 99.2%, compared to other urban areas (98.6%) and rural areas (96.9%). However, due to the specificity of concepts used by health authorities (e.g. an almost full pit latrine is not counted as a latrine but a health hazard), respondent’s self-reporting as opposed to enumerator’s observation and inspection might overestimate the degree of access to sanitary means of excreta disposal. 12.13. During data edit, cases of “in the bush” and “no toilet” were combined into one category of “no toilet”. Kilifi (20.0%) reported the largest number of pre-schools in which the children had “no toilet”, followed by Narok (8.1%) and Kisumu district (4.8%). 12.14. Statistical Appendix Table 73 shows estimated numbers of children per toilet stall by district/ municipality for attached and unattached pre-schools. The indices for attached and unattached pre-schools were computed separately for fear that headteachers of attached pre-schools could have included primary school toilet stalls in reporting pre-school stalls. The number of children per toilet stall in attached pre-schools ranged from 6.9 in Thika to 44.6 in Nakuru municipality; and from 10.3 in Narok to 46.1 in Kilifi for unattached pre-schools. Nakuru municipality, Eldoret, Nyandarua, Uasin Gishu, Kericho, Narok and Garissa Central Division reported lower indices for unattached pre-schools compared to attached pre-schools. The indices for attached and unattached pre-schools were close, except in Thika.
SOURCE OF CLASSROOM LIGHTING
12.15. Statistical Appendix Table 74 shows that most of pre-schools (79.2%) depended on direct sunlight, especially in the rural areas (89.3%). Use of electricity was more common in major urban areas (58.2%), compared with other urban areas (34.3%) and the rural districts (4.3%). Fifty two (52) pre-schools reported that they use solar energy as the source of classroom lighting, mainly in Uasin Gishu (15), Kakamega (13) and Nakuru district (8).
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CHAPTER 13: OVERVIEW, CONCLUSIONS AND RECOMMENDATIONS
OVERVIEW
13.1. The report of the ECCD survey carried out in 1995 reviews the structure and development of pre-schools, describes the organization and methodology of the survey, and presents an analysis of the results. 13.2. In the review of the structure and development of early childhood care and education, it was found that pre-schools have come up as alternative ways to traditional methods of taking care of young children. The pre-schools are referred to by various terms including day-care centres, nursery schools, kindergartens, duksi/madrassa, etc. 13.3. The fundamental role played by pre-schools and their centrality in Kenya’s formal education system has made them the subject of various studies. Among the main areas of interest are: their number and structure, types and quality of services offered, size of enrolment, and number and quality of their teachers and other caregivers. 13.4. The emerging role of pre-schools in Kenya’s educational system has been recognized, and has led to the establishment of specialized institutions within the Ministry of Education. The main one is the DICECE programme, under NACECE, which is established in every district in the country. At the district level, DICECEs train pre-school teachers, develop localized curriculum, coordinate district-based research, conduct awareness programmes, and supervise and inspect pre-school programmes. The DICECE staffs are accountable to the District Education Officers (in the case of districts) or Municipal Education Officers (in the case of municipalities) in their day-to-day operations. 13.5. The review has shown that pre-school education in Kenya is carried out on a partnership framework. The joint efforts of the Government, local authorities, parents and local communities, voluntary organizations, religious bodies and private sector have contributed to significant expansion of pre-school care and education. Review of Existing Information 13.6. The report has attempted to review available information on early childhood care and education. This was carried out by reviewing the annual statistics on pre-schools compiled by the Ministry of Education, and some recent studies on the status of pre-school education. 13.7. The annual statistics on pre-schools is a useful tool in planning of pre-school education. Despite their usefulness, the statistics have some gaps and discrepancies. One gap is that enrolment data by age of children are not widely disseminated. There is also lack of data on school facilities, types of services offered, etc. In addition, there are several discrepancies, e.g. there are various cases of the same reported total enrolment for a district/ municipality for two or three consecutive years. 13.8. The reported enrolment for 1994 was 951,997, comprising 485,352 male and 466,645 female children. A rough estimate based on enrolment and estimated population aged 3-6 years gives a national gross enrolment ratio of about 35%. However, gross enrolment ratios for pre-school education are somewhat different from those of primary and secondary education due to lack of a fixed and compulsory period of attendance in pre-school education. 13.9. Some of the recent studies on early childhood care and education reviewed in this report highlight some characteristics of pre-school education which are not collected through the annual returns compiled by the Ministry of Education. They also address in detail some issues that shed light into the structure of pre-school education in Kenya. The studies are limited in their scope and the degree to which the results could be generalized to represent the whole of Kenya, particular provinces, or districts. In particular, the methods
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used for selection of districts (study areas) vary from statistically selected samples to subjective/purposeful selection; the respondents varied; and the data was collected in different years. The 1995 Sample Survey of ECCD Centres 13.10. As a response to the need for current and reliable information, the survey of early childhood care and development centres, and which is the subject of this report, was carried out in 1995. The survey covered 906 ECCD centres, and was conducted on a sample of 17 districts/urban centres representing urban (slum and non-slum), pastoral and other rural areas. 13.11. The survey collected information on (i) identification and location particulars of the ECCD centre, (ii) enrolment data, (iii) size and structure of teaching and nonteaching staff, (iv) centre’s financial data, (v) child feeding, (vi) nature of health surveillance/interventions at the centre, and (vii) inventory of centre’s facilities. 13.12. The fieldwork did not run smoothly as planned. The data collection exercise took longer than expected, mainly because the use of random sampling design at the district level generated a geographically scattered sample. Also, there was perceived insecurity on the part of the supervisors and enumerators in two rural districts. Because of such logistical problems, the survey fieldwork took about one month instead of the planned 5 days. 13.13. The control of questionnaires from the field was made by use of a checklist. This was followed by thorough editing of the questionnaires involving scrutinizing for errors, omissions and ambiguities. Further coding or conversion of responses to numerical codes was effected before data entry commenced. 13.14. Data were entered using SPSS. After data entry, validation runs were carried out in an effort to produce an error-free data file. Eventually, a minimum of 64 basic tables were prepared for this report. Accuracy of the Survey Results 13.15. In this survey a maximum of three visits were made to each sampled pre-school so as to enhance response. In some cases the respondents, majority being headteachers of pre-schools, were asked to refer to past records. The main limitation to this method was that some pre-schools kept no records; the existing records were not properly kept; or they were not readily accessible. This resulted in many blanks for important aggregates such as past child enrolment, financial data, and teacher turnover. In addition, soliciting of historical data put a great strain on respondents’ memory to recall past events. Lack of proper records also resulted in several cases of discrepancies between the reported totals and the summation of individual entries. 13.16. In addition to sampling errors, the survey results may have been compromised by any of the following non-sampling errors:
(a) Inaccuracies of previous surveys on which the sample frame (or weights) have been based; (b) Inaccuracy of information provided by the respondents; (c) Errors by interviewer in recording responses; or (d) Errors in editing, coding, and data entry.
13.17. Although little could be done about (a) and (b), the other errors were reduced to a minimum by close supervision of the data collection exercise, editing of survey returns, and thorough checking during data entry and validation.
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SUMMARY OF SURVEY FINDINGS
Profiles of Pre-schools 13.18. The coverage of the ECCD sample survey was efficient resulting with a 95.6% response rate. The survey revealed the central role that parents/community have played in the growth and maintenance of pre-schools. Most pre-schools offer formal education and therefore act as a preparatory stage for entry into primary schools. Registration process was not clearly understood by the respondents. The survey also revealed that between January 1994 and the date of interview (around July 1995), about 14% of pre-schools were not supervised. There was also a general misunderstanding of who a sponsor of a pre-school was. For example, community pre-schools which also received some support from, say, local authority, religious organization or a company, could have reported as sponsored by any of them. Enrolment in Pre-schools 13.19. The 1995 ECCD survey revealed a gross enrolment ratio of 36.0% in the rural districts, underscoring the fact that despite its growth, pre-school care and education is netting a very small proportion of pre-school age children. While the survey showed that 10 district/municipalities had reported higher enrolment ratios of boys than girls, the official pre-school statistics showed higher gross enrolment ratio for boys only in three study areas. Pre-school fees charged were low in rural areas compared to urban areas. Pre-school Personnel 13.20. Most of pre-school employees were females. Overall there were slightly over two teachers per centre. In the rural areas, mean employee’s monthly salaries were low and a majority of pre-school teachers were of low education, which could imply that employment at pre-school is taken as a last resort. Most pre-school teachers do not stay in employment for long periods, with only teachers in Machakos district reporting an average of about nine years in ECCD employment. Financing of Pre-schools 13.21. The role of parents, either through Harambee or school fees/levies, in the financing of pre-school education was evident from the data on operating costs and current market value of the pre-schools. Other major sponsors are local authorities, religious organizations, companies and private individuals. The survey results show that community/school levies were the main sources of operating costs, the bulk of which went towards meeting employees’ salaries. The high ratio of employees’ salaries to total operating costs was reflected by the large number of pre-schools that reported not owning a bank account, since what is received from school fees/levies is paid out directly as employees’ salaries. Feeding and Health Interventions 13.22. Most pre-schools have made some arrangement to ensure that children drink or eat something during their stay in the centre. Children attending 52.7% of rural pre-schools carry food from home while the proportion was lower in other urban and major urban areas. Firewood/charcoal was the main fuel used in cooking food in the 243 pre-schools that prepare food within the centre. The School Milk Programme is beyond the reach of most of the vulnerable pre-school children, since only 98 pre-schools (11.3%) had access to the school milk, courtesy of the headmasters/ headmistresses of the local primary schools. 13.23. The survey revealed some degree of lack of concern on health issues. While 67.2% of the responding pre-schools ask for health immunization card when a child first seeks admission, only 58.3% would take action of informing parents or health personnel or refuse admission altogether. Concern with other health interventions such as growth monitoring was generally weak.
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Pre-school Facilities 13.24. Most responding pre-schools operate either under semi-permanent or permanent premises. Nevertheless, there were 17 pre-schools where children learn in the open or under a tree. While piped water is accessible to a large proportion of urban pre-schools, it is only accessible to a small proportion of rural pre-schools. The case of the few pre-schools that draw water from streams, rivers or dams, particularly in the urban areas, needs official intervention. 13.25. A large proportion of pre-schools in urban areas reported as having access to flush toilets. Pit latrines were commonly used in pre-schools in rural areas. There were a few cases of pre-schools with no toilets, particularly in Kilifi, Narok and Kisumu districts.
RECOMMENDATIONS
13.26. Development of pre-school education in Kenya needs a viable database. To come up with a good system for monitoring early childhood care and education, it is recommended that:
a) The Ministry of Education should prepare clear guidelines to be used by field staff in collection of basic data on pre-schools, including enrolment by age and sex, and financial data.
b) Initiate a process of forwarding comprehensive information from the field to the Ministry
of Education headquarters, and compile a publicly-available regular report on pre-school education.
c) A clear definition of a sponsor needs to be made. d) Regular supervision of pre-schools is important to ensure that accepted levels of education
and environment are maintained. Arrangement should be effected to facilitate Zonal Inspectors and DICECE staffs to make regular visits to each centre at least once a year.
e) The computed gross enrolment ratios were not directly comparable across
districts/municipalities since the mean number of years taken by children in pre-schools differs. It is recommended that a household-based survey module on pre-school age children be tagged to the next round of the National Household Welfare Monitoring and Evaluation Survey conducted by the Central Bureau of Statistics.
f) The collection of data for the 1995 ECCD Survey would have been made easier if pre-
schools maintained records of enrolment. It is recommended that the Ministry of Education advises pre-schools on keeping some form of enrolment and attendance records.
g) The survey revealed that 10 out of 17 municipalities/districts registered higher gross
enrolment ratios for boys compared to girls. It is recommended that, the general population, in conjunction with other interested organizations, be sensitized on the importance of enrolling both boys and girls in early childhood care and education.
h) There is need to introduce some kind of scheme of service for pre-school teachers e.g.
recommended minimum salaries by education level and ECCD-training. i) Parents/communities should be sensitized on the dangers of food contamination,
particularly food carried from home by pre-school children.
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j) Demand for health immunization card should be made compulsory, and children not fully
immunized referred to health personnel through their parents. There is also need for training of teachers and other caregivers on micronutrient malnutrition, food sources of various micronutrients (e.g. iron, iodine, vitamin A, zinc), and iron and vitamin A supplementation.
k) Since access to potable water and efficient waste disposal are essential for the health of the
pre-school child, it is important to educate pre-school personnel as well as parents/communities on the dangers of open waste disposal and drinking unsafe water.
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ANNEX 1: CODES FOR ECCD SURVEY OPEN-ENDED QUESTIONS Question 301 (i) Sex: M = 1 F = 2 (ii) Main type of work
Teacher = 01 Child-minder/Maid = 02 Manager/Administrator = 03 Bookkeeper/Bursar = 04 Secretary/Clerk = 05 Cook = 06 Cleaner/Messenger/Groundsman (groundskeeper)/Gardener/ Subordinate staff = 07 Watchman/Caretaker/Security = 08 Driver = 09 Other specify = 10
(iii) Status of work
F = 1 P = 2
Question 302 (i) Sponsor of Training
N/A or Blank = 1 Self/Parent = 2 DICECE/UNICEF = 3 Religious Organisation = 4 Ministry of Culture and Social Services = 5 Company = 6 Local Authority = 7 NGO = 8 Other = 9
(ii) Year of Completion
N/A = 9999 Undergoing training = Year of Completion e.g. 1995, 1998, etc No date = 0000
Question 407 (i) Anticipated sponsors of facilities
Community/PTA = 1 Religious Organisation = 2 Private individual(s)/Company = 3 Plantation/Estates = 4 Local Authority = 5 Central Government = 6 NGO = 7 Other = 9
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ANNEX 2: TERMS OF REFERENCE SAMPLE SURVEY OF ORGANIZED CHILDHOOD CARE AND PRE-SCHOOL EDUCATION BACKGROUND Baseline data for planning, policy formulation and monitoring of early childhood care and pre-school education are inadequate. Available information indicates that in 1994, about 951,997 children were attending 19,083 pre-schools for early childhood care and education, and with a teaching force of 27,829. These statistics are neither comprehensive nor totally reliable. The collection of data in some areas is difficult and a number of schools are operating without the knowledge of the Government. There are also major gaps of information regarding types of services provided, the actual number of teachers and their qualifications, their salaries, teaching materials, equipment, physical facilities, centre’s management, school fees, financing, and sponsorship. OBJECTIVES This study has two main objectives: (1) To undertake a sample survey of early childhood care and education centres; and (2) To design a computerized database management system for monitoring early childhood care and
education. SPECIFIC TASKS Sample Survey: The unit of analysis of survey shall be the ECCD centre. A total of 800 ECCD centres will be selected using a purposeful sampling design which is intended to characterize service delivery in different environments and management/sponsorship systems. The sampling design shall conform to the guidelines set forth in the Table below: TABLE 1: SAMPLING DESIGN
SPONSORSLocation Sample Size Parents &
Community Local
Authorities Religious
Organization NGO Private
Urban Slum areas Other urban Rural Plantation Settled Agriculture Pastoralism
100 150
150 300 100
30 80
90 130 60
5 10
10 20 10
10 20
20 40 10
10 20
20 50 10
5 10
10 20 10
TOTAL 800 390 55 100 110 55 The main variables to be generated by the survey shall include the following: 1. Location code for various groupings used in Table 1. 2. Population size of community/village: total and 0-6 year old population. 3. Main sponsors: e.g. municipal council, county council, town council, urban council, religious
organization, private companies, plantations, estates, private individuals, parents/community association, other NGOs.
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4. Whether the pre-school is (a) attached, (b) linked or (c) not related to a primary school. Do the pre-school and the primary school share the same school committee?
5. Year the school was established. 6. Enrolment history: 1990, 1991, 1992, 1993, 1994, 1995. Enrolment broken down by (a) boys, girls,
and (b) age group 1, 2, 3, 4, 5, 6 and >6 years old. 7. Number of teachers, gender of teacher (male, female). 8. Number of trained teachers. Who provided training? (a) Government (b) private 9. Training received by teachers: (a) two-year course (b) 5-week course (c) one-year course (d) others,
specify. 10. Teacher’s salary per month. 11. Educational attainment of teachers (for each teacher: primary, secondary, and postsecondary). Years
of teaching experience. How long has she/he been teaching in the pre-school centre? 12. School hours: (a) morning only (b) whole day. 13. Of the children presently enrolled, how many are unable to pay fees? 14. Does pre-school provide feeding? What is provided? How many times a day? 15. If feeding provided, source: (a) pre-school (b) parents (c) World Food Programme (d) other
organizations. 16. Does school conduct growth monitoring? If yes, by whom? 17. Has any of the following health interventions been conducted and by whom? (a) De-worming, (b)
immunization, (c) eye/ear check up, (d) vitamin A capsule distribution. Health providers for each of above may include government clinic/dispensary, Mission clinic, private doctor, NGO, religious organization.
18. Who do you consider to be your supervisor? (a) DICECE, (b) Headteacher, (c) Others, specify. 19. Who made supervisory visit in last year (a) no visit (b) DICECE (c) pre-school supervisor (d)
headteacher (e) others, specify? How many visits in the last year? 20. How many children presently enrolled have disabilities (e.g. problem of vision, hearing, etc.)? 21. Is the pre-school registered (yes, no)? If yes, what is the registration number? 22. Who is in charge of managing the pre-school? (a) pre-school committee, (b) headteacher (c) NGO (d)
others, specify. 23. What is the composition of the management committee? 24. Does the management committee have a bank account? 25. Estimate the cost of the school facility: (a) building materials, (b) land, (c) furniture and equipment.
Indicate if cost of labour was contributed by community.
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26. Source of funds for construction of pre-school and its facilities? (a) Harambee/parents, (b) NGO, (c)
religious organization, (d) private, (e) others. 27. Source of funds for operating costs? (a) Parents, (b) sponsors, (c) others, specify. 28. Estimate of monthly operating cost/breakdown by (a) teacher salary, (b) food, (c) school materials,
(d) maintenance, and (e) others, specify. OUTPUTS Survey Output: Prior to the launching of the sample survey, the Consultant will be required to submit a copy of the Sampling Design, Questionnaire and Survey Manual including methods for data quality control, and Coding Instructions. The survey results will be summarized in a report that provides a descriptive analysis of the characteristics of ECCD centres analyzed according to the groups described in Table 1. The main topics to be covered by the report shall include (but not limited to) the following: 1. Profile of ECCD service provision by groups and by main sponsors. 2. Trends in enrolment by age group. Proportion of 0-3, 3-6 year old in the community currently
enrolled in the ECCD centre. 3. Pupil-teacher ratio. 4. Teacher/caregiver profiles: gender, age, education, training, experience, turnover rates, working
hours. 5. Teacher training profiles: who trains, how long, cost of training. 6. Cost of setting up and operating ECCD centres:
(a) Capital cost - land, building, furniture, equipment, kitchen. (b) Operating cost - teacher salary, food, school materials.
7. Source of funds for capital cost, and for operating cost. 8. Health and nutrition services provided - what services, how often. 9. Supervision of ECCD centres - who, how often? 10. Profile of ECCD centre management. 11. Profile of ECCD centre's financing. Database Management System: The output shall consist of a system design for collection and retrieval of data on ECCD centres nationwide. The design shall include the following features: (a) computerized database management system to be installed at the Ministry of Education (MOE) Pre-School Unit; (b) proposed method for data collection; (c) resource requirements for installing the system at MOE - including manpower, computer, and materials; and (d) resource requirements for conducting a nationwide census of existing centres - roughly 19,000 in 1994 - and periodic updating of information. The main types of information shall consist of selected variables from the sample survey. (Note: Computer software called CAREFINDER (US) shall be made available to the consultant as a model for design of the database
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management system.) ADDITIONAL NOTES (Issued on May 4, 1995) Consultation with Other ECCD Studies Since the survey is intended to inform other future studies, the consultant shall:
(a) Collaborate with other ECCD study consultants in designing the questionnaire. The proposed questionnaire design may then include new variables not identified in the original Terms of Reference; (b) Make data files available to other ECCD study consultants as soon as these data files are cleaned and ready for analysis; and (c) Collaborate/consult with other ECCD study consultants in subsequent analysis of data.
Sampling The new sampling design proposed by the Consultants in their memo dated May 2, 1995 suggests a survey design covering 10 selected districts as alternative to the nationwide sampling in the original TOR. This is a realistic option given time and logistical constraints. However, there are two important criteria that should guide in the final sampling design: (a) Since the project is interested in information on differences in characteristics of pre-school centres according to the various sponsorship categories (i.e. parents/communities, local governments, religious/NGO and private), it would be essential to oversample those categories which may not be drawn in sufficient numbers in the random selection process within districts. This would likely be true of the religious/NGO groups and the privately run centres. In order to address this problem, it may be necessary to oversample (purposely) these groups, or to increase the overall sample size to about 900. (b) At least one district in the North Eastern province should be included in the final sample. Study Outputs The consultants shall adhere to the outputs specified in the Terms of Reference. The two main groups of outputs are those related to (a) the sample survey, and (b) the design of the database management system. For the sample survey, new variables may be included depending on the needs of the other ECCD studies. While the Consultant’s proposal did not spell out the methods for (b), it should be emphasized that the design of the database management system and its installation in the Ministry of Education are part of the output to be delivered by the study.
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ANNEX 3: THE EXTENT TO WHICH THE QUESTIONNAIRE MEETS THE TERMS OF REFERENCE
A) MAIN INPUT VARIABLE AS PER TOR CORRESPONDING QUESTION IN
THE ECCD QUESTIONNAIRE 1. Location of the centre Q102 Gives the districts,
divisions/municipalities and type of neighbourhood (urban slum, other urban, pastoral, plantations, settled agriculture) the Centre is located in.
2. Target (0 - 6 years) population See results of the pre-test. 3. Main sponsor Q109 Asks for identification of the main
sponsor in 1994. 4. Attachment/linkage to primary school Q114 Seeks information on whether the
Centre is linked or attached to a primary school, while Q116 is on whether the attached Centre shares the same management committee with the mother primary school.
5. Year centre was established Q104 Seeks information on when the
Centre was established. 6. Enrolment history Q201 Seeks information on enrolment for
the years 1990-1995 by age and sex, while Q202 seeks the same information for 1995 by grade/class/year of study.
7. Teachers - numbers Q301 Lists all Centre’s teaching and
nonteaching staff. 8. Teachers - number trained and training provider Q302 Solicits particulars of each Centre’s
teaching staff by ECCD-specific training, training programme and sponsorship of training, among other variables.
9. Teachers - type of training received Q302 Solicits particulars of each Centre’s
teaching staff by ECCD-specific training (training programme and duration) and highest teacher training college certificates obtained, among other variables.
10. Teachers - salaries per month Q301 Seeks particulars of employees
including gross salaries per month, among other variables.
11. Teachers - formal education Q302 Solicits particulars of each Centre’s
teaching staff by their highest educational attainment, among other variables.
Teachers - teaching experience Q302 Solicits particulars of each Centre’s
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teaching staff by their teaching experience i.e. number of years taken in teaching at both ECCD centres and other educational institutions, among other variables.
Teachers - years worked in the centre Q301 Solicits particulars of each Centre’s
staff by their length of stay at the Centre by asking the date of appointment, among other variables.
12. School hours Q118 Asks whether the children stay in the
centre during morning section only, during afternoon section, or for the whole day.
13. Ability to pay school fees Q206 Seeks information in respect of 1994
on the number of children, by gender; who had completed paying compulsory school fees and charges, made partial payment, or made no payment at all.
14. Feeding arrangements Q501 Asks whether the children take any
meals during their stay in school.
Q502 Asks the number of times children take food or drink.
Q504 Asks the type of food or drink the
children take at each meal break. 15. Sources of feeding Q503 Asks the provider of the meals. 16. Growth monitoring activities Q604 Seeks information on various health
interventions which include growth monitoring activities, among other issues.
17. Health intervention by type and provider Q604 Seeks information on Centre’s
involvement in various health interventions (de-worming, eye/ear check-up, and vitamin A and iron supplementation) by the last time the centre participated, and the type of provider, among other issues.
19. Supervision - who is your supervisor? Q119 Asks for identification of the
Centre’s main supervisor/ inspector. 20. Supervision - who made most supervisory visits in 1994 Q120 Asks whether the Centre has ever
been supervised.
Q121 Asks when centre was last supervised.
Q122 Asks who made most supervisory
visits in 1994. 21. Disabilities by type Q606 Inquires about the main types of
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disabilities, by gender of child, observed for 1995.
22. Registration of the centre Q105 Asks whether Centre is registered.
Registration number of the centre See the results of the pre-test. 23. Management of centre Q110 Inquires about who manages the
Centre on a day-to-day basis. 24. Composition of the management committee Q111 Asks whether the Centre has a
parents/school committee.
Q112 Asks for composition of parents/school committee by gender.
25. Does management committee operate a bank account? Q408 Asks whether the Centre operates a
bank account. 26. Estimate of the cost of school facilities Q404 Inquires about the current cost of
various facilities. 27. Sources of funds for various facilities Q404 Inquires about the current cost of
various Centre’s facilities by sponsor/source of finance.
28. Sources of funds for operating costs Q403 Inquires about the main sources of
funds for operating costs of the Centre for reference year 1994.
29. Monthly operating costs/break-down Q403 Asks for break-down of operating
costs.
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ANNEX 4: SELECTED REFERENCES Cochran, W. G., Sampling Techniques, Second edition, John Wiley & Sons, New York, 1963 Fisher, R.A. and F. Yates, Statistical Tables for Biological, Agricultural and Medical Research, Oliver and Boyd, Edinburgh, Fifth edition, 1957 Gakuru, O.N., P.F. Riak, P.H. Ogula, R. Mugo, and A.W. Njenga, Evaluation of NACECE-DICECE Programme, Kenya Institute of Education and Bernard Van Leer Foundation, Nairobi, August 1987 Jaetzold, R. and H. Schmidt, Farm Management Handbook of Kenya (Volume II: Natural Conditions and Farm Management Information: Part A: West Kenya; Part B: Central Kenya; Part C: East Kenya), Ministry of Agriculture, Nairobi, Kenya, 1982 Kenya, The Education Act, Cap. 211 of the Laws of Kenya, Government Printer, Nairobi, 1980 Kenya, Central Bureau of Statistics, Kenya Population Census, 1979: Volumes 1, Government Printer, Nairobi, 1981 Kenya, Public Health Act, Cap. 242 of the Laws of Kenya, Government Printer, Nairobi, 1986 Kenya, Ministry of Health, Division of Environmental Health, Sanitation Field Manual for Kenya, 1987 Kenya, National Centre for Early Childhood Education (NACECE) and Aga Khan Foundation, Evaluation Report of the Aga Khan Foundation Sponsored DICECE, Kenya Institute of Education, June 1990 Kenya, Central Bureau of Statistics, Economic Survey 1991 (Chapter 3: The 1989 Population Census Provisional Results), Government Printer, Nairobi, 1991 Kenya, Central Bureau of Statistics, Urban Household Budget Survey, 1992/93: Survey Instruments and Enumerators’ Reference Manual, August, Nairobi, 1992 Kenya, National Centre for Early Childhood Education (NACECE) and UNICEF, Early Childhood Care and Education in Kenya: A Report of an Evaluation of UNICEF-Sponsored Districts, Kenya Institute of Education, November 1992 Kenya, National Centre for Early Childhood Education (NACECE), Report of the Samburu Community-Based Early Childhood Care and Education Project (1990-1993), December 1993 Kenya, Ministry of Planning and National Development, District Development Plan, 1994-1996 (for various districts), Government Printer, Nairobi, 1993 Kenya, Central Bureau of Statistics, Kenya Population Census, 1989: Volumes I & II, Government Printer, Nairobi, 1994 Kish, Leslie, Survey Sampling, John Wiley & Sons, New York, 1965 Moser, C.A. and G. Kalton, Survey Methods in Social Investigation, Heinemann Educational Books,
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London, 1979 Mukui, John T., Kenya: Poverty Profiles, 1982-92, Report Prepared for the World Bank and the Ministry of Planning and National Development, Nairobi, Kenya, March 1994a Mukui, John T., Kenya’s Capacity to Monitor Children’s Goals: A Medium-Term Assessment, Report Prepared for UNICEF, Kenya Country Office, 1994b Owano, Alice, et al, The State of Pre-School Education in Kenya, Kenya Institute of Education, 1986 Pressat, Roland, Demographic Analysis: Methods, Results, Applications, Aldine-Atherton Inc., Chicago, 1972
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ANNEX 5: STATISTICAL APPENDIX TABLES Table 1: Statistics on Pre-schools in Kenya: 1994 Table 2: Statistics on Pre-schools in Kenya: 1993 Table 3: Statistics on Pre-schools in Kenya: 1992 Table 4: Statistics on Pre-schools in Kenya: 1991 Table 5: Statistics on Pre-schools in Kenya: 1990 Table 6: Percentage Changes in Statistics on Pre-schools in Kenya, 1994/1993 Table 7: Number of Sampled ECCD Centres Table 8: Comparison between Reported 1994 and 1995 ECCD Centres Table 9: Population in Urban Areas as Reported in the 1989 Census Table 10: Population Projections for Age 3-5 Years by District/Municipality, 1990-1995 Table 11: Response Status of the Sample Survey of ECCD Centres Table 12: Distribution of Pre-Schools by Year Established and Sponsor Table 13: Distribution of Pre-Schools by Sponsor Table 14: Distribution of Pre-Schools by Ownership and Type of Neighbourhood, 1995 Table 15: Distribution of Pre-Schools by Main Type of Service Offered, 1995 Table 16: Distribution of Pre-Schools by Registration Status and Enrolment Size, 1995 Table 17: Distribution of Pre-Schools by Management of ECCD Centre, 1995 Table 18: Distribution of Pre-Schools by Size of Management Committee, 1995 Table 19: Composition of Management Committees by Sex, 1995 Table 20: Distribution of Pre-Schools by Date of Last Meeting of Management Committee Table 21: Distribution of Pre-Schools by Attachment/Linkage to a Primary School, 1995 Table 22: Distribution of Attached Pre-Schools by Sharing Arrangements of Management Committee and
Headteachers’ Attendance of Primary School Staff Meetings, 1995 Table 23: Distribution of Pre-Schools by Main Supervisor and Sponsor Table 24: Distribution of Pre-Schools Which Reported Enrolment Data, 1990-1995 Table 25: Distribution of Pre-Schools by Enrolment Size and Main Sponsor, 1995 Table 26: Pre-School Gross Enrolment Ratios by Sex Based on the ECCD Survey, 1995 (%) Table 27: Pre-School Gross Enrolment Ratios by Sex Based on Official Statistics, 1994 (%) Table 28: Estimated Weighted Enrolment and Fees, 1994 Table 29: Distribution of Pre-Schools by Annual Fees (Shs) per Child, 1995 Table 30: Distribution of Pre-Schools by Action Taken When Fees is Not Paid in Part or Full Table 31: Percentage Distribution of Enrolment in Pre-Schools by Ability to Pay Fees, 1994 Table 32: Distribution of Pre-School Employees by Gender, Occupation and Monthly Salary, 1995 Table 33(a): Distribution of Teachers by Monthly Salary (Shs), 1995 Table 33(b): Percentage Distribution of Teachers by Monthly Salary, 1995 Table 34: Distribution of Pre-School Teachers by Academic Attainment and ECCD Training, 1995 Table 35: Distribution of Pre-School Teachers by Academic Attainment and Gender, 1995 Table 36: Distribution of Pre-School Teachers by ECCD Training and Gender, 1995 Table 37: Distribution of Pre-School Teachers by ECCD Training and Year of Completion, 1995 Table 38: Distribution of Pre-School Teachers by Training Status, 1995 Table 39: Distribution of Trained Teachers by Training Programme, 1995 Table 40: Distribution of Weighted Number of Teachers by Training Status, 1995 Table 41: Mean Years of Teaching Experience for Pre-School Teachers, 1995 Table 42: Pre-School Pupil-Teacher Ratios, 1995 Table 43: Pre-Schools’ Pupil-Teacher Ratios by Sponsor, 1995 Table 44: Distribution of Pre-Schools by Receipt of Grants/Aid, 1994 Table 45: Grants/Aid Received per Pre-School by Source (Shs), 1994 Table 46(a): Annual Operating Costs per Pre-School by Main Source of Funding (Shs), 1994 Table 46(b): Percentage Distribution of Annual Operating Costs per Pre-School by Main Source of Funding, 1994 Table 47(a): Distribution of Operating Costs (Shs) Per Pre-School by Main Expenditure Item, 1994 Table 47(b): Percentage Distribution of Operating Costs per Pre-School by Main Expenditure Item, 1994 Table 48(a): Distribution of Operating Costs (Shs) Per Child by Main Expenditure Item, 1994 Table 48(b): Percentage Distribution of Operating Costs per Child by Main Expenditure Item, 1994 Table 49: Current Market Value (Shs) per Pre-School by Source of Funding, 1995 Table 50: Current Market Value (Shs) per Attached Pre-School by Source of Funding, 1995
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Table 51: Current Market Value (Shs) per Unattached Pre-School by Source of Funding, 1995 Table 52: Current Market Value (Shs) per Pre-School, Excluding Land, by Source of Funding, 1995 Table 53: Current Market Value (Shs) per Unattached Pre-School, Excluding Land, by Source of Funding, 1995 Table 54: Distribution of Pre-Schools by Whether has Bank Account and Main Sponsor, 1995 Table 55: Distribution of Pre-Schools by School-Feeding Arrangements, 1995 Table 56: Distribution of Pre-Schools by Feeding Times per Day, 1995 Table 57: Distribution of Pre-Schools by Whether Prepare Food, 1995 Table 58: Distribution of Pre-Schools Which Prepare Food by Type of Cooking Fuel, 1995 Table 59: Distribution of Pre-Schools by Receipt of Milk under School Milk Programme, 1995 Table 60: Distribution of Pre-Schools by Request for Immunization Records and Main Sponsor, 1995 Table 61: Distribution of Pre-Schools by Action Taken on Children who are not Fully Immunized, 1995 Table 62(a): Distribution of Pre-Schools by Type of Health Interventions Undertaken, 1990-1995 Table 62(b): Percentage Distribution of Pre-Schools by Type of Health Interventions Undertaken, 1990-1995 Table 63: Distribution of Pre-Schools by Distance to Nearest Health Facility in Kilometres, 1995 Table 64: Distribution of Disabilities by Gender of the Disabled, 1995 Table 65: Distribution of Pre-Schools by Type of Premises, 1995 Table 66: Distribution of Pre-Schools by Type of Roofing Material, 1995 Table 67: Distribution of Pre-Schools by Type of Wall, 1995 Table 68: Distribution of Pre-Schools by Type of Floor, 1995 Table 69: Distribution of Pre-Schools by Type of Wall and Roof, 1995 Table 70: Distribution of Pre-Schools by Type of Structure, 1995 Table 71: Distribution of Pre-Schools by Source of Water, 1995 Table 72: Distribution of Pre-Schools by Type of Toilet, 1995 Table 73: Distribution of Pre-Schools by Number of Children per Toilet Stall, 1995 Table 74: Distribution of Pre-Schools by Source of Classroom Lighting, 1995
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Table 1: Statistics on Pre-schools in Kenya: 1994 Enrolment Teachers Pre-schools Boys Girls Total Trained Untrained Total CENTRAL 71,363 67,919 139,282 1,860 2,253 4,113 2,437Kiambu 18,033 16,995 35,028 577 560 1,137 596Murang’a 17,326 16,357 33,683 619 385 1,004 658Nyeri 14,589 13,850 28,439 296 536 832 454Kirinyaga 7,426 7,104 14,530 158 232 390 220Nyandarua 12,635 12,250 24,885 127 497 624 459Thika Municipal 1,354 1,363 2,717 83 43 126 50COAST 41,487 35,791 77,278 921 1,200 2,121 1,285Kilifi 12,990 8,576 21,566 232 354 586 425Kwale 7,906 6,905 14,811 134 156 290 261Lamu 1,055 898 1,953 54 26 80 55Mombasa 12,430 12,876 25,306 314 491 805 233Taita Taveta 5,383 4,956 10,339 149 121 270 235Tana River 1,723 1,580 3,303 38 52 90 76EASTERN 88,111 85,421 173,532 1,830 3,038 4,868 4,264Embu 7,638 7,651 15,289 229 189 418 343Isiolo 2,997 2,744 5,741 55 117 172 110Kitui/Mwingi 16,520 16,620 33,140 180 687 867 759Machakos 18,305 17,432 35,737 619 525 1,144 946Meru/Nyambene 16,709 16,593 33,302 159 609 768 633Marsabit 2,408 1,757 4,165 19 83 102 174Makueni 17,514 16,715 34,229 526 527 1,053 912Tharaka-Nithi 6,020 5,909 11,929 43 301 344 387NORTH EASTERN 4,726 3,008 7,734 106 86 192 138Garissa 2,113 1,381 3,494 70 6 76 64Mandera 822 685 1,507 27 17 44 24Wajir 1,791 942 2,733 9 63 72 50NYANZA 75,858 75,531 151,389 1,414 2,285 3,699 2,963Kisii 18,240 18,392 36,632 213 510 723 653Kisumu 10,130 10,885 21,015 362 230 592 497Siaya 8,245 8,032 16,277 123 349 472 376Nyamira 10,879 10,775 21,654 130 265 395 387Homa Bay 13,391 12,610 26,001 228 409 637 500Migori/Kuria 9,810 10,362 20,172 114 358 472 403Kisumu Municipal 5,163 4,475 9,638 244 164 408 147RIFT VALLEY 131,595 124,802 256,397 2,433 4,984 7,417 5,057Baringo 7,756 7,507 15,263 276 238 514 519Trans Nzoia 11,059 10,853 21,912 191 296 487 343Uasin Gishu 7,875 7,646 15,521 203 196 399 317Nandi 10,633 10,364 20,997 127 424 551 459Keiyo Marakwet 6,852 6,848 13,700 231 167 398 137West Pokot 4,400 4,225 8,625 74 160 234 178Kajiado 7,729 6,163 13,892 167 312 479 358Narok 8,219 7,236 15,455 127 365 492 340Laikipia 6,539 6,021 12,560 72 320 392 282Samburu 4,200 3,209 7,409 94 95 189 164Turkana 7,043 5,868 12,911 38 144 182 174Nakuru 18,898 18,109 37,007 306 792 1,098 652Kericho 10,222 9,850 20,072 135 445 580 423Bomet 10,508 10,731 21,239 123 494 617 439Nakuru Municipal 4,791 4,756 9,547 127 243 370 96Kitale Municipal 2,581 2,968 5,549 98 87 185 65Eldoret Municipal 2,290 2,448 4,738 44 206 250 111WESTERN 55,025 55,425 110,450 813 2,257 3,070 2,172Kakamega 21,120 21,314 42,434 359 855 1,214 787Bungoma 13,638 13,795 27,433 158 497 655 442Busia 8,960 8,805 17,765 114 275 389 309Vihiga 9,767 10,033 19,800 175 571 746 410Mt. Elgon 1,540 1,478 3,018 7 59 66 224Nairobi 17,187 18,748 35,935 1,174 1,175 2,349 767GRAND TOTAL 485,352 466,645 951,997 10,551 17,278 27,829 19,083
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Table 2: Statistics on Pre-schools in Kenya: 1993 Enrolment Teachers Pre-schools Boys Girls Total Trained Untrained Total CENTRAL 70,294 67,279 137,573 1,806 2,313 4,119 2,411Kiambu 16,947 16,606 33,553 544 596 1,140 608Murang’a 16,228 15,096 31,324 567 415 982 637Nyeri 15,762 14,992 30,754 349 495 844 454Kirinyaga 7,448 7,220 14,668 167 239 406 206Nyandarua 12,416 11,876 24,292 107 511 618 458Thika Municipal 1,493 1,489 2,982 72 57 129 48COAST 38,683 33,551 72,234 817 1,225 2,042 1,214Kilifi 12,990 8,576 21,566 189 289 478 432Kwale 5,734 5,031 10,765 93 229 322 209Lamu 947 828 1,775 55 9 64 49Mombasa 12,405 12,851 25,256 300 461 761 215Taita Taveta 5,185 4,937 10,122 146 194 340 240Tana River 1,422 1,328 2,750 34 43 77 69EASTERN 81,574 78,116 159,690 1,743 2,833 4,576 3,947Embu 7,143 7,158 14,301 204 148 352 317Isiolo 2,172 2,005 4,177 45 55 100 92Kitui/Mwingi 14,811 14,522 29,333 191 570 761 753Machakos 18,154 17,583 35,737 576 561 1,137 904Meru/Nyambene 13,043 12,228 25,271 134 653 787 622Marsabit 3,078 2,202 5,280 16 85 101 74Makueni 16,880 15,944 32,824 499 515 1,014 871Tharaka-Nithi 6,293 6,474 12,767 78 246 324 314NORTH EASTERN 2,394 1,625 4,019 56 55 111 96Garissa 1,186 737 1,923 24 12 36 52Mandera 783 593 1,376 20 24 44 22Wajir 425 295 720 12 19 31 22NYANZA 65,206 64,956 130,162 1,187 2,233 3,420 2,833Kisii 16,006 15,772 31,778 174 525 699 610Kisumu 11,305 11,865 23,170 331 248 579 547Siaya 8,243 8,409 16,652 122 352 474 380Nyamira 10,138 9,939 20,077 125 260 385 363Homa Bay 10,041 10,877 20,918 166 387 553 468Migori 4,997 4,040 9,037 78 280 358 344Kisumu Municipal 4,476 4,054 8,530 191 181 372 121RIFT VALLEY 135,236 123,424 258,660 2,772 4,261 7,033 5,138Baringo 7,516 7,490 15,006 438 53 491 449Trans Nzoia 11,059 10,853 21,912 191 296 487 343Uasin Gishu 8,968 7,656 16,624 191 207 398 337Nandi 10,137 10,201 20,338 130 406 536 584Keiyo Marakwet 7,641 7,023 14,664 180 160 340 326West Pokot 4,280 4,094 8,374 71 189 260 178Kajiado 7,261 5,793 13,054 174 303 477 314Narok 8,219 7,236 15,455 127 365 492 340Laikipia 6,539 6,021 12,560 72 320 392 282Samburu 3,246 2,903 6,149 94 80 174 158Turkana 11,717 7,441 19,158 38 147 185 170Nakuru 19,575 18,458 38,033 255 778 1,033 630Kericho 9,065 8,931 17,996 375 125 500 386Bomet 11,341 11,033 22,374 76 522 598 411Nakuru Municipal 4,296 4,311 8,607 117 228 345 85Kitale Municipal 1,100 1,075 2,175 49 49 98 52Eldoret Municipal 3,276 2,905 6,181 194 33 227 93WESTERN 55,646 60,613 116,259 752 2,339 3,091 2,144Kakamega 19,527 19,817 39,344 335 824 1,159 771Bungoma 12,649 16,708 29,357 142 530 672 643Busia 9,013 8,567 17,580 111 271 382 309Vihiga 11,019 12,007 23,026 142 598 740 421Mt. Elgon 3,438 3,514 6,952 22 116 138 Nairobi 22,991 22,506 45,497 1,302 931 2,233 704GRAND TOTAL 472,024 452,070 924,094 10,435 16,190 26,625 18,487
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Table 3: Statistics on Pre-schools in Kenya: 1992 Enrolment Teachers Pre-schools Boys Girls Total Trained Untrained Total CENTRAL 55,715 53,838 146,865 1,637 2,280 3,917 2,385Kiambu 18,407 18,404 36,811 479 485 964 602Murang’a 17,330 16,510 33,840 564 372 936 626Nyeri 37,312 239 685 924 513Kirinyaga 8,276 7,872 16,148 162 222 384 201Nyandarua 10,474 9,771 20,245 139 466 605 401Thika Municipal 1,228 1,281 2,509 54 50 104 42COAST 40,593 37,416 78,009 928 1,185 2,113 1,237Kilifi 12,791 8,376 21,167 165 273 438 422Kwale 8,550 7,397 15,947 211 209 420 287Lamu 894 859 1,753 20 42 62 48Mombasa 11,660 14,030 25,690 320 441 761 216Taita Taveta 5,395 5,474 10,869 178 178 356 205Tana River 1,303 1,280 2,583 34 42 76 59EASTERN 84,440 81,406 165,846 1,682 2,922 4,604 3,863Embu 7,773 7,708 15,481 224 187 411 325Isiolo 1,773 1,646 3,419 38 62 100 80Kitui 16,014 14,127 30,141 117 662 779 741Machakos 16,743 16,550 33,293 545 522 1,067 826Meru 17,261 17,427 34,688 202 599 801 632Marsabit 2,314 1,919 4,233 16 85 101 74Makueni 16,823 16,246 33,069 487 531 1,018 884Tharaka-Nithi 5,739 5,783 11,522 53 274 327 301NORTH EASTERN 2,836 2,122 4,958 89 35 124 93Garissa 1,714 1,406 3,120 59 4 63 54Mandera 688 458 1,146 21 12 33 19Wajir 434 258 692 9 19 28 20NYANZA 60,127 60,625 127,645 991 2,209 3,200 2,760Kisii 17,213 17,681 34,894 174 525 699 610Kisumu 10,934 11,382 22,316 215 347 562 532Siaya 7,714 7,858 15,572 121 337 458 363Nyamira 9,181 9,166 18,347 75 274 349 349Homa Bay 10,088 10,498 20,586 157 343 500 458Migori 4,997 4,040 9,037 78 280 358 344Kisumu Municipal 6,893 171 103 274 104RIFT VALLEY 108,018 100,259 253,027 2,231 4,466 6,697 4,967Baringo 7,715 7,390 15,105 263 180 443 449Trans Nzoia 9,990 10,125 20,115 143 432 575 404Uasin Gishu 9,642 9,264 18,906 157 272 429 370Nandi 10,327 10,091 20,418 116 391 507 449Keiyo Marakwet 7,641 7,023 14,664 180 160 340 326West Pokot 3,955 3,411 7,366 58 159 217 159Kajiado 5,100 4,900 10,000 140 230 370 290Narok 8,564 7,291 15,855 119 353 472 334Laikipia 5,231 6,342 11,573 54 328 382 288Samburu 3,064 2,431 5,495 83 114 197 149Turkana 11,717 7,441 19,158 38 147 185 170Nakuru 17,126 16,707 33,833 213 670 883 563Kericho/Bomet 44,750 390 701 1,091 834Nakuru Municipal 4,178 4,179 8,357 114 220 334 82Kitale Municipal 1,525 1,538 3,063 42 83 125 44Eldoret Municipal 2,243 2,126 4,369 121 26 147 56WESTERN 56,141 56,347 112,488 604 2,201 2,805 1,954Kakamega 20,354 20,519 40,873 284 809 1,093 755Bungoma 17,020 17,361 34,381 156 555 711 502Busia 8,248 8,097 16,345 114 220 334 280Vihiga 10,519 10,370 20,889 50 617 667 417Nairobi 21,986 21,001 42,987 1,073 828 1,901 650GRAND TOTAL 429,856 413,014 931,825 9,235 16,126 25,361 17,909
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Table 4: Statistics on Pre-schools in Kenya: 1991 Enrolment Teachers Pre-schools Boys Girls Total Trained Untrained Total CENTRAL 52,593 52,086 141,991 1,549 2,237 3,786 2,299Kiambu 17,407 17,949 35,356 458 463 921 574Murang’a 17,051 16,177 33,228 580 371 951 619Nyeri 37,312 239 685 924 513Kirinyaga 8,276 7,872 16,148 133 252 385 195Nyandarua 9,859 10,088 19,947 139 466 605 398Thika Municipal 1,228 1,281 2,509 54 50 104 42COAST 39,378 36,679 76,057 826 1,215 2,041 1,222Kilifi 12,791 8,376 21,167 165 273 438 422Kwale 7,473 6,654 14,127 140 227 367 273Lamu 903 875 1,778 20 42 62 48Mombasa 11,660 14,030 25,690 320 441 761 216Taita Taveta 5,297 5,432 10,729 148 192 340 205Tana River 1,254 1,312 2,566 33 40 73 58EASTERN 83,721 78,103 161,824 1,573 2,961 4,534 3,784Embu 7,323 7,277 14,600 224 187 411 325Isiolo 1,773 1,646 3,419 38 62 100 80Kitui 16,014 14,127 30,141 117 661 778 747Machakos 32,739 30,858 63,597 950 1,083 2,033 1,639Meru 23,636 22,562 46,198 232 880 1,112 924Marsabit 2,236 1,633 3,869 12 88 100 69NORTH EASTERN 2,691 2,112 4,803 88 17 105 82Garissa 1,714 1,406 3,120 59 4 63 54Mandera 625 439 1,064 23 4 27 17Wajir 352 267 619 6 9 15 11NYANZA 58,025 58,332 123,250 895 2,161 3,056 2,731Kisii 15,973 15,955 31,928 168 482 650 650Kisumu 10,461 10,983 21,444 195 339 534 523Siaya 7,600 7,747 15,347 111 322 433 363Nyamira 9,086 9,174 18,260 75 274 349 349South Nyanza 14,905 14,473 29,378 175 641 816 742Kisumu Municipal 6,893 171 103 274 104RIFT VALLEY 127,898 121,276 249,174 1,968 4,658 6,626 5,024Baringo 7,302 7,021 14,323 225 241 466 412Trans Nzoia 9,990 10,125 20,115 143 434 577 357Uasin Gishu 9,118 8,988 18,106 96 285 381 328Nandi 10,327 10,091 20,418 116 388 504 436Keiyo Marakwet 7,229 7,000 14,229 140 190 330 323West Pokot 3,955 3,411 7,366 58 159 217 159Kajiado 5,100 4,900 10,000 140 230 370 290Narok 7,988 6,897 14,885 90 336 426 523Laikipia 5,231 6,342 11,573 54 328 382 288Samburu 2,686 2,289 4,975 44 137 181 154Turkana 10,310 7,100 17,410 26 146 172 166Nakuru 18,132 17,631 35,763 209 737 946 580Kericho 22,832 21,898 44,730 356 735 1,091 834Nakuru Municipal 3,930 3,919 7,849 108 203 311 74Kitale Municipal 1,525 1,538 3,063 42 83 125 44Eldoret Municipal 2,243 2,126 4,369 121 26 147 56WESTERN 55,321 56,487 111,808 667 2,147 2,814 1,816Kakamega 29,906 30,846 60,752 420 1,356 1,776 1,050Bungoma 17,167 17,544 34,711 133 571 704 502Busia 8,248 8,097 16,345 114 220 334 264Nairobi 18,269 17,207 35,476 975 768 1,743 650GRAND TOTAL 437,896 422,282 904,383 8,541 16,164 24,705 17,608
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Table 5: Statistics on Pre-schools in Kenya: 1990 Enrolment Teachers Pre-schools Boys Girls Total Trained Untrained Total CENTRAL 68,531 68,553 137,084 1,217 2,335 3,552 2,364Kiambu 16,169 17,127 33,296 404 549 953 650Murang’a 16,254 15,635 31,889 451 408 859 619Nyeri 15,808 15,860 31,668 125 623 748 445Kirinyaga 9,305 8,699 18,004 112 254 366 231Nyandarua 9,859 10,088 19,947 65 466 531 383Thika Municipal 1,136 1,144 2,280 60 35 95 36COAST 34,081 30,958 67,039 577 1,238 1,815 1,118Kilifi 10,133 9,566 19,699 82 375 457 409Kwale 7,473 6,754 14,227 66 244 310 249Lamu 825 857 1,682 21 30 51 38Mombasa 9,804 8,046 17,850 333 352 685 186Taita Taveta 4,649 4,660 11,309 52 193 245 205Tana River 1,197 1,075 2,272 23 44 67 31EASTERN 82,566 79,168 161,734 1,298 2,987 4,285 3,580Embu 7,773 7,708 15,481 148 234 382 304Isiolo 1,561 1,467 3,028 37 58 95 68Kitui 14,757 13,764 28,521 61 647 708 709Machakos 33,054 31,954 65,008 837 1,105 1,942 1,576Meru 23,185 22,642 45,827 203 855 1,058 854Marsabit 2,236 1,633 3,869 12 88 100 69NORTH EASTERN 1,913 951 2,864 46 24 70 60Garissa 1,153 376 1,529 31 5 36 35Mandera 469 308 777 9 10 19 14Wajir 291 267 558 6 9 15 11NYANZA 55,365 54,325 109,690 777 1,934 2,711 2,404Kisii/Nyamira 23,879 24,019 47,898 228 707 935 875Kisumu 8,278 8,590 16,868 161 309 470 455Siaya 5,914 5,831 11,745 126 218 344 292South Nyanza 14,150 13,204 27,354 121 614 735 642Kisumu Municipal 3,144 2,681 5,825 141 86 227 140RIFT VALLEY 122,504 114,024 236,528 1,431 4,163 5,594 4,341Baringo 7,214 6,797 14,011 89 363 452 401Trans Nzoia 10,579 10,883 21,462 107 373 480 327Uasin Gishu 9,118 8,988 18,106 274 97 371 328Nandi 10,755 10,226 20,981 93 355 448 379Keiyo Marakwet 7,229 7,000 14,229 81 249 330 323West Pokot 3,718 2,395 6,113 32 139 171 132Kajiado 3,225 2,669 5,894 45 162 207 153Narok 7,716 6,619 14,335 69 281 350 287Laikipia 5,642 5,352 10,994 42 65 107 300Samburu 2,710 2,417 5,127 35 131 166 132Turkana 9,279 6,752 16,031 30 143 173 155Nakuru 18,416 17,820 36,236 151 744 895 555Kericho 20,400 19,682 40,082 155 807 962 721Nakuru Municipal 2,735 2,760 5,495 65 145 210 48Kitale Municipal 1,525 1,538 3,063 42 83 125 44Eldoret Municipal 2,243 2,126 4,369 121 26 147 56WESTERN 48,874 48,447 97,321 573 2,088 2,661 1,812Kakamega 25,704 26,000 51,704 381 1,301 1,682 1,121Bungoma 16,181 15,784 31,965 106 552 658 496Busia 6,989 6,663 13,652 86 235 321 195Nairobi 17,130 17,406 34,536 294 62 356 650GRAND TOTAL 430,964 413,832 846,796 6,213 14,831 21,044 16,329
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Table 6: Percentage Changes in Statistics on Pre-schools in Kenya, 1994/1993 Enrolment Teachers Pre-schools Boys Girls Total Trained Untrained Total CENTRAL 1.521 0.951 1.242 2.990 (2.594) (0.146) 1.078Kiambu 6.408 2.343 4.396 6.066 (6.040) (0.263) (1.974)Murang’a 6.766 8.353 7.531 9.171 (7.229) 2.240 3.297Nyeri (7.442) (7.617) (7.527) (15.186) 8.283 (1.422) 0.000Kirinyaga (0.295) (1.607) (0.941) (5.389) (2.929) (3.941) 6.796Nyandarua 1.764 3.149 2.441 18.692 (2.740) 0.971 0.218Thika Municipal (9.310) (8.462) (8.887) 15.278 (24.561) (2.326) 4.167COAST 7.249 6.676 6.983 12.729 (2.041) 3.869 5.848Kilifi 0.000 0.000 0.000 22.751 22.491 22.594 (1.620)Kwale 37.879 37.249 37.585 44.086 (31.878) (9.938) 24.880Lamu 11.404 8.454 10.028 (1.818) 188.889 25.000 12.245Mombasa 0.202 0.195 0.198 4.667 6.508 5.782 8.372Taita Taveta 3.819 0.385 2.144 2.055 (37.629) (20.588) (2.083)Tana River 21.167 18.976 20.109 11.765 20.930 16.883 10.145EASTERN 8.014 9.351 8.668 4.991 7.236 6.381 8.031Embu 6.930 6.887 6.909 12.255 27.703 18.750 8.202Isiolo 37.983 36.858 37.443 22.222 112.727 72.000 19.565Kitui/Mwingi 11.539 14.447 12.979 (5.759) 20.526 13.929 0.797Machakos 0.832 (0.859) 0.000 7.465 (6.417) 0.616 4.646Meru/Nyambene 28.107 35.697 31.780 18.657 (6.738) (2.414) 1.768Marsabit (21.767) (20.209) (21.117) 18.750 (2.353) 0.990 135.135Makueni 3.756 4.836 4.280 5.411 2.330 3.846 4.707Tharaka-Nithi (4.338) (8.727) (6.564) (44.872) 22.358 6.173 23.248NORTH EASTERN 97.410 85.108 92.436 89.286 56.364 72.973 43.750Garissa 78.162 87.381 81.695 191.667 (50.000) 111.111 23.077Mandera 4.981 15.514 9.520 35.000 (29.167) 0.000 9.091Wajir 321.412 219.322 279.583 (25.000) 231.579 132.258 127.273NYANZA 16.336 16.280 16.308 19.124 2.329 8.158 4.589Kisii 13.957 16.612 15.275 22.414 (2.857) 3.433 7.049Kisumu (10.394) (8.260) (9.301) 9.366 (7.258) 2.245 (9.141)Siaya 0.024 (4.483) (2.252) 0.820 (0.852) (0.422) (1.053)Nyamira 7.309 8.411 7.855 4.000 1.923 2.597 6.612Homa Bay 33.363 15.933 24.300 37.349 5.685 15.190 6.838Migori/Kuria 96.318 156.485 123.216 46.154 27.857 31.844 17.151Kisumu Municipal 15.349 10.385 12.989 27.749 (9.392) 9.677 21.488RIFT VALLEY (2.692) 1.116 (0.875) (12.229) 16.968 5.460 (1.576)Baringo 3.193 0.227 1.713 (36.986) 349.057 4.684 15.590Trans Nzoia 0.000 0.000 0.000 0.000 0.000 0.000 0.000Uasin Gishu (12.188) (0.131) (6.635) 6.283 (5.314) 0.251 (5.935)Nandi 4.893 1.598 3.240 (2.308) 4.433 2.799 (21.404)Keiyo Marakwet (10.326) (2.492) (6.574) 28.333 4.375 17.059 (57.975)West Pokot 2.804 3.200 2.997 4.225 (15.344) (10.000) 0.000Kajiado 6.445 6.387 6.419 (4.023) 2.970 0.419 14.013Narok 0.000 0.000 0.000 0.000 0.000 0.000 0.000Laikipia 0.000 0.000 0.000 0.000 0.000 0.000 0.000Samburu 29.390 10.541 20.491 0.000 18.750 8.621 3.797Turkana (39.891) (21.140) (32.608) 0.000 (2.041) (1.622) 2.353Nakuru (3.458) (1.891) (2.698) 20.000 1.799 6.292 3.492Kericho 12.763 10.290 11.536 (64.000) 256.000 16.000 9.585Bomet (7.345) (2.737) (5.073) 61.842 (5.364) 3.177 6.813Nakuru Municipal 11.522 10.322 10.921 8.547 6.579 7.246 12.941Kitale Municipal 134.636 176.093 155.126 100.000 77.551 88.776 25.000Eldoret Municipal (30.098) (15.731) (23.346) (77.320) 524.242 10.132 19.355WESTERN (1.116) (8.559) (4.997) 8.112 (3.506) (0.679) 1.306Kakamega 8.158 7.554 7.854 7.164 3.762 4.745 2.075Bungoma 7.819 (17.435) (6.554) 11.268 (6.226) (2.530) (31.260)Busia (0.588) 2.778 1.052 2.703 1.476 1.832 0.000Vihiga (11.362) (16.440) (14.010) 23.239 (4.515) 0.811 (2.613)Mt. Elgon (55.207) (57.940) (56.588) (68.182) (49.138) (52.174) Nairobi (25.245) (16.698) (21.017) (9.831) 26.208 5.195 8.949GRAND TOTAL 2.824 3.224 3.019 1.112 6.720 4.522 3.224
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Table 7: Number of Sampled ECCD Centres District/ Municipality No. Parent Local Authority Religious Organization Private Other TotalNairobi N 151 93 178 255 - 677 n 23 14 27 38 - 101Mombasa N 54 12 104 54 27 251 n 8 2 16 8 4 38Kilifi N 259 82 10 15 - 366 n 39 12 1 2 - 55Garissa N 47 1 4 3 8 63 n 7 - 1 - 1 9Machakos N 781 64 11 48 12 916 n 117 10 2 7 2 137Nakuru District N 462 70 84 53 - 669 n 69 10 13 8 - 100Nakuru Municipality N 9 10 46 48 - 113 n 1 2 7 7 - 17Uasin Gishu N 307 5 6 3 3 324 n 46 1 1 1 - 49Eldoret N 14 5 38 51 11 119 n 2 1 6 8 2 18Narok N 97 118 17 3 - 235 n 15 18 3 - - 35Kitale N 12 9 6 19 2 48 n 2 1 1 3 - 7Kericho N 333 1 3 27 - 364 n 50 - 1 4 - 55Kisumu district N 315 108 20 12 - 455 n 47 16 3 2 - 68Kisumu Municipality N 48 6 35 50 12 151 n 7 1 5 7 2 23Kakamega N 485 88 110 20 - 703 n 73 13 16 3 - 105Thika Municipality N 14 9 14 13 - 50 n 2 1 2 2 - 7Nyandarua N 426 12 42 20 5 505 n 64 2 6 3 1 76Total N 3,814 693 728 694 80 6,009 n 571 104 109 104 12 900 * = Totals differ because of rounding.
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Table 8: Comparison between Reported 1994 and 1995 ECCD Centres DISTRICT/MUNICIPALITY 1994 1995 DIFFERENCE URBAN Nairobi 767 677 -90Mombasa 233 251 +18Kisumu Municipality 147 151 +4Nakuru Municipality 96 113 +17Eldoret Municipality 111 119 +8Kitale Municipality 65 48 -17Thika Municipality 50 50 0RURAL Kilifi 425 366 -59Machakos 946 916 -30Nyandarua 459 505 +46Narok 340 235 -105Nakuru 652 669 +17Kericho 423 364 -59Uasin Gishu 317 324 +7Kisumu 497 455 -42Kakamega 787 703 -84Garissa 64 63 -1TOTAL 6,379 6,009 -370 Table 9: Population in Urban Areas as Reported in the 1989 Census DISTRICT URBAN CENTRE POPULATION Kilifi district Kilifi 14,145 Malindi 34,047 Mariakani 8,372 Mambrui and Watamu 5,040Machakos district Machakos 116,293 Athi River 13,072 Tala 10,880 Matuu, Mtito Andei and Kibwezi 9,135Nyandarua district Nyahururu 14,829 Ol Kalou 2,546Garissa district Garissa 31,319 Liboi 2,380Nakuru district Naivasha 34,519 Gilgil 14,304 Molo 11,175 Elburgon 12,072 Njoro 9,026Narok district Narok 11,629 Kilgoris 5,059Kericho district Kericho 48,511 Sotik, Londiani and Kipkelion 10,032Uasin Gishu district Lemook, Turbo, Moi’s Bridge, Simat, and Burnt Forest 17,146Kakamega district Kakamega 58,862 Mumias 23,668 Luanda, Majengo, Mbale and Butere 12,936
73
Table 10: Population Projections for Age 3-5 Years by District/Municipality, 1990-1995 1979 1989 r 1990 1991 1992 1993 1994 1995 Nairobi 67,694 96,726 3.63 100,240 103,882 107,657 111,568 115,622 119,823 Male 33,690 48,559 3.72 50,367 52,242 54,188 56,205 58,298 60,469 Female 34,004 48,167 3.54 49,874 51,641 53,471 55,365 57,327 59,358Mombasa 29,428 36,729 2.24 37,552 38,394 39,254 40,134 41,033 41,953 Male 14,775 18,404 2.22 18,813 19,230 18,404 18,813 19,230 19,657 Female 14,653 18,325 2.26 18,739 19,163 18,325 18,739 19,163 19,597Kilifi 49,558 70,675 3.61 73,229 75,875 78,616 81,457 84,400 87,449 Male 24,381 35,225 3.75 36,545 37,915 39,336 40,810 42,340 43,927 Female 25,177 35,450 3.48 36,684 37,961 39,283 40,650 42,065 43,529Nyandarua 28,315 39,465 3.38 40,797 42,175 43,598 45,070 46,592 48,165 Male 14,242 20,047 3.48 20,744 21,466 22,212 22,985 23,784 24,611 Female 14,073 19,418 3.27 20,053 20,709 21,387 22,087 22,809 23,556Nakuru Rural 50,634 78,658 4.50 82,200 85,902 89,770 93,813 98,038 102,453 Male 25,550 40,047 4.60 41,888 43,813 45,827 47,934 50,137 52,442 Female 25,084 38,611 4.41 40,313 42,090 43,945 45,882 47,904 50,015Nakuru Municipal 8,757 15,129 5.62 15,979 16,877 17,826 18,827 19,886 21,003 Male 4,419 7,703 5.71 8,143 8,609 9,101 9,621 10,170 10,752 Female 4,338 7,426 5.52 7,836 8,269 8,725 9,207 9,716 10,252Eldoret 4,367 10,647 9.32 11,639 12,724 13,910 15,207 16,624 18,173 Male 2,188 5,325 9.30 5,820 6,362 6,954 7,601 8,308 9,081 Female 2,180 5,322 9.34 5,819 6,362 6,956 7,606 8,316 9,093Uasin Gishu Rural 29,435 38,417 2.70 39,454 40,519 41,612 42,736 43,889 45,074 Male 14,745 19,433 2.80 19,977 20,536 21,111 21,702 22,309 22,934 Female 14,689 18,984 2.60 19,477 19,983 20,502 21,035 21,581 22,142Kitale 2,768 5,398 6.91 5,771 6,169 6,595 7,051 7,538 8,059 Male 1,383 2,754 7.13 2,950 3,161 3,386 3,628 3,886 4,163 Female 1,385 2,644 6.68 2,821 3,009 3,210 3,424 3,653 3,897Kisumu Rural 34,386 49,868 3.79 51,757 53,717 55,751 57,863 60,054 62,328 Male 17,089 25,133 3.93 26,121 27,149 28,216 29,326 30,480 31,678 Female 17,297 24,735 3.64 25,636 26,569 27,537 28,540 29,579 30,656Kisumu Municipal 14,735 18,081 2.07 18,455 18,836 19,226 19,623 20,029 20,443 Male 7,323 8,984 2.07 9,170 9,359 9,552 9,750 9,951 10,156 Female 7,412 9,097 2.07 9,285 9,477 9,674 9,874 10,078 10,287Thika 3,036 4,563 4.16 4,753 4,951 5,156 5,371 5,594 5,827 Male 1,528 2,253 3.96 2,342 2,435 2,531 2,631 2,735 2,844 Female 1,507 2,310 4.36 2,411 2,516 2,626 2,740 2,860 2,984Machakos 64,446 86,365 2.97 88,930 91,572 94,293 97,094 99,978 102,948 Male 32,316 43,696 3.06 45,034 46,413 47,835 49,300 50,810 52,366 Female 32,131 42,669 2.88 43,897 45,160 46,459 47,796 49,171 50,586Kericho 36,111 49,792 3.26 51,417 53,096 54,830 56,620 58,468 60,377 Male 18,212 25,192 3.30 26,023 26,881 27,767 28,683 29,629 30,606 Female 17,899 24,600 3.23 25,395 26,215 27,062 27,937 28,839 29,771Garissa Central Division 2,426 4,088 5.36 4,307 4,537 4,780 5,037 5,306 5,591 Male 1,239 2,103 5.43 2,217 2,337 2,464 2,598 2,739 2,888 Female 1,187 1,985 5.28 2,090 2,200 2,316 2,439 2,567 2,703Kakamega 78,246 113,302 3.77 117,576 122,010 126,611 131,386 136,341 141,483 Male 39,174 56,598 3.75 58,720 60,921 63,204 65,573 68,031 70,581 Female 39,073 56,704 3.79 58,856 61,089 63,407 65,813 68,310 70,902Narok 16,779 32,969 6.99 35,272 37,737 40,374 43,195 46,213 49,442 Male 8,313 16,649 7.19 17,846 19,130 20,505 21,980 23,561 25,255 Female 8,466 16,320 6.78 17,427 18,609 19,871 21,219 22,659 24,196
74
Table 11: Response Status of the Sample Survey of ECCD Centres Number % Completed Closed Not
Located Other
NonresponseTotal Completed Closed Not
Located Other
NonresponseTotal
MAJOR URBAN
122 11 4 1 138 88.4 8.0 2.9 0.7 100.0
Mombasa 34 3 0 0 37 91.9 8.1 0.0 0.0 100.0Nairobi 88 8 4 1 101 87.1 7.9 4.0 1.0 100.0OTHER URBAN
70 0 2 0 72 97.2 0.0 2.8 0.0 100.0
Thika 7 0 0 0 7 100.0 0.0 0.0 0.0 100.0Nakuru 17 0 0 0 17 100.0 0.0 0.0 0.0 100.0Eldoret 16 0 2 0 18 88.9 0.0 11.1 0.0 100.0Kitale 7 0 0 0 7 100.0 0.0 0.0 0.0 100.0Kisumu 23 0 0 0 23 100.0 0.0 0.0 0.0 100.0RURAL 674 18 2 2 696 96.8 2.6 0.3 0.3 100.0Kilifi 50 4 0 0 54 92.6 7.4 0.0 0.0 100.0Nyandarua 75 0 0 0 75 100.0 0.0 0.0 0.0 100.0Machakos 138 2 0 0 140 98.6 1.4 0.0 0.0 100.0Uasin Gishu
45 3 0 0 48 93.8 6.3 0.0 0.0 100.0
Nakuru 95 2 1 2 100 95.0 2.0 1.0 2.0 100.0Kericho 54 1 0 0 55 98.2 1.8 0.0 0.0 100.0Narok 37 0 0 0 37 100.0 0.0 0.0 0.0 100.0Kakamega 104 0 1 0 105 99.0 0.0 1.0 0.0 100.0Kisumu 62 5 0 0 67 92.5 7.5 0.0 0.0 100.0Garissa 14 1 0 0 15 93.3 6.7 0.0 0.0 100.0TOTAL 866 29 8 3 906 95.6 3.2 0.9 0.3 100.0
75
Table 12: Distribution of Pre-Schools by Year Established and Sponsor Community Religious
organizationPrivate
individual/ company
Plantations, estates and
other companies
Local Authority
NGO Total Total (%)
MAJOR URBAN
23 44 34 3 17 1 122 100.0
Not Stated
2 2 0 0 0 0 4 3.3
Before 1980
5 10 5 3 8 0 31 25.4
1980-1984
2 8 4 0 4 0 18 14.8
1985-1989
6 11 4 0 5 1 27 22.1
1990-May 1995
8 13 21 0 0 0 42 34.4
OTHER URBAN
22 20 18 3 7 0 70 100.0
Not Stated
0 2 0 0 0 0 2 2.9
Before 1980
5 3 2 2 4 0 16 22.9
1980-1984
2 2 2 0 0 0 6 8.6
1985-1989
4 1 1 1 1 0 8 11.4
1990-May 1995
11 12 13 0 2 0 38 54.3
RURAL 523 42 23 10 74 2 674 100.0Not Stated
8 0 0 0 1 0 9 1.3
Before 1980
242 10 3 2 39 0 296 43.9
1980-1984
103 4 1 3 11 0 122 18.1
1985-1989
98 13 7 2 14 0 134 19.9
1990-May 1995
72 15 12 3 9 2 113 16.8
TOTAL 568 106 75 16 98 3 866 100.0Not Stated
10 4 0 0 1 0 15 1.7
Before 1980
252 23 10 7 51 0 343 39.6
1980-1984
107 14 7 3 15 0 146 16.9
1985-1989
108 25 12 3 20 1 169 19.5
1990-May 1995
91 40 46 3 11 2 193 22.3
76
Table 13: Distribution of Pre-Schools by Sponsor Number % Community Religious
organization Private
individual/ company
Plantations, estates, other
companies
LocalAuthority
NGO Total Community Religiousorganization
Private individual/ company
Plantations, estates, other
companies
LocalAuthority
NGO Total
MAJOR URBAN
23 44 34 3 17 1 122 18.9 36.1 27.9 2.5 13.9 0.8 100.0
Mombasa 10 13 7 1 3 0 34 29.4 38.2 20.6 2.9 8.8 0.0 100.0 Nairobi 13 31 27 2 14 1 88 14.8 35.2 30.7 2.3 15.9 1.1 100.0 OTHER URBAN
22 20 18 3 7 0 70 31.4 28.6 25.7 4.3 10.0 0.0 100.0
Thika 2 1 2 1 1 0 7 28.6 14.3 28.6 14.3 14.3 0.0 100.0 Nakuru 3 4 5 2 3 0 17 17.6 23.5 29.4 11.8 17.6 0.0 100.0 Eldoret 6 6 3 0 1 0 16 37.5 37.5 18.8 0.0 6.3 0.0 100.0 Kitale 4 1 1 0 1 0 7 57.1 14.3 14.3 0.0 14.3 0.0 100.0 Kisumu 7 8 7 0 1 0 23 30.4 34.8 30.4 0.0 4.3 0.0 100.0 RURAL 523 42 23 10 74 2 674 77.6 6.2 3.4 1.5 11.0 0.3 100.0 Kilifi 30 6 2 0 12 0 50 60.0 12.0 4.0 0.0 24.0 0.0 100.0 Nyandarua 63 7 1 0 4 0 75 84.0 9.3 1.3 0.0 5.3 0.0 100.0 Machakos 122 3 7 0 6 0 138 88.4 2.2 5.1 0.0 4.3 0.0 100.0 Uasin Gishu
44 0 1 0 0 0 45 97.8 0.0 2.2 0.0 0.0 0.0 100.0
Nakuru 70 9 5 4 7 0 95 73.7 9.5 5.3 4.2 7.4 0.0 100.0 Kericho 48 1 1 3 1 0 54 88.9 1.9 1.9 5.6 1.9 0.0 100.0 Narok 17 3 1 0 16 0 37 45.9 8.1 2.7 0.0 43.2 0.0 100.0 Kakamega 82 7 3 1 11 0 104 78.8 6.7 2.9 1.0 10.6 0.0 100.0 Kisumu 38 6 0 2 16 0 62 61.3 9.7 0.0 3.2 25.8 0.0 100.0 Garissa 9 0 2 0 1 2 14 64.3 0.0 14.3 0.0 7.1 14.3 100.0 TOTAL 568 106 75 16 98 3 866 65.6 12.2 8.7 1.8 11.3 0.3 100.0
77
Table 14: Distribution of Pre-Schools by Ownership and Type of Neighborhood, 1995 Number % Total
(%) Urban Slum
Urban Non-slum
Pastoral Plantations Settled agriculture
Total Urban Slum
Urban Non-slum
Pastoral Plantations Settled agriculture
MAJOR URBAN
Public 24 39 0 0 1 64 37.5 60.9 0.0 0.0 1.6 52.5
Private 15 43 0 0 0 58 25.9 74.1 0.0 0.0 0.0 47.5 Total 39 82 0 0 1 122 32.0 67.2 0.0 0.0 0.8 100.0 Mombasa Public 3 14 0 0 0 17 17.6 82.4 0.0 0.0 0.0 50.0 Private 1 16 0 0 0 17 5.9 94.1 0.0 0.0 0.0 50.0 Total 4 30 0 0 0 34 11.8 88.2 0.0 0.0 0.0 100.0 Nairobi Public 21 25 0 0 1 47 44.7 53.2 0.0 0.0 2.1 53.4 Private 14 27 0 0 0 41 34.1 65.9 0.0 0.0 0.0 46.6 Total 35 52 0 0 1 88 39.8 59.1 0.0 0.0 1.1 100.0 OTHER URBAN
Public 21 14 0 0 2 37 56.8 37.8 0.0 0.0 5.4 52.9
Private 14 18 0 1 0 33 42.4 54.5 0.0 3.0 0.0 47.1 Total 35 32 0 1 2 70 50.0 45.7 0.0 1.4 2.9 100.0 Thika Public 1 1 0 0 0 2 50.0 50.0 0.0 0.0 0.0 28.6 Private 2 2 0 1 0 5 40.0 40.0 0.0 20.0 0.0 71.4 Total 3 3 0 1 0 7 42.9 42.9 0.0 14.3 0.0 100.0 Nakuru Public 1 7 0 0 1 9 11.1 77.8 0.0 0.0 11.1 52.9 Private 0 8 0 0 0 8 0.0 100.0 0.0 0.0 0.0 47.1 Total 1 15 0 0 1 17 5.9 88.2 0.0 0.0 5.9 100.0 Eldoret Public 7 1 0 0 1 9 77.8 11.1 0.0 0.0 11.1 56.3 Private 7 0 0 0 0 7 100.0 0.0 0.0 0.0 0.0 43.8 Total 14 1 0 0 1 16 87.5 6.3 0.0 0.0 6.3 100.0 Kitale Public 5 0 0 0 0 5 100.0 0.0 0.0 0.0 0.0 71.4 Private 2 0 0 0 0 2 100.0 0.0 0.0 0.0 0.0 28.6 Total 7 0 0 0 0 7 100.0 0.0 0.0 0.0 0.0 100.0 Kisumu Public 7 5 0 0 0 12 58.3 41.7 0.0 0.0 0.0 52.2 Private 3 8 0 0 0 11 27.3 72.7 0.0 0.0 0.0 47.8 Total 10 13 0 0 0 23 43.5 56.5 0.0 0.0 0.0 100.0 RURAL Public 12 42 19 37 517 627 1.9 6.7 3.0 5.9 82.5 93.0 Private 7 15 0 10 15 47 14.9 31.9 0.0 21.3 31.9 7.0 Total 19 57 19 47 532 674 2.8 8.5 2.8 7.0 78.9 100.0
78
Number % Total(%) Urban
Slum Urban Non-
slum Pastoral Plantations Settled
agriculture Total Urban
Slum Urban Non-
slum Pastoral Plantations Settled
agriculture Kilifi Public 1 12 1 0 33 47 2.1 25.5 2.1 0.0 70.2 94.0 Private 0 1 0 0 2 3 0.0 33.3 0.0 0.0 66.7 6.0 Total 1 13 1 0 35 50 2.0 26.0 2.0 0.0 70.0 100.0 Nyandarua Public 2 1 0 2 65 70 2.9 1.4 0.0 2.9 92.9 93.3 Private 1 0 0 0 4 5 20.0 0.0 0.0 0.0 80.0 6.7 Total 3 1 0 2 69 75 4.0 1.3 0.0 2.7 92.0 100.0 Machakos Public 0 10 1 1 119 131 0.0 7.6 0.8 0.8 90.8 94.9 Private 0 5 0 0 2 7 0.0 71.4 0.0 0.0 28.6 5.1 Total 0 15 1 1 121 138 0.0 10.9 0.7 0.7 87.7 100.0 Uasin Gishu Public 0 0 0 0 43 43 0.0 0.0 0.0 0.0 100.0 95.6 Private 1 0 0 0 1 2 50.0 0.0 0.0 0.0 50.0 4.4 Total 1 0 0 0 44 45 2.2 0.0 0.0 0.0 97.8 100.0 Nakuru Public 2 8 2 2 70 84 2.4 9.5 2.4 2.4 83.3 88.4 Private 2 3 0 3 3 11 18.2 27.3 0.0 27.3 27.3 11.6 Total 4 11 2 5 73 95 4.2 11.6 2.1 5.3 76.8 100.0 Kericho Public 2 1 1 3 42 49 4.1 2.0 2.0 6.1 85.7 90.7 Private 0 1 0 2 2 5 0.0 20.0 0.0 40.0 40.0 9.3 Total 2 2 1 5 44 54 3.7 3.7 1.9 9.3 81.5 100.0 Narok Public 0 2 11 2 20 35 0.0 5.7 31.4 5.7 57.1 94.6 Private 1 1 0 0 0 2 50.0 50.0 0.0 0.0 0.0 5.4 Total 1 3 11 2 20 37 2.7 8.1 29.7 5.4 54.1 100.0 Kakamega Public 3 3 0 18 76 100 3.0 3.0 0.0 18.0 76.0 96.2 Private 0 2 0 2 0 4 0.0 50.0 0.0 50.0 0.0 3.8 Total 3 5 0 20 76 104 2.9 4.8 0.0 19.2 73.1 100.0 Kisumu Public 1 0 0 9 48 58 1.7 0.0 0.0 15.5 82.8 93.5 Private 0 0 0 3 1 4 0.0 0.0 0.0 75.0 25.0 6.5 Total 1 0 0 12 49 62 1.6 0.0 0.0 19.4 79.0 100.0 Garissa Public 1 5 3 0 1 10 10.0 50.0 30.0 0.0 10.0 71.4 Private 2 2 0 0 0 4 50.0 50.0 0.0 0.0 0.0 28.6 Total 3 7 3 0 1 14 21.4 50.0 21.4 0.0 7.1 100.0 TOTAL Public 57 95 19 37 520 728 7.8 13.0 2.6 5.1 71.4 84.1 Private 36 76 0 11 15 138 26.1 55.1 0.0 8.0 10.9 15.9 Total 93 171 19 48 535 866 10.7 19.7 2.2 5.5 61.8 100.0
79
Table 15: Distribution of Pre-Schools by Main Type of Service Offered, 1995 Number % Formal
education Day-Care
Christian religious teaching
Duksi/ madrassa
Integrated duksi/
madrassa
Other Total Formal education
Day-Care
Christianreligious teaching
Duksi/ madrassa
Integrated duksi/
madrassa
Other Total
MAJOR URBAN
113 3 1 1 2 2 122 92.6 2.5 0.8 0.8 1.6 1.6 100.0
Mombasa 31 1 0 0 2 0 34 91.2 2.9 0.0 0.0 5.9 0.0 100.0 Nairobi 82 2 1 1 0 2 88 93.2 2.3 1.1 1.1 0.0 2.3 100.0 OTHER URBAN
70 0 0 0 0 0 70 100.0 0.0 0.0 0.0 0.0 0.0 100.0
Thika 7 0 0 0 0 0 7 100.0 0.0 0.0 0.0 0.0 0.0 100.0 Nakuru 17 0 0 0 0 0 17 100.0 0.0 0.0 0.0 0.0 0.0 100.0 Eldoret 16 0 0 0 0 0 16 100.0 0.0 0.0 0.0 0.0 0.0 100.0 Kitale 7 0 0 0 0 0 7 100.0 0.0 0.0 0.0 0.0 0.0 100.0 Kisumu 23 0 0 0 0 0 23 100.0 0.0 0.0 0.0 0.0 0.0 100.0 RURAL 657 10 0 0 1 6 674 97.5 1.5 0.0 0.0 0.1 0.9 100.0 Kilifi 48 0 0 0 1 1 50 96.0 0.0 0.0 0.0 2.0 2.0 100.0 Nyandarua 75 0 0 0 0 0 75 100.0 0.0 0.0 0.0 0.0 0.0 100.0 Machakos 130 8 0 0 0 0 138 94.2 5.8 0.0 0.0 0.0 0.0 100.0 Uasin Gishu 45 0 0 0 0 0 45 100.0 0.0 0.0 0.0 0.0 0.0 100.0 Nakuru 94 1 0 0 0 0 95 98.9 1.1 0.0 0.0 0.0 0.0 100.0 Kericho 54 0 0 0 0 0 54 100.0 0.0 0.0 0.0 0.0 0.0 100.0 Narok 32 1 0 0 0 4 37 86.5 2.7 0.0 0.0 0.0 10.8 100.0 Kakamega 104 0 0 0 0 0 104 100.0 0.0 0.0 0.0 0.0 0.0 100.0 Kisumu 61 0 0 0 0 1 62 98.4 0.0 0.0 0.0 0.0 1.6 100.0 Garissa 14 0 0 0 0 0 14 100.0 0.0 0.0 0.0 0.0 0.0 100.0 TOTAL 840 13 1 1 3 8 866 97.0 1.5 0.1 0.1 0.3 0.9 100.0 Table 16: Distribution of Pre-Schools by Registration Status and Enrolment Size, 1995 Total Pre-School Enrolment REGISTRATION
STATUS 1-9 10-19 20-29 30-39 40-49 50-69 70-99 100-149 150+ Total Total (%)
MAJOR URBAN Registered 1 7 11 6 12 17 20 20 10 104 85.2 Not Registered 1 2 3 2 3 4 0 2 1 18 14.8 Mombasa Registered 0 2 4 1 3 2 7 5 3 27 79.4 Not Registered 1 1 1 1 1 2 0 0 0 7 20.6
80
Total Pre-School Enrolment REGISTRATION
STATUS 1-9 10-19 20-29 30-39 40-49 50-69 70-99 100-149 150+ Total Total (%)
Nairobi Registered 1 5 7 5 9 15 13 15 7 77 87.5 Not Registered 0 1 2 1 2 2 0 2 1 11 12.5 OTHER URBAN Registered 0 1 5 7 9 15 12 6 5 60 85.7 Not Registered 0 1 1 0 0 4 3 1 0 10 14.3 Thika Registered 0 1 1 0 1 1 3 0 0 7 100.0 Nakuru Registered 0 0 1 1 1 3 4 2 2 14 82.4 Not Registered 0 0 1 0 0 2 0 0 0 3 17.6 Eldoret Registered 0 0 1 4 2 3 1 2 1 14 87.5 Not Registered 0 1 0 0 0 0 0 1 0 2 12.5 Kitale Registered 0 0 2 0 1 1 0 1 1 6 85.7 Not Registered 0 0 0 0 0 0 1 0 0 1 14.3 Kisumu Registered 0 0 0 2 4 7 4 1 1 19 82.6 Not Registered 0 0 0 0 0 2 2 0 0 4 17.4 RURAL Registered 3 26 67 83 73 101 84 35 7 479 71.1 Not Registered 0 13 23 41 23 52 24 11 8 195 28.9 Kilifi Registered 1 0 0 8 6 9 10 5 3 42 84.0 Not Registered 0 0 1 1 0 2 4 0 0 8 16.0 Nyandarua Registered 1 4 12 10 5 11 12 7 1 63 84.0 Not Registered 0 0 4 2 2 3 1 0 0 12 16.0 Machakos Registered 0 11 30 32 20 25 11 2 0 131 94.9 Not Registered 0 1 2 2 0 1 0 1 0 7 5.1 Uasin Gishu Registered 0 2 4 2 2 7 10 2 0 29 64.4 Not Registered 0 1 3 4 4 3 1 0 0 16 35.6 Nakuru Registered 0 3 6 7 4 11 9 4 1 45 47.4 Not Registered 0 3 4 5 5 15 9 5 4 50 52.6 Kericho Registered 0 2 3 6 13 15 8 3 0 50 92.6 Not Registered 0 1 0 1 0 1 1 0 0 4 7.4 Narok Registered 0 1 2 1 0 0 3 0 0 7 18.9 Not Registered 0 5 5 9 3 6 1 1 0 30 81.1 Kakamega Registered 1 1 3 6 10 14 16 10 2 63 60.6 Not Registered 0 2 2 10 6 10 5 3 3 41 39.4 Kisumu Registered 0 1 6 11 12 6 3 2 0 41 66.1 Not Registered 0 0 2 7 2 10 0 0 0 21 33.9 Garissa Registered 0 1 1 0 1 3 2 0 0 8 57.1
81
Total Pre-School Enrolment REGISTRATION
STATUS 1-9 10-19 20-29 30-39 40-49 50-69 70-99 100-149 150+ Total Total (%)
Not Registered 0 0 0 0 1 1 2 1 1 6 42.9 TOTAL Registered 4 34 83 96 94 133 116 61 22 643 74.2 Not Registered 1 16 27 43 26 60 27 14 9 223 25.8 Total 5 50 110 139 120 193 143 75 31 866 100.0 Table 17: Distribution of Pre-Schools by Management of ECCD Centre, 1995 Number % Headteacher-
employee of Centre Committee Primary
Headteacher ReligiousLeader
Other Total Headteacher-employee of Centre
Committee PrimaryHeadteacher
ReligiousLeader
Other Total
MAJOR URBAN
84 9 9 13 7 122 68.9 7.4 7.4 10.7 5.7 100.0
Mombasa 23 3 1 4 3 34 67.6 8.8 2.9 11.8 8.8 100.0 Nairobi 61 6 8 9 4 88 69.3 6.8 9.1 10.2 4.5 100.0 OTHER URBAN
39 10 10 10 1 70 55.7 14.3 14.3 14.3 1.4 100.0
Thika 6 0 1 0 0 7 85.7 0.0 14.3 0.0 0.0 100.0 Nakuru 6 4 3 3 1 17 35.3 23.5 17.6 17.6 5.9 100.0 Eldoret 10 3 0 3 0 16 62.5 18.8 0.0 18.8 0.0 100.0 Kitale 2 0 4 1 0 7 28.6 0.0 57.1 14.3 0.0 100.0 Kisumu 15 3 2 3 0 23 65.2 13.0 8.7 13.0 0.0 100.0 RURAL 204 135 314 12 9 674 30.3 20.0 46.6 1.8 1.3 100.0 Kilifi 28 2 20 0 0 50 56.0 4.0 40.0 0.0 0.0 100.0 Nyandarua 13 34 24 3 1 75 17.3 45.3 32.0 4.0 1.3 100.0 Machakos 34 22 80 2 0 138 24.6 15.9 58.0 1.4 0.0 100.0 Uasin Gishu 15 5 24 1 0 45 33.3 11.1 53.3 2.2 0.0 100.0 Nakuru 22 36 29 4 4 95 23.2 37.9 30.5 4.2 4.2 100.0 Kericho 9 13 31 0 1 54 16.7 24.1 57.4 0.0 1.9 100.0 Narok 18 0 18 0 1 37 48.6 0.0 48.6 0.0 2.7 100.0 Kakamega 24 14 64 1 1 104 23.1 13.5 61.5 1.0 1.0 100.0 Kisumu 33 9 18 1 1 62 53.2 14.5 29.0 1.6 1.6 100.0 Garissa 8 0 6 0 0 14 57.1 0.0 42.9 0.0 0.0 100.0 TOTAL 327 154 333 35 17 866 37.8 17.8 38.5 4.0 2.0 100.0
82
Table 18: Distribution of Pre-Schools by Size of Management Committee, 1995 Have Management Committee Number of Committee Members Have Don’t Have Total % with committee Not Responded 1-4 5-9 10-19 20+ MAJOR URBAN 68 54 122 55.7 0 10 25 30 2 Mombasa 22 12 34 64.7 0 3 9 10 0 Nairobi 46 42 88 52.3 0 7 16 20 2 OTHER URBAN 45 25 70 64.3 0 7 17 18 3 Thika 3 4 7 42.9 0 1 1 1 0 Nakuru 12 5 17 70.6 0 4 5 3 0 Eldoret 11 5 16 68.8 0 1 6 3 1 Kitale 6 1 7 85.7 0 0 4 1 1 Kisumu 13 10 23 56.5 0 1 1 10 1 RURAL 548 125 673 81.4 1 51 228 254 5 Kilifi 36 14 50 72.0 0 3 8 22 0 Nyandarua 69 6 75 92.0 0 2 48 19 0 Machakos 103 35 138 74.6 0 22 41 40 0 Uasin Gishu 43 2 45 95.6 0 5 20 15 1 Nakuru 88 6 94 93.6 1 6 54 28 0 Kericho 49 5 54 90.7 0 4 17 28 0 Narok 32 5 37 86.5 0 2 15 15 0 Kakamega 64 40 104 61.5 0 4 11 41 3 Kisumu 53 9 62 85.5 0 2 12 38 1 Garissa 11 3 14 78.6 0 1 2 8 0
83
Table 19: Composition of Management Committees by Sex, 1995 Mean Number of Committees With: Male Female Total Male: Female
ratio With no males
With males
With no females
With females
MAJOR URBAN
4 63 4 63
Mombasa 4.7 3.4 8.1 1.4 1 21 2 20Nairobi 5.0 4.6 9.5 1.1 3 42 2 43OTHER URBAN
5 40 4 41
Thika 6.3 1.3 7.7 4.8 0 3 1 2Nakuru 3.6 3.1 6.7 1.2 3 9 1 11Eldoret 5.0 4.5 9.5 1.1 1 10 0 11Kitale 6.3 3.3 9.7 1.9 0 6 1 5Kisumu 7.2 6.8 14.1 1.1 1 12 1 12RURAL 20 518 47 491Kilifi 8.0 2.8 10.8 2.9 2 31 4 29Nyandarua 5.3 3.7 9.0 1.4 0 69 2 67Machakos 4.6 3.6 8.2 1.3 12 91 9 94Uasin Gishu 6.4 2.5 8.9 2.6 1 40 5 36Nakuru 4.9 3.7 8.6 1.3 3 85 1 87Kericho 8.0 2.0 10.0 4.0 0 49 9 40Narok 7.6 1.5 9.2 5.1 0 32 10 22Kakamega 8.6 4.1 12.6 2.1 2 57 1 58Kisumu 7.5 3.6 11.1 2.1 0 53 2 51Garissa 8.8 1.6 10.5 5.5 0 11 4 7 Table 20: Distribution of Pre-Schools by Date of Last Meeting of Management Committee Number % Never Met 1995 1994 1993 <1993 Total Never Met 1995 1994 1993 <1993MAJOR URBAN 1 58 9 0 0 68 1.5 85.3 13.2 0.0 0.0Mombasa 1 18 3 0 0 22 4.5 81.8 13.6 0.0 0.0Nairobi 0 40 6 0 0 46 0.0 87.0 13.0 0.0 0.0OTHER URBAN
1 34 10 0 0 45 2.2 75.6 22.2 0.0 0.0
Thika 0 2 1 0 0 3 0.0 66.7 33.3 0.0 0.0Nakuru 1 10 1 0 0 12 8.3 83.3 8.3 0.0 0.0Eldoret 0 6 5 0 0 11 0.0 54.5 45.5 0.0 0.0Kitale 0 4 2 0 0 6 0.0 66.7 33.3 0.0 0.0Kisumu 0 12 1 0 0 13 0.0 92.3 7.7 0.0 0.0RURAL 5 506 33 3 1 548 0.9 92.3 6.0 0.5 0.2Kilifi 0 32 4 0 0 36 0.0 88.9 11.1 0.0 0.0Nyandarua 1 65 3 0 0 69 1.4 94.2 4.3 0.0 0.0Machakos 0 101 2 0 0 103 0.0 98.1 1.9 0.0 0.0Uasin Gishu 0 39 4 0 0 43 0.0 90.7 9.3 0.0 0.0Nakuru 0 75 11 2 0 88 0.0 85.2 12.5 2.3 0.0Kericho 1 46 2 0 0 49 2.0 93.9 4.1 0.0 0.0Narok 0 30 1 0 1 32 0.0 93.8 3.1 0.0 3.1Kakamega 2 61 1 0 0 64 3.1 95.3 1.6 0.0 0.0Kisumu 1 48 4 0 0 53 1.9 90.6 7.5 0.0 0.0Garissa 0 9 1 1 0 11 0.0 81.8 9.1 9.1 0.0TOTAL 7 598 52 3 1 661 1.1 90.5 7.9 0.5 0.2
84
Table 21: Distribution of Pre-Schools by Attachment/Linkage to a Primary School, 1995 Number % Attached Linked Not
attached/ Linked
Total Attached Linked Attached/ Linked
Not attached/
Linked
Total
MAJOR URBAN
25 13 84 122 20.5 10.7 31.1 68.9 100.0
Mombasa 7 5 22 34 20.6 14.7 35.3 64.7 100.0Nairobi 18 8 62 88 20.5 9.1 29.5 70.5 100.0OTHER URBAN
24 6 40 70 34.3 8.6 42.9 57.1 100.0
Thika 2 0 5 7 28.6 0.0 28.6 71.4 100.0Nakuru 4 1 12 17 23.5 5.9 29.4 70.6 100.0Eldoret 3 1 12 16 18.8 6.3 25.0 75.0 100.0Kitale 7 0 0 7 100.0 0.0 100.0 0.0 100.0Kisumu 8 4 11 23 34.8 17.4 52.2 47.8 100.0RURAL 484 133 57 674 71.8 19.7 91.5 8.5 100.0Kilifi 36 10 4 50 72.0 20.0 92.0 8.0 100.0Nyandarua 44 25 6 75 58.7 33.3 92.0 8.0 100.0Machakos 99 19 20 138 71.7 13.8 85.5 14.5 100.0Uasin Gishu 40 4 1 45 88.9 8.9 97.8 2.2 100.0Nakuru 45 38 12 95 47.4 40.0 87.4 12.6 100.0Kericho 46 8 0 54 85.2 14.8 100.0 0.0 100.0Narok 29 2 6 37 78.4 5.4 83.8 16.2 100.0Kakamega 96 8 0 104 92.3 7.7 100.0 0.0 100.0Kisumu 42 14 6 62 67.7 22.6 90.3 9.7 100.0Garissa 7 5 2 14 50.0 35.7 85.7 14.3 100.0TOTAL 533 152 181 866 61.5 17.6 79.1 20.9 100.0
85
Table 22: Distribution of Attached Pre-Schools by Sharing Arrangements of Management Committee and Headteachers’ Attendance of Primary School Staff Meetings, 1995 No. of
Attached Pre-schools
Sharing Management Committee
Centre Headteacher attend Primary School Meetings
Share Don’t Share
% Sharing
Attended Not Attended
% Attended
MAJOR URBAN
25 16 9 64.0 17 8 68.0
Mombasa 7 4 3 57.1 2 5 28.6Nairobi 18 12 6 66.7 15 3 83.3OTHER URBAN
24 17 7 70.8 15 9 62.5
Thika 2 1 1 50.0 1 1 50.0Nakuru 4 2 2 50.0 3 1 75.0Eldoret 3 2 1 66.7 1 2 33.3Kitale 7 6 1 85.7 6 1 85.7Kisumu 8 6 2 75.0 4 4 50.0RURAL 484 369 115 76.2 325 159 67.1Kilifi 36 34 2 94.4 26 10 72.2Nyandarua 44 19 25 43.2 15 29 34.1Machakos 99 89 10 89.9 68 31 68.7Uasin Gishu 40 15 25 37.5 24 16 60.0Nakuru 45 27 18 60.0 13 32 28.9Kericho 46 29 17 63.0 30 16 65.2Narok 29 28 1 96.6 29 0 100.0Kakamega 96 88 8 91.7 86 10 89.6Kisumu 42 33 9 78.6 30 12 71.4Garissa 7 7 0 100.0 4 3 57.1TOTAL 533 402 131 75.4 357 176 67.0
86
Table 23: Distribution of Pre-Schools by Main Supervisor and Sponsor Number % No
Visit Primary School
Inspector
Zonal Inspector
DICECE Staff
Total Central Govt.
Nursery School
Supervisor
Primary School
Headteacher
Other Total No Visit
Primary School
Inspector
Zonal Inspector
DICECE Staff
Total Central Govt.
Nursery School
Supervisor
Primary School
Headteacher
Other Total
BY SPONSOR
ALL AREAS
119 55 196 83 334 238 115 60 866 13.7 6.4 22.6 9.6 38.6 27.5 13.3 6.9 100.0
Community 88 31 134 34 199 207 43 31 568 15.5 5.5 23.6 6.0 35.0 36.4 7.6 5.5 100.0 Religious 20 8 22 18 48 2 23 13 106 18.9 7.5 20.8 17.0 45.3 1.9 21.7 12.3 100.0 Private 6 5 18 17 40 6 17 6 75 8.0 6.7 24.0 22.7 53.3 8.0 22.7 8.0 100.0 Local Auth. 4 10 20 12 42 18 29 5 98 4.1 10.2 20.4 12.2 42.9 18.4 29.6 5.1 100.0 Other 1 1 2 2 5 5 3 5 19 5.3 5.3 10.5 10.5 26.3 26.3 15.8 26.3 100.0 MAJOR URBAN
17 5 20 35 60 7 23 15 122 13.9 4.1 16.4 28.7 49.2 5.7 18.9 12.3 100.0
Community 5 2 7 4 13 2 2 1 23 21.7 8.7 30.4 17.4 56.5 8.7 8.7 4.3 100.0 Religious 9 2 3 12 17 0 12 6 44 20.5 4.5 6.8 27.3 38.6 0.0 27.3 13.6 100.0 Private 3 1 6 12 19 3 5 4 34 8.8 2.9 17.6 35.3 55.9 8.8 14.7 11.8 100.0 Local Auth. 0 0 4 7 11 2 3 1 17 0.0 0.0 23.5 41.2 64.7 11.8 17.6 5.9 100.0 Other 0 0 0 0 0 0 1 3 4 0.0 0.0 0.0 0.0 0.0 0.0 25.0 75.0 100.0 OTHER URBAN
4 6 21 3 30 1 30 5 70 5.7 8.6 30.0 4.3 42.9 1.4 42.9 7.1 100.0
Community 1 3 8 1 12 1 6 2 22 4.5 13.6 36.4 4.5 54.5 4.5 27.3 9.1 100.0 Religious 2 0 6 2 8 0 9 1 20 10.0 0.0 30.0 10.0 40.0 0.0 45.0 5.0 100.0 Private 1 3 6 0 9 0 7 1 18 5.6 16.7 33.3 0.0 50.0 0.0 38.9 5.6 100.0 Local Auth. 0 0 1 0 1 0 6 0 7 0.0 0.0 14.3 0.0 14.3 0.0 85.7 0.0 100.0 Other 0 0 0 0 0 0 2 1 3 0.0 0.0 0.0 0.0 0.0 0.0 66.7 33.3 100.0 RURAL 98 44 155 45 244 230 62 40 674 14.5 6.5 23.0 6.7 36.2 34.1 9.2 5.9 100.0 Community 82 26 119 29 174 204 35 28 523 15.7 5.0 22.8 5.5 33.3 39.0 6.7 5.4 100.0 Religious 9 6 13 4 23 2 2 6 42 21.4 14.3 31.0 9.5 54.8 4.8 4.8 14.3 100.0 Private 2 1 6 5 12 3 5 1 23 8.7 4.3 26.1 21.7 52.2 13.0 21.7 4.3 100.0 Local Auth. 4 10 15 5 30 16 20 4 74 5.4 13.5 20.3 6.8 40.5 21.6 27.0 5.4 100.0 Other 1 1 2 2 5 5 0 1 12 8.3 8.3 16.7 16.7 41.7 41.7 0.0 8.3 100.0 BY REGION
MAJOR URBAN
17 5 20 35 60 7 23 15 122 13.9 4.1 16.4 28.7 49.2 5.7 18.9 12.3 100.0
Mombasa 7 1 9 10 20 2 1 4 34 20.6 2.9 26.5 29.4 58.8 5.9 2.9 11.8 100.0 Nairobi 10 4 11 25 40 5 22 11 88 11.4 4.5 12.5 28.4 45.5 5.7 25.0 12.5 100.0 OTHER URBAN
4 6 21 3 30 1 30 5 70 5.7 8.6 30.0 4.3 42.9 1.4 42.9 7.1 100.0
Thika 1 0 1 0 1 0 5 0 7 14.3 0.0 14.3 0.0 14.3 0.0 71.4 0.0 100.0
87
Number % No
Visit Primary School
Inspector
Zonal Inspector
DICECE Staff
Total Central Govt.
Nursery School
Supervisor
Primary School
Headteacher
Other Total No Visit
Primary School
Inspector
Zonal Inspector
DICECE Staff
Total Central Govt.
Nursery School
Supervisor
Primary School
Headteacher
Other Total
Nakuru 3 0 1 1 2 0 10 2 17 17.6 0.0 5.9 5.9 11.8 0.0 58.8 11.8 100.0 Eldoret 0 1 4 0 5 1 9 1 16 0.0 6.3 25.0 0.0 31.3 6.3 56.3 6.3 100.0 Kitale 0 0 2 0 2 0 5 0 7 0.0 0.0 28.6 0.0 28.6 0.0 71.4 0.0 100.0 Kisumu 0 5 13 2 20 0 1 2 23 0.0 21.7 56.5 8.7 87.0 0.0 4.3 8.7 100.0 RURAL 98 44 155 45 244 230 62 40 674 14.5 6.5 23.0 6.7 36.2 34.1 9.2 5.9 100.0 Kilifi 9 2 11 5 18 15 5 3 50 18.0 4.0 22.0 10.0 36.0 30.0 10.0 6.0 100.0 Nyandarua 9 3 14 3 20 40 2 4 75 12.0 4.0 18.7 4.0 26.7 53.3 2.7 5.3 100.0 Machakos 18 0 32 4 36 56 17 11 138 13.0 0.0 23.2 2.9 26.1 40.6 12.3 8.0 100.0 Uasin Gishu 3 6 9 0 15 24 3 0 45 6.7 13.3 20.0 0.0 33.3 53.3 6.7 0.0 100.0 Nakuru 13 11 21 3 35 37 4 6 95 13.7 11.6 22.1 3.2 36.8 38.9 4.2 6.3 100.0 Kericho 18 4 11 4 19 14 1 2 54 33.3 7.4 20.4 7.4 35.2 25.9 1.9 3.7 100.0 Narok 4 2 9 3 14 5 13 1 37 10.8 5.4 24.3 8.1 37.8 13.5 35.1 2.7 100.0 Kakamega 14 9 36 3 48 28 10 4 104 13.5 8.7 34.6 2.9 46.2 26.9 9.6 3.8 100.0 Kisumu 10 5 12 10 27 9 7 9 62 16.1 8.1 19.4 16.1 43.5 14.5 11.3 14.5 100.0 Garissa 0 2 0 10 12 2 0 0 14 0.0 14.3 0.0 71.4 85.7 14.3 0.0 0.0 100.0 TOTAL 119 55 196 83 334 238 115 60 866 13.7 6.4 22.6 9.6 38.6 27.5 13.3 6.9 100.0
88
Table 24: Distribution of Pre-Schools Which Reported Enrolment Data, 1990-1995 1990 1991 1992 1993 1994 1995 MAJOR URBAN 42 50 65 75 96 120Mombasa 16 16 22 25 30 33Nairobi 26 34 43 50 66 87OTHER URBAN 20 28 37 49 59 70Thika 2 6 6 6 7 7Nakuru 5 6 9 15 17 17Eldoret 4 7 9 12 13 16Kitale 4 4 6 7 7 7Kisumu 5 5 7 9 15 23RURAL 331 385 423 488 586 672Kilifi 32 34 34 41 45 49Nyandarua 26 34 43 53 70 75Machakos 94 116 122 128 133 138Uasin Gishu 14 17 20 22 32 45Nakuru 50 50 55 67 82 95Kericho 40 46 49 50 54 54Narok 2 4 6 11 18 37Kakamega 49 58 67 79 87 103Kisumu 21 22 23 29 53 62Garissa 3 4 4 8 12 14TOTAL 393 463 525 612 741 862
89
Table 25: Distribution of Pre-Schools by Enrolment Size and Main Sponsor, 1995 Enrolment Size Enrolment Size (%) 1-19 20-39 40-69 70-99 100+ Total 1-19 20-39 40-69 70-99 100+ Mean Enrolment MAJOR URBAN 9 22 36 20 33 120 7.5 18.3 30.0 16.7 27.5 77.4 Community 2 7 6 4 4 23 8.7 30.4 26.1 17.4 17.4 58.3 Religious organization 3 9 8 5 17 42 7.1 21.4 19.0 11.9 40.5 90.5 Private 4 4 12 5 9 34 11.8 11.8 35.3 14.7 26.5 78.2 Local Authority 0 2 7 5 3 17 0.0 11.8 41.2 29.4 17.6 70.5 Other 0 0 3 1 0 4 0.0 0.0 75.0 25.0 0.0 63.5 OTHER URBAN 2 13 28 15 12 70 2.9 18.6 40.0 21.4 17.1 72.0 Community 1 3 11 5 2 22 4.5 13.6 50.0 22.7 9.1 68.5 Religious organization 0 4 7 3 6 20 0.0 20.0 35.0 15.0 30.0 73.6 Private 0 3 6 6 3 18 0.0 16.7 33.3 33.3 16.7 84.1 Local Authority 0 2 3 1 1 7 0.0 28.6 42.9 14.3 14.3 64.0 Other 1 1 1 0 0 3 33.3 33.3 33.3 0.0 0.0 32.7 RURAL 40 214 249 108 61 672 6.0 31.8 37.1 16.1 9.1 56.1 Community 29 164 203 84 42 522 5.6 31.4 38.9 16.1 8.0 54.5 Religious organization 6 17 12 5 2 42 14.3 40.5 28.6 11.9 4.8 47.8 Private 3 7 6 4 3 23 13.0 30.4 26.1 17.4 13.0 59.0 Local Authority 2 24 25 11 11 73 2.7 32.9 34.2 15.1 15.1 59.9 Other 0 2 3 4 3 12 0.0 16.7 25.0 33.3 25.0 121.9 BY REGION MAJOR URBAN Mombasa 3 7 8 7 8 33 9.1 21.2 24.2 21.2 24.2 86.42 Nairobi 6 15 28 13 25 87 6.9 17.2 32.2 14.9 28.7 75.70 OTHER URBAN Thika 1 1 2 3 0 7 14.3 14.3 28.6 42.9 0.0 54.43 Nakuru 0 3 6 4 4 17 0.0 17.6 35.3 23.5 23.5 84.18 Eldoret 1 5 5 1 4 16 6.3 31.3 31.3 6.3 25.0 70.06 Kitale 0 2 2 1 2 7 0.0 28.6 28.6 14.3 28.6 77.57 Kisumu 0 2 13 6 2 23 0.0 8.7 56.5 26.1 8.7 67.91
90
Enrolment Size Enrolment Size (%) 1-19 20-39 40-69 70-99 100+ Total 1-19 20-39 40-69 70-99 100+ Mean Enrolment RURAL Kilifi 0 10 17 14 8 49 0.0 20.4 34.7 28.6 16.3 71.84 Nyandarua 5 28 21 13 8 75 6.7 37.3 28.0 17.3 10.7 53.97 Machakos 12 66 46 11 3 138 8.7 47.8 33.3 8.0 2.2 41.02 Uasin Gishu 3 13 16 11 2 45 6.7 28.9 35.6 24.4 4.4 53.29 Nakuru 6 22 35 18 14 95 6.3 23.2 36.8 18.9 14.7 66.51 Kericho 3 10 29 9 3 54 5.6 18.5 53.7 16.7 5.6 55.35 Narok 6 17 9 4 1 37 16.2 45.9 24.3 10.8 2.7 41.30 Kakamega 3 21 40 21 18 103 2.9 20.4 38.8 20.4 17.5 73.01 Kisumu 1 26 30 3 2 62 1.6 41.9 48.4 4.8 3.2 45.39 Garissa 1 1 6 4 2 14 7.1 7.1 42.9 28.6 14.3 70.86
91
Table 26: Pre-School Gross Enrolment Ratios by Sex Based on the ECCD Survey, 1995 (%) Boys Girls Total Boys - girls (percentage points) MAJOR URBAN 43.7 45.7 44.0 -2.0Mombasa 56.7 50.6 53.6 6.1Nairobi 39.5 44.1 40.8 -4.6OTHER URBAN 46.3 47.7 47.0 -1.4Thika 49.5 44.0 46.7 5.5Nakuru 44.1 46.5 45.3 -2.4Eldoret 46.8 44.9 45.9 1.9Kitale 46.1 46.3 46.2 -0.2Kisumu 47.2 53.1 50.2 -5.9RURAL 36.7 35.2 36.0 1.5Kilifi 31.4 27.5 29.5 3.9Nyandarua 56.4 52.5 54.5 3.9Machakos 35.5 35.9 35.7 -0.4Uasin Gishu 37.3 39.4 38.3 -2.1Nakuru 43.8 43.1 43.4 0.7Kericho 34.4 32.3 33.4 2.1Narok 21.9 17.3 19.6 4.6Kakamega 36.7 35.1 35.9 1.6Kisumu 32.1 34.2 33.1 -2.1Garissa 39.0 26.5 33.0 12.5OVERALL 38.6 38.0 38.2 0.6 Table 27: Pre-School Gross Enrolment Ratios by Sex Based on Official Statistics, 1994 (%) Boys Girls Total Boys - girls (percentage points) MAJOR URBAN 38.1 41.1 39.6 -3.0Mombasa 63.2 65.7 64.5 -2.5Nairobi 28.4 31.6 30.0 -3.2OTHER URBAN 44.2 43.9 44.0 0.4Thika 47.6 45.7 46.6 1.9Nakuru 44.6 46.4 45.5 -1.8Eldoret 25.2 26.9 26.1 -1.7Kitale 62.0 76.2 68.8 -14.2Kisumu 50.8 43.5 47.1 7.3RURAL 32.7 32.3 32.5 0.4Kilifi 29.6 19.7 24.7 9.9Nyandarua 51.3 52.0 51.7 -0.7Machakos 35.0 34.5 34.7 0.5Uasin Gishu 34.3 34.5 34.4 -0.2Nakuru 36.0 36.2 36.1 -0.2Kericho 33.4 33.1 33.2 0.3Narok - - -Kakamega 29.9 30.1 30.0 -0.2Kisumu 32.0 35.5 33.7 -3.5Garissa - - -TOTAL 34.4 34.5 34.4 -0.1
92
Table 28: Estimated Weighted Enrolment and Fees, 1994 Mean Fees (Shs) Weighted Enrolment Weighted Total Fees per Year (Shs) MAJOR URBAN Mombasa 4,581 21,054 96,442,555Nairobi 4,911 50,667 248,846,962OTHER URBAN Thika 1,289 2,721 3,509,000Nakuru 3,806 9,512 36,198,088Eldoret 1,946 8,337 16,223,568Kitale 1,553 3,723 5,782,937Kisumu 2,003 10,255 20,542,959RURAL Kilifi 541 26,271 14,210,062Nyandarua 840 27,257 22,887,472Machakos 543 37,576 20,400,047Uasin Gishu 386 17,266 6,663,154Nakuru 539 44,492 23,987,463Kericho 827 20,148 16,666,577Narok 692 9,705 6,713,977Kakamega 769 50,832 39,091,532Kisumu 266 20,651 5,483,975Garissa 658 1,842 1,212,324 Table 29: Distribution of Pre-Schools by Annual Fees (Shs) per Child, 1995 Number % Don’t
Pay <500 500-
999 1000-2999
3000+ Total Don’t Pay
<500 500-999
1000-2999
3000+
MAJOR URBAN
2 2 13 50 49 116 1.7 1.7 11.2 43.1 42.2
Mombasa 0 0 4 19 9 32 0.0 0.0 12.5 59.4 28.1Nairobi 2 2 9 31 40 84 2.4 2.4 10.7 36.9 47.6OTHER URBAN
0 9 23 25 13 70 0.0 12.9 32.9 35.7 18.6
Thika 0 2 1 4 0 7 0.0 28.6 14.3 57.1 0.0Nakuru 0 0 2 8 7 17 0.0 0.0 11.8 47.1 41.2Eldoret 0 1 8 6 1 16 0.0 6.3 50.0 37.5 6.3Kitale 0 0 4 3 0 7 0.0 0.0 57.1 42.9 0.0Kisumu 0 6 8 4 5 23 0.0 26.1 34.8 17.4 21.7RURAL 9 439 127 63 12 650 1.4 67.5 19.5 9.7 1.8Kilifi 1 32 14 2 0 49 2.0 65.3 28.6 4.1 0.0Nyandarua 0 21 30 22 1 74 0.0 28.4 40.5 29.7 1.4Machakos 0 99 28 9 1 137 0.0 72.3 20.4 6.6 0.7Uasin Gishu 0 37 5 2 1 45 0.0 82.2 11.1 4.4 2.2Nakuru 3 59 19 9 0 90 3.3 65.6 21.1 10.0 0.0Kericho 0 40 8 2 3 53 0.0 75.5 15.1 3.8 5.7Narok 0 26 4 4 1 35 0.0 74.3 11.4 11.4 2.9Kakamega 0 68 14 6 5 93 0.0 73.1 15.1 6.5 5.4Kisumu 4 51 2 3 0 60 6.7 85.0 3.3 5.0 0.0Garissa 1 6 3 4 0 14 7.1 42.9 21.4 28.6 0.0TOTAL 11 450 163 138 74 836 1.3 53.8 19.5 16.5 8.9
93
Table 30: Distribution of Pre-Schools by Action Taken When Fees is Not Paid in Part or Full Number % Continue Sent
AwayAssisted Don’t
Pay Other
Actions Total Continue Sent
Away Assisted Don’t
Pay Other
Actions Continue/ Assisted
Total
MAJOR URBAN
43 47 11 2 19 122 35.2 38.5 9.0 1.6 15.6 44.3 100.0
Mombasa 17 11 2 0 4 34 50.0 32.4 5.9 0.0 11.8 55.9 100.0Nairobi 26 36 9 2 15 88 29.5 40.9 10.2 2.3 17.0 39.8 100.0OTHER URBAN
12 34 8 0 16 70 17.1 48.6 11.4 0.0 22.9 28.6 100.0
Thika 5 2 0 0 0 7 71.4 28.6 0.0 0.0 0.0 71.4 100.0Nakuru 0 11 0 0 6 17 0.0 64.7 0.0 0.0 35.3 0.0 100.0Eldoret 3 6 7 0 0 16 18.8 37.5 43.8 0.0 0.0 62.5 100.0Kitale 0 7 0 0 0 7 0.0 100.0 0.0 0.0 0.0 0.0 100.0Kisumu 4 8 1 0 10 23 17.4 34.8 4.3 0.0 43.5 21.7 100.0RURAL 215 323 20 9 107 674 31.9 47.9 3.0 1.3 15.9 34.9 100.0Kilifi 13 18 2 1 16 50 26.0 36.0 4.0 2.0 32.0 30.0 100.0Nyandarua 6 47 5 0 17 75 8.0 62.7 6.7 0.0 22.7 14.7 100.0Machakos 63 61 2 0 12 138 45.7 44.2 1.4 0.0 8.7 47.1 100.0Uasin Gishu
12 22 3 0 8 45 26.7 48.9 6.7 0.0 17.8 33.3 100.0
Nakuru 21 59 1 3 11 95 22.1 62.1 1.1 3.2 11.6 23.2 100.0Kericho 10 28 1 0 15 54 18.5 51.9 1.9 0.0 27.8 20.4 100.0Narok 17 12 2 0 6 37 45.9 32.4 5.4 0.0 16.2 51.4 100.0Kakamega 44 47 3 0 10 104 42.3 45.2 2.9 0.0 9.6 45.2 100.0Kisumu 19 27 1 4 11 62 30.6 43.5 1.6 6.5 17.7 32.3 100.0Garissa 10 2 0 1 1 14 71.4 14.3 0.0 7.1 7.1 71.4 100.0TOTAL 270 404 39 11 142 866 31.2 46.7 4.5 1.3 16.4 35.7 100.0
Table 31: Percentage Distribution of Enrolment in Pre-Schools by Ability to Pay Fees, 1994 Completed Partial No Payment Number of CentresMAJOR URBAN Mombasa 81.5 12.8 5.7 29Nairobi 82.8 9.9 7.3 74OTHER URBAN Thika 68.7 10.6 20.7 7Nakuru 80.4 8.0 11.6 17Eldoret 87.3 8.7 4.0 14Kitale 55.3 30.5 14.2 7Kisumu 76.5 14.1 9.4 20RURAL Kilifi 63.5 20.6 15.8 45Nyandarua 83.5 13.9 2.6 73Machakos 82.7 9.8 7.5 135Uasin Gishu 74.7 15.7 9.6 42Nakuru 80.9 11.0 8.2 80Kericho 73.7 17.1 9.1 48Narok 80.2 10.6 9.2 31Kakamega 56.1 24.3 19.5 89Kisumu 47.8 25.1 27.1 50Garissa 63.5 16.8 19.6 12
94
Table 32: Distribution of Pre-School Employees by Gender, Occupation and Monthly Salary, 1995 Number %
MaleNo. of centres
Personnel per centre
Monthly Salary (Shs) Male Female Total Males Females TotalMAJOR URBAN
Teachers 18 455 473 3.8 122 3.9 3,527 3,890 3,877
Nonteaching 38 121 159 23.9 122 1.3 3,247 2,836 2,937Mombasa Teachers 2 139 141 1.4 34 4.1 4,500 3,730 3,741 Nonteaching 9 27 36 25.0 34 1.1 2,461 2,350 2,375Nairobi Teachers 16 316 332 4.8 88 3.8 3,378 3,972 3,945 Nonteaching 29 94 123 23.6 88 1.4 3,472 2,994 3,114OTHER URBAN
Teachers 8 215 223 3.6 70 3.2 1,409 2,178 2,152
Nonteaching 26 38 64 40.6 70 0.9 1,777 1,387 1,537Thika Teachers 1 17 18 5.6 7 2.6 1,560 2,111 2,080 Nonteaching 1 2 3 33.3 7 0.4 1,560 1,875 1,770Nakuru Teachers 4 63 67 6.0 17 3.9 1,450 2,797 2,716 Nonteaching 11 22 33 33.3 17 1.9 2,514 1,465 1,825Eldoret Teachers 0 48 48 0.0 16 3.0 2,142 2,142 Nonteaching 1 3 4 25.0 16 0.3 1,760 1,340 1,445Kitale Teachers 0 24 24 0.0 7 3.4 1,236 1,236 Nonteaching 2 7 9 22.2 7 1.3 800 1,300 1,238Kisumu Teachers 3 63 66 4.5 23 2.9 1,250 1,926 1,902 Nonteaching 11 4 15 73.3 23 0.7 1,011 925 985RURAL Teachers 24 1060 1084 2.2 674 1.6 1,944 1,508 1,518 Nonteaching 55 98 153 35.9 674 0.2 1,081 824 917Kilifi Teachers 3 80 83 3.6 50 1.7 2,307 1,935 1,948 Nonteaching 0 10 10 0.0 50 0.2 925 925Nyandarua Teachers 1 124 125 0.8 75 1.7 1,000 1,083 1,083 Nonteaching 3 6 9 33.3 75 0.1 633 950 814Machakos Teachers 3 187 190 1.6 138 1.4 933 1,293 1,287 Nonteaching 15 7 22 68.2 138 0.2 757 450 659Uasin Gishu Teachers 1 58 59 1.7 45 1.3 600 1,457 1,443 Nonteaching 1 3 4 25.0 45 0.1 2,330 1,067 1,383Nakuru Teachers 2 173 175 1.1 95 1.8 1,817 1,803 Nonteaching 6 11 17 35.3 95 0.2 550 877 871Kericho Teachers 0 77 77 0.0 54 1.4 858 1,255 1,255 Nonteaching 3 8 11 27.3 54 0.2 933 1,284 1,188Narok Teachers 4 56 60 6.7 37 1.6 2,013 2,837 2,782 Nonteaching 0 0 0 - 37 0.0 Kakamega Teachers 2 205 207 1.0 104 2.0 3,965 1,179 1,207 Nonteaching 20 45 65 30.8 104 0.6 1,123 614 767Kisumu Teachers 1 83 84 1.2 62 1.4 350 1,712 1,693 Nonteaching 1 3 4 25.0 62 0.1 3,810 2,726 2,997Garissa Teachers 7 17 24 29.2 14 1.7 2,557 1,759 2,002 Nonteaching 6 5 11 54.5 14 0.8 1,617 760 1,227TOTAL Teachers 50 1730 1780 2.8 866 2.1 2,379 2,178 2,183 Nonteaching 119 257 376 31.6 866 0.4 1,913 1,825 1,853
95
Table 33(a): Distribution of Teachers by Monthly Salary (Shs), 1995 Not
Stated <500 501-
1000 1001-1500
1501-2000
2001-3000
3001-4000
4001-6000
6000+ Total (excluding not stated)
Total (including not stated)
MAJOR URBAN
50 2 22 59 63 82 32 73 90 423 473
Mombasa 1 2 6 22 24 26 7 20 33 140 141Nairobi 49 0 16 37 39 56 25 53 57 283 332OTHER URBAN
10 7 26 72 38 39 9 14 8 213 223
Thika 0 1 0 5 6 4 0 2 0 18 18Nakuru 0 0 4 21 12 17 5 2 6 67 67Eldoret 0 2 10 13 6 9 2 4 2 48 48Kitale 0 1 6 15 1 1 0 0 0 24 24Kisumu 10 3 6 18 13 8 2 6 0 56 66RURAL 17 163 429 187 58 95 46 84 5 1,067 1084Kilifi 1 4 35 18 4 2 1 18 0 82 83Nyandarua 3 0 81 38 0 0 0 2 1 122 125Machakos 1 24 77 45 19 14 4 6 0 189 190Uasin Gishu
0 7 26 7 3 16 0 0 0 59 59
Nakuru 0 4 83 29 8 20 6 25 0 175 175Kericho 0 11 46 7 6 2 0 4 1 77 77Narok 0 0 6 15 1 7 18 13 0 60 60Kakamega 2 82 54 20 14 24 6 2 3 205 207Kisumu 9 31 16 2 0 3 10 13 0 75 84Garissa 1 0 5 6 3 7 1 1 0 23 24TOTAL 77 172 477 318 159 216 87 171 103 1703 1780 Table 33(b): Percentage Distribution of Teachers by Monthly Salary, 1995 <500 501-
1000 1001-1500
1501-2000
2001-3000
3001-4000
4001-6000
6000+ Total (excluding not stated)
MAJOR URBAN
0.5 5.2 13.9 14.9 19.4 7.6 17.3 21.3 100.0
Mombasa 1.4 4.3 15.7 17.1 18.6 5.0 14.3 23.6 100.0Nairobi 0.0 5.7 13.1 13.8 19.8 8.8 18.7 20.1 100.0OTHER URBAN
3.3 12.2 33.8 17.8 18.3 4.2 6.6 3.8 100.0
Thika 5.6 0.0 27.8 33.3 22.2 0.0 11.1 0.0 100.0Nakuru 0.0 6.0 31.3 17.9 25.4 7.5 3.0 9.0 100.0Eldoret 4.2 20.8 27.1 12.5 18.8 4.2 8.3 4.2 100.0Kitale 4.2 25.0 62.5 4.2 4.2 0.0 0.0 0.0 100.0Kisumu 5.4 10.7 32.1 23.2 14.3 3.6 10.7 0.0 100.0RURAL 15.3 40.2 17.5 5.4 8.9 4.3 7.9 0.5 100.0Kilifi 4.9 42.7 22.0 4.9 2.4 1.2 22.0 0.0 100.0Nyandarua 0.0 66.4 31.1 0.0 0.0 0.0 1.6 0.8 100.0Machakos 12.7 40.7 23.8 10.1 7.4 2.1 3.2 0.0 100.0Uasin Gishu 11.9 44.1 11.9 5.1 27.1 0.0 0.0 0.0 100.0Nakuru 2.3 47.4 16.6 4.6 11.4 3.4 14.3 0.0 100.0Kericho 14.3 59.7 9.1 7.8 2.6 0.0 5.2 1.3 100.0Narok 0.0 10.0 25.0 1.7 11.7 30.0 21.7 0.0 100.0Kakamega 40.0 26.3 9.8 6.8 11.7 2.9 1.0 1.5 100.0Kisumu 41.3 21.3 2.7 0.0 4.0 13.3 17.3 0.0 100.0Garissa 0.0 21.7 26.1 13.0 30.4 4.3 4.3 0.0 100.0TOTAL 10.1 28.0 18.7 9.3 12.7 5.1 10.0 6.0 100.0
96
Table 34: Distribution of Pre-School Teachers by Academic Attainment and ECCD Training, 1995 Educational Attainment Training
Programme Not
Stated Below CPE
CPE Secondary Postsecondary Total Total (%)
MAJOR URBAN
1 22 52 393 5 473 100.0
Major Urban - per cent
0.2 4.7 11.0 83.1 1.1 100.0
None 1 9 20 108 0 138 29.2 Government 0 8 24 158 1 191 40.4 KHA 0 1 1 26 1 29 6.1 Montessori 0 0 5 54 0 59 12.5 Other 0 4 2 47 3 56 11.8OTHER URBAN
4 15 51 152 1 223 100.0
Other Urban - per cent
1.4 6.8 23.0 68.5 0.5 100.0
Not Stated 3 0 0 0 0 3 1.4 None 0 5 20 52 0 77 34.7 Government 1 7 21 69 0 98 43.7 KHA 0 1 1 6 1 9 4.1 Montessori 0 1 0 4 0 5 2.3 Other 0 1 9 21 0 31 14.0RURAL 6 119 427 532 0 1,084 100.0Rural - per cent
0.6 11.0 39.4 49.1 0.0 100.0
Not Stated 4 0 0 0 0 4 0.4 None 0 50 217 273 0 540 49.8 Government 2 54 168 224 0 448 41.3 KHA 0 1 5 4 0 10 0.9 Montessori 0 0 3 3 0 6 0.6 Other 0 14 34 28 0 76 7.0TOTAL 11 156 530 1077 6 1780 100.0Total - per cent
0.6 8.8 29.8 60.5 0.3 100.0
Not Stated 7 0 0 0 0 7 0.4 None 1 64 257 433 0 755 42.4 Government 3 69 213 451 1 737 41.4 KHA 0 3 7 36 2 48 2.7 Montessori 0 1 8 61 0 70 3.9 Other 0 19 45 96 3 163 9.2 Note: KHA stands for “The Kindergarten Headmistresses Association”.
97
Table 35: Distribution of Pre-School Teachers by Academic Attainment and Gender, 1995 Sex Educational Attainment % Not
Stated Below CPE
CPE Secondary Postsecondary Total CPE and below
Secondary and above
MAJOR URBAN
Male 0 1 1 14 2 18 11.1 88.9
Female 1 21 51 379 3 455 15.9 84.1 Total 1 22 52 393 5 473 15.7 84.3Mombasa Male 0 1 0 1 0 2 50.0 50.0 Female 0 4 30 105 0 139 24.5 75.5 Total 0 5 30 106 0 141 24.8 75.2Nairobi Male 0 0 1 13 2 16 6.3 93.8 Female 1 17 21 274 3 316 12.0 87.7 Total 1 17 22 287 5 332 11.7 88.0OTHER URBAN
Male 0 0 3 5 0 8 37.5 62.5
Female 4 15 48 147 1 215 29.9 70.1 Total 4 15 51 152 1 223 30.1 69.9Thika Male 0 0 1 0 0 1 100.0 0.0 Female 0 3 3 11 0 17 35.3 64.7 Total 0 3 4 11 0 18 38.9 61.1Nakuru Male 0 0 1 3 0 4 25.0 75.0 Female 1 0 13 48 1 63 20.6 77.8 Total 1 0 14 51 1 67 20.9 77.6Eldoret Female 1 6 9 32 0 48 31.3 66.7Kitale Female 0 0 7 17 0 24 29.2 70.8Kisumu Male 0 0 1 2 0 3 33.3 66.7 Female 2 6 16 39 0 63 34.9 61.9 Total 2 6 17 41 0 66 34.8 62.1RURAL Male 0 3 14 7 0 24 70.8 29.2 Female 6 116 413 525 0 1060 50.2 49.8 Total 6 119 427 532 0 1084 50.6 49.4Kilifi Male 0 0 2 1 0 3 66.7 33.3 Female 0 13 45 22 0 80 72.5 27.5 Total 0 13 47 23 0 83 72.3 27.7Nyandarua Male 0 0 0 1 0 1 0.0 100.0 Female 0 7 29 88 0 124 29.0 71.0 Total 0 7 29 89 0 125 28.8 71.2Machakos Male 0 0 1 2 0 3 33.3 66.7 Female 0 19 90 78 0 187 58.3 41.7 Total 0 19 91 80 0 190 57.9 42.1Uasin Gishu Male 0 0 1 0 0 1 100.0 0.0 Female 0 5 23 30 0 58 48.3 51.7 Total 0 5 24 30 0 59 49.2 50.8Nakuru Male 0 1 1 0 0 2 100.0 0.0 Female 1 11 62 99 0 173 42.2 57.2 Total 1 12 63 99 0 175 42.9 56.6Kericho Female 0 10 27 40 0 77 48.1 51.9Narok Male 0 1 3 0 0 4 100.0 0.0 Female 3 17 17 19 0 56 60.7 33.9 Total 3 18 20 19 0 60 63.3 31.7Kakamega Male 0 0 0 2 0 2 0.0 100.0 Female 2 23 77 103 0 205 48.8 50.2 Total 2 23 77 105 0 207 48.3 50.7Kisumu Male 0 0 1 0 0 1 100.0 0.0 Female 0 10 35 38 0 83 54.2 45.8
98
Sex Educational Attainment % Not
Stated Below CPE
CPE Secondary Postsecondary Total CPE and below
Secondary and above
Total 0 10 36 38 0 84 54.8 45.2Garissa Male 0 1 5 1 0 7 85.7 14.3 Female 0 1 8 8 0 17 52.9 47.1 Total 0 2 13 9 0 24 62.5 37.5TOTAL Male 0 4 18 26 2 50 44.0 56.0 Female 11 152 512 1,051 4 1,730 38.6 61.4 Total 11 156 530 1,077 6 1,780 38.8 61.2 Table 36: Distribution of Pre-School Teachers by ECCD Training and Gender, 1995 SEX None Government KHA Montessori Other Total % trained by
Government MAJOR URBAN
Male 14 2 0 0 2 18 50.0
Female 124 189 29 59 54 455 57.1 Total 138 191 29 59 56 473 57.0Mombasa Male 2 0 0 0 0 2 - Female 46 66 3 18 6 139 71.0 Total 48 66 3 18 6 141 71.0Nairobi Male 12 2 0 0 2 16 50.0 Female 78 123 26 41 48 316 51.7 Total 90 125 26 41 50 332 51.7OTHER URBAN
Male 5 0 0 1 2 8 0.0
Female 72 98 9 4 29 212 70.0 Total 77 98 9 5 31 220 68.5Thika Male 1 0 0 0 0 1 - Female 6 10 0 0 1 17 90.9 Total 7 10 0 0 1 18 90.9Nakuru Male 1 0 0 1 2 4 0.0 Female 17 23 4 3 16 63 50.0 Total 18 23 4 4 18 67 46.9Eldoret Female 21 13 4 1 8 47 50.0Kitale Female 8 16 0 0 0 24 100.0Kisumu Male 3 0 0 0 0 3 - Female 20 36 1 0 4 61 87.8 Total 23 36 1 0 4 64 87.8RURAL Male 8 14 0 0 0 22 100.0 Female 438 346 4 4 61 853 83.4 Total 446 360 4 4 61 875 83.9Kilifi Male 2 1 0 0 0 3 100.0 Female 32 45 0 0 3 80 93.8 Total 34 46 0 0 3 83 93.9Nyandarua Male 0 1 0 0 0 1 100.0 Female 82 36 1 1 4 124 85.7 Total 82 37 1 1 4 125 86.0Machakos Male 3 0 0 0 0 3 - Female 89 55 2 0 41 187 56.1 Total 92 55 2 0 41 190 56.1Uasin Gishu Male 1 0 0 0 0 1 -
99
SEX None Government KHA Montessori Other Total % trained by Government
Female 25 29 0 0 4 58 87.9 Total 26 29 0 0 4 59 87.9Nakuru Male 1 1 0 0 0 2 100.0 Female 91 74 0 1 7 173 90.2 Total 92 75 0 1 7 175 90.4Kericho Female 51 24 1 0 1 77 92.3Narok Male 1 3 0 0 0 4 100.0 Female 37 17 0 0 0 54 100.0 Total 38 20 0 0 0 58 100.0Kakamega Male 2 0 0 0 0 2 - Female 92 88 6 2 15 203 79.3 Total 94 88 6 2 15 205 79.3Kisumu Male 0 1 0 0 0 1 100.0 Female 29 51 0 2 1 83 94.4 Total 29 52 0 2 1 84 94.5Garissa Male 0 7 0 0 0 7 100.0 Female 2 15 0 0 0 17 100.0 Total 2 22 0 0 0 24 100.0TOTAL Male 27 16 0 1 4 48 76.2 Female 634 633 42 67 144 1520 71.4 Total 661 649 42 68 148 1568 71.6 Note: KHA stands for “The Kindergarten Headmistresses Association”.
100
Table 37: Distribution of Pre-School Teachers by ECCD Training and Year of Completion, 1995 Training
Programme Year of Completion Total
(excluding Not Stated)
Total excluding
Not Stated (%)
Not Stated
1960-1984
1985-1989
1990-1994
1995+ Total
MAJOR URBAN
167 73 58 132 43 473 306 100.0
None 138 0 0 0 0 138 0 0.0 Government 8 40 31 83 29 191 183 59.8 KHA 5 4 5 15 0 29 24 7.8 Montessori 10 9 11 21 8 59 49 16.0 Other 6 20 11 13 6 56 50 16.3OTHER URBAN
84 26 25 72 16 223 139 100.0
Not Stated 3 0 0 0 0 3 0 0.0 None 77 0 0 0 0 77 0 0.0 Government 3 10 15 56 14 98 95 68.3 KHA 0 3 3 3 0 9 9 6.5 Montessori 0 2 0 1 2 5 5 3.6 Other 1 11 7 12 0 31 30 21.6RURAL 569 104 92 223 96 1084 515 100.0 Not Stated 4 0 0 0 0 4 0 0.0 None 540 0 0 0 0 540 0 0.0 Government 22 63 79 195 89 448 426 82.7 KHA 1 3 1 5 0 10 9 1.7 Montessori 0 4 1 1 0 6 6 1.2 Other 2 34 11 22 7 76 74 14.4TOTAL 820 203 175 427 155 1780 960 TOTAL (excluding not stated)
813 203 175 427 155 1773 960 100.0
Not Stated 7 0 0 0 0 7 0 0.0 None 755 0 0 0 0 755 0 0.0 Government 33 113 125 334 132 737 704 73.3 KHA 6 10 9 23 0 48 42 4.4 Montessori 10 15 12 23 10 70 60 6.3 Other 9 65 29 47 13 163 154 16.0 Note: KHA stands for “The Kindergarten Headmistresses Association”.
101
Table 38: Distribution of Pre-School Teachers by Training Status, 1995 Number % Trained Untrained Total Trained Untrained Total MAJOR URBAN 266 207 473 56.2 43.8 100.0Mombasa 82 59 141 58.2 41.8 100.0Nairobi 184 148 332 55.4 44.6 100.0OTHER URBAN 105 118 223 47.1 52.9 100.0Thika 9 9 18 50.0 50.0 100.0Nakuru 38 29 67 56.7 43.3 100.0Eldoret 12 36 48 25.0 75.0 100.0Kitale 13 11 24 54.2 45.8 100.0Kisumu 33 33 66 50.0 50.0 100.0RURAL 356 728 1,084 32.8 67.2 100.0Kilifi 40 43 83 48.2 51.8 100.0Nyandarua 30 95 125 24.0 76.0 100.0Machakos 37 153 190 19.5 80.5 100.0Uasin Gishu 28 31 59 47.5 52.5 100.0Nakuru 56 119 175 32.0 68.0 100.0Kericho 22 55 77 28.6 71.4 100.0Narok 16 44 60 26.7 73.3 100.0Kakamega 70 137 207 33.8 66.2 100.0Kisumu 38 46 84 45.2 54.8 100.0Garissa 19 5 24 79.2 20.8 100.0TOTAL 727 1053 1780 40.8 59.2 100.0 Table 39: Distribution of Trained Teachers by Training Programme, 1995 Number % Government KHA Montessori Other Total Government KHA Montessori Other TotalMAJOR URBAN
170 23 45 28 266 63.9 8.6 16.9 10.5 100.0
Mombasa 62 3 15 2 82 75.6 3.7 18.3 2.4 100.0Nairobi 108 20 30 26 184 58.7 10.9 16.3 14.1 100.0OTHER URBAN
82 4 5 14 105 78.1 3.8 4.8 13.3 100.0
Thika 9 0 0 0 9 100.0 0.0 0.0 0.0 100.0Nakuru 20 3 4 11 38 52.6 7.9 10.5 28.9 100.0Eldoret 8 1 1 2 12 66.7 8.3 8.3 16.7 100.0Kitale 13 0 0 0 13 100.0 0.0 0.0 0.0 100.0Kisumu 32 0 0 1 33 97.0 0.0 0.0 3.0 100.0RURAL 330 5 1 20 356 92.7 1.4 0.3 5.6 100.0Kilifi 39 0 0 1 40 97.5 0.0 0.0 2.5 100.0Nyandarua 25 1 1 3 30 83.3 3.3 3.3 10.0 100.0Machakos 31 0 0 6 37 83.8 0.0 0.0 16.2 100.0Uasin Gishu
27 0 0 1 28 96.4 0.0 0.0 3.6 100.0
Nakuru 54 0 0 2 56 96.4 0.0 0.0 3.6 100.0Kericho 20 1 0 1 22 90.9 4.5 0.0 4.5 100.0Narok 16 0 0 0 16 100.0 0.0 0.0 0.0 100.0Kakamega 61 3 0 6 70 87.1 4.3 0.0 8.6 100.0Kisumu 38 0 0 0 38 100.0 0.0 0.0 0.0 100.0Garissa 19 0 0 0 19 100.0 0.0 0.0 0.0 100.0TOTAL 582 32 51 62 727 80.1 4.4 7.0 8.5 100.0Note: KHA stands for “The Kindergarten Headmistresses Association”.
102
Table 40: Distribution of Weighted Number of Teachers by Training Status, 1995 Survey Data Official Statistics Trained Untrained Total Trained Untrained Total MAJOR URBAN 2,021 1,574 3,595 1,488 1,666 3,154Mombasa 605 436 1,041 314 491 805Nairobi 1,416 1,139 2,554 1,174 1,175 2,349OTHER URBAN 712 817 1,529 596 743 1,339Thika 64 64 129 83 43 126Nakuru 253 193 445 127 243 370Eldoret 89 268 357 44 206 250Kitale 89 75 165 98 87 185Kisumu 217 217 433 244 164 408RURAL 2,374 4,954 7,328 - - -Kilifi 293 315 608 232 354 586Nyandarua 202 640 842 127 497 624Machakos 246 1,016 1,261 619 525 1,144Uasin Gishu 202 223 425 203 196 399Nakuru 394 838 1,232 306 792 1,098Kericho 148 371 519 135 445 580Narok 102 279 381 - - -Kakamega 473 926 1,399 359 855 1,214Kisumu 279 338 616 362 230 592Garissa 35 9 45 - - -
103
Table 41: Mean Years of Teaching Experience for Pre-School Teachers, 1995 In Pre-
School ECCD-Related
Other Teaching Experience
Total Teaching Experience
MAJOR URBAN 4.77 6.64 1.32 7.96Mombasa 4.48 7.48 .38 7.86Nairobi 4.89 6.29 1.71 8.00OTHER URBAN
3.85 6.34 .36 6.70
Thika 7.85 8.89 .00 8.89Nakuru 2.76 6.26 .77 7.03Eldoret 3.20 4.36 .21 4.57Kitale 4.13 6.33 .00 6.33Kisumu 4.20 7.14 .29 7.42RURAL 5.70 6.81 .44 7.25Kilifi 5.60 6.43 .00 6.43Nyandarua 3.81 4.25 .94 5.19Machakos 8.61 9.24 .37 9.62Uasin Gishu 5.27 6.21 .16 6.36Nakuru 4.35 6.04 .25 6.29Kericho 5.54 6.31 .58 6.90Narok 4.53 4.98 .68 5.67Kakamega 6.46 7.89 .60 8.49Kisumu 5.64 7.81 .29 8.10Garissa 1.99 3.83 .08 3.92 Table 42: Pre-School Pupil-Teacher Ratios, 1995 Pupil-Teacher Ratio MAJOR URBAN 21.7Mombasa 20.3Nairobi 22.2OTHER URBAN 24.9Thika 23.7Nakuru 22.5Eldoret 24.7Kitale 22.7Kisumu 27.8RURAL 36.6Kilifi 46.9Nyandarua 32.4Machakos 30.2Uasin Gishu 43.4Nakuru 39.1Kericho 39.4Narok 27.2Kakamega 37.3Kisumu 38.2Garissa 46.8
104
Table 43: Pre-Schools’ Pupil-Teacher Ratios by Sponsor, 1995 Sponsor Pupil-Teacher Ratio MAJOR URBAN 21.7Community 23.4Religious organization 24.3Private 20.8Local Authority 15.5Other 16.9OTHER URBAN 24.9Community 25.2Religious organization 23.4Private 25.9Local Authority 28.8Other 16.8RURAL 36.6Community 37.8Religious organization 29.9Private 27.0Local Authority 34.5Other 39.3 Table 44: Distribution of Pre-Schools by Receipt of Grants/Aid, 1994 Number % Received Didn’t Receive Total Received Didn’t Receive MAJOR URBAN 5 117 122 4.1 95.9Mombasa 3 31 34 8.8 91.2Nairobi 2 86 88 2.3 97.7OTHER URBAN 8 62 70 11.4 88.6Thika 1 6 7 14.3 85.7Nakuru 1 16 17 5.9 94.1Eldoret 4 12 16 25.0 75.0Kitale 0 7 7 0.0 100.0Kisumu 2 21 23 8.7 91.3RURAL 58 616 674 8.6 91.4Kilifi 3 47 50 6.0 94.0Nyandarua 9 66 75 12.0 88.0Machakos 17 121 138 12.3 87.7Uasin Gishu 3 42 45 6.7 93.3Nakuru 4 91 95 4.2 95.8Kericho 5 49 54 9.3 90.7Narok 4 33 37 10.8 89.2Kakamega 8 96 104 7.7 92.3Kisumu 4 58 62 6.5 93.5Garissa 1 13 14 7.1 92.9TOTAL 71 795 866 8.2 91.8
105
Table 45: Grants/Aid Received per Pre-School by Source (Shs), 1994 Central
Government Local
Authority Community Religious
organization Companies/
Estates NGO Other Total per pre-
school Number of
Centres Grand Total
(1) (2) (3) (4) (5) (6) (7) (8) (9) 8*9 MAJOR URBAN
0 0 0 4,000 44,000 40 6,505 54,545 5 272,725
Mombasa 0 0 0 0 73,333 67 2,509 75,909 3 227,727 Nairobi 0 0 0 10,000 0 0 12,500 22,500 2 45,000 OTHER URBAN
0 0 625 358,718 13,750 6,250 0 379,343 8 3,034,744
Thika 0 0 0 0 0 50,000 0 50,000 1 50,000 Nakuru 0 0 0 1,394,246 0 0 0 1,394,246 1 1,394,246 Eldoret 0 0 1,250 366,375 0 0 0 367,625 4 1,470,500 Kitale 0 Kisumu 0 0 0 5,000 55,000 0 0 60,000 2 120,000 RURAL 0 2,294 22,793 1,759 236 10,193 6,310 43,587 58 2,528,046 Kilifi 0 0 500 0 667 5,900 0 7,067 3 21,201 Nyandarua 0 2,756 5,000 3,457 0 1,667 0 12,879 9 115,911 Machakos 0 528 9,397 0 229 647 0 10,802 17 183,634 Uasin Gishu 0 13,000 1,700 0 1,667 0 0 16,367 3 49,101 Nakuru 0 0 245,486 0 0 0 0 245,486 4 981,944 Kericho 0 60 6,961 0 230 98,240 43,200 148,691 5 743,455 Narok 0 5,000 18,124 2,250 0 0 37,500 62,874 4 251,496 Kakamega 0 5,000 1,163 6,381 56 0 0 12,600 8 100,800 Kisumu 0 0 3,030 2,723 300 13,750 0 19,803 4 79,212 Garissa 0 0 0 0 0 1,280 0 1,280 1 1,280
106
Table 46(a): Annual Operating Costs per Pre-School by Main Source of Funding (Shs), 1994 Central
Government Community/ School
Levies Religious
organization Companies/
Estates Local
Authority NGO Other Not
Specified* Total
MAJOR URBAN 6,704 155,356 18,342 31,729 40,174 4,677 3,779 44,442 305,203 Mombasa 20,175 171,733 11,201 53,906 20,474 6,840 7,926 0 292,255 Nairobi 756 148,125 21,495 21,936 48,872 3,722 1,948 64,066 310,921 OTHER URBAN
0 111,578 4,957 2,947 6,076 983 3,455 7,998 137,993
Thika 0 54,431 0 2,703 9,600 8,703 0 25,552 100,988 Nakuru 0 196,806 13,412 9,398 5,294 0 0 0 224,910 Eldoret 0 108,836 4,025 308 3,077 0 0 0 116,245 Kitale 0 84,351 0 0 10,596 0 0 0 94,948 Kisumu 0 65,877 1,500 0 5,853 0 11,900 17,611 102,741 RURAL 308 20,191 297 1,303 8,132 332 217 483 31,263 Kilifi 0 16,348 375 2,236 21,273 0 271 0 40,502 Nyandarua 0 24,453 855 0 184 203 0 0 25,695 Machakos 0 16,086 5 296 3,326 80 53 968 20,815 Uasin Gishu 0 15,398 0 22 10,303 0 2 0 25,725 Nakuru 0 25,798 0 2,241 8,637 0 321 653 37,650 Kericho 0 19,805 222 6 5,187 0 194 336 25,750 Narok 0 8,264 847 0 29,462 63 0 0 38,636 Kakamega 96 35,730 102 4,173 7,430 0 160 1,088 48,778 Kisumu 3,281 2,977 491 1,959 8,909 1,579 87 0 19,283 Garissa 0 31,144 2,650 0 8,700 7,750 4,990 0 55,234 TOTAL 7,012 287,125 23,596 35,979 54,382 5,992 7,451 52,923 474,459 * = “Not Specified” is a balancing item, which is the difference between the total stated operating costs and the total funding identified by source.
107
Table 46(b): Percentage Distribution of Annual Operating Costs per Pre-School by Main Source of Funding, 1994 Central Government Community/ School Levies Religious organization Companies/ Estates Local Authority NGO Other Not Specified* Total MAJOR URBAN 2.6 62.1 8.8 7.4 9.3 1.0 1.0 7.6 100.0 Mombasa 5.8 73.6 7.9 7.4 4.5 0.4 0.4 0.0 100.0 Nairobi 1.2 57.1 9.2 7.4 11.5 1.3 1.3 11.0 100.0 OTHER URBAN 0.0 78.5 3.7 3.4 7.4 0.4 2.8 4.0 100.0 Thika 0.0 67.6 0.0 13.4 8.0 3.3 0.0 7.7 100.0 Nakuru 0.0 82.4 5.9 5.9 5.9 0.0 0.0 0.0 100.0 Eldoret 0.0 88.3 2.8 1.2 7.7 0.0 0.0 0.0 100.0 Kitale 0.0 85.7 0.0 0.0 14.3 0.0 0.0 0.0 100.0 Kisumu 0.0 69.2 5.0 0.0 5.6 0.0 9.5 10.8 100.0 RURAL 0.8 77.3 1.1 2.1 15.9 0.4 0.8 1.5 100.0 Kilifi 0.0 68.3 2.2 4.1 24.1 0.0 1.4 0.0 100.0 Nyandarua 0.0 96.5 3.1 0.0 0.4 0.1 0.0 0.0 100.0 Machakos 0.0 89.9 0.0 1.4 5.7 0.3 0.3 2.4 100.0 Uasin Gishu 0.0 66.2 0.0 0.1 33.6 0.0 0.0 0.0 100.0 Nakuru 0.0 79.6 0.0 6.7 11.7 0.0 0.9 1.1 100.0 Kericho 0.0 88.0 0.5 0.1 9.3 0.0 0.2 1.9 100.0 Narok 0.0 36.1 3.3 0.0 60.4 0.2 0.0 0.0 100.0 Kakamega 1.3 74.5 0.8 1.5 16.1 0.0 1.3 4.5 100.0 Kisumu 7.0 54.9 1.3 4.0 28.9 1.6 2.3 0.0 100.0 Garissa 0.0 62.3 8.3 0.0 11.8 11.5 6.1 0.0 100.0 TOTAL 1.5 60.5 5.0 7.6 11.5 1.3 1.6 11.2 100.0 * = “Not Specified” is a balancing item, which is the difference between the total stated operating costs and the total funding identified by source.
108
Table 47(a): Distribution of Operating Costs (Shs) Per Pre-School by Main Expenditure Item, 1994 Teachers’ Salaries Other Workers’ Salaries Food Transport Teaching Materials Utilities Other Total MAJOR URBAN 171,644 31,632 44,234 6,510 12,730 30,315 8,139 305,203 Mombasa 179,745 17,911 41,050 441 13,096 19,016 20,996 292,255 Nairobi 168,067 37,691 45,640 9,189 12,568 35,304 2,462 310,921 OTHER URBAN 71,356 15,821 19,229 1,806 6,300 10,684 12,797 137,993 Thika 60,955 7,314 18,743 0 1,823 725 11,429 100,988 Nakuru 116,895 36,801 18,713 876 11,990 25,500 14,134 224,910 Eldoret 51,863 5,533 37,942 3,316 8,608 6,219 2,765 116,245 Kitale 46,466 14,014 17,657 0 2,782 5,143 8,886 94,948 Kisumu 56,149 7,448 7,000 3,000 2,367 5,944 20,833 102,741 RURAL 23,508 1,695 3,307 341 1,526 542 391 31,311 Kilifi 36,143 1,282 2,295 0 616 134 32 40,502 Nyandarua 19,081 778 1,473 2,514 1,311 405 132 25,695 Machakos 16,626 711 981 47 996 240 1,215 20,815 Uasin Gishu 18,213 1,315 4,333 480 968 171 244 25,725 Nakuru 31,811 2,132 1,903 3 1,233 364 202 37,650 Kericho 19,257 1,048 4,001 0 1,233 185 26 25,750 Narok 36,501 0 0 19 1,070 1,047 0 38,636 Kakamega 25,733 4,241 12,032 0 4,498 1,947 327 48,778 Kisumu 16,977 429 1,650 0 562 0 0 19,618 Garissa 38,025 12,763 390 100 1,607 1,450 900 55,234
109
Table 47(b): Percentage Distribution of Operating Costs per Pre-School by Main Expenditure Item, 1994 Teachers’ Salaries Other Workers’ Salaries Food Transport Teaching Materials Utilities Other Total MAJOR URBAN 56.2 10.4 14.5 2.1 4.2 9.9 2.7 100.0 Mombasa 61.5 6.1 14.0 0.2 4.5 6.5 7.2 100.0 Nairobi 54.1 12.1 14.7 3.0 4.0 11.4 0.8 100.0 OTHER URBAN 51.7 11.5 13.9 1.3 4.6 7.7 9.3 100.0 Thika 60.4 7.2 18.6 0.0 1.8 0.7 11.3 100.0 Nakuru 52.0 16.4 8.3 0.4 5.3 11.3 6.3 100.0 Eldoret 44.6 4.8 32.6 2.9 7.4 5.3 2.4 100.0 Kitale 48.9 14.8 18.6 0.0 2.9 5.4 9.4 100.0 Kisumu 54.7 7.2 6.8 2.9 2.3 5.8 20.3 100.0 RURAL 75.1 5.4 10.6 1.1 4.9 1.7 1.3 100.0 Kilifi 89.2 3.2 5.7 0.0 1.5 0.3 0.1 100.0 Nyandarua 74.3 3.0 5.7 9.8 5.1 1.6 0.5 100.0 Machakos 79.9 3.4 4.7 0.2 4.8 1.2 5.8 100.0 Uasin Gishu 70.8 5.1 16.8 1.9 3.8 0.7 1.0 100.0 Nakuru 84.5 5.7 5.1 0.0 3.3 1.0 0.5 100.0 Kericho 74.8 4.1 15.5 0.0 4.8 0.7 0.1 100.0 Narok 94.5 0.0 0.0 0.0 2.8 2.7 0.0 100.0 Kakamega 52.8 8.7 24.7 0.0 9.2 4.0 0.7 100.0 Kisumu 86.5 2.2 8.4 0.0 2.9 0.0 0.0 100.0 Garissa 68.8 23.1 0.7 0.2 2.9 2.6 1.6 100.0
110
Table 48(a): Distribution of Operating Costs (Shs) per Child by Main Expenditure Item, 1994 Teachers’
Salaries Other Workers’
Salaries Food Transport Teaching
Materials Utilities Other Total Operating costs less
fees Ratio of operating costs to
fees MAJOR URBAN
2,331 453 639 91 188 478 365 4,545
Mombasa 2,235 395 784 6 237 717 1,132 5,507 926 1.20 Nairobi 2,371 478 576 128 167 376 37 4,133 (778) 0.84 OTHER URBAN
973 204 247 32 66 105 179 1,805
Thika 1,643 230 708 0 36 12 519 3,149 1,860 2.44 Nakuru 1,453 344 240 11 124 221 147 2,539 (1,267) 0.67 Eldoret 456 42 199 32 52 43 37 859 (1,087) 0.44 Kitale 652 310 140 0 36 30 63 1,231 (322) 0.79 Kisumu 756 138 152 79 45 104 223 1,497 (506) 0.75 RURAL 459 32 57 6 25 11 11 600 Kilifi 482 11 30 0 11 1 1 535 (6) 0.99 Nyandarua 372 12 22 32 29 6 3 475 (365) 0.57 Machakos 435 16 27 1 28 6 40 553 10 1.02 Uasin Gishu 394 75 213 21 34 10 8 755 369 1.96 Nakuru 543 37 28 0 22 8 3 641 102 1.19 Kericho 385 45 59 0 20 6 0 515 (312) 0.62 Narok 986 0 0 2 24 20 0 1,031 339 1.49 Kakamega 372 59 120 0 30 34 4 618 (151) 0.80 Kisumu 424 10 68 0 14 0 0 516 250 1.94 Garissa 512 169 9 1 20 18 11 740 82 1.12 Note: Mean fees per pre-school child are extracted from Statistical Appendix Table 28.
111
Table 48(b): Percentage Distribution of Operating Costs per Child by Main Expenditure Item, 1994 Teachers’ Salaries Other Workers’ Salaries Food Transport Teaching Materials Utilities Other Total MAJOR URBAN 51.3 10.0 14.0 2.0 4.1 10.5 8.0 100.0 Mombasa 40.6 7.2 14.2 0.1 4.3 13.0 20.6 100.0 Nairobi 57.4 11.6 13.9 3.1 4.0 9.1 0.9 100.0 OTHER URBAN 53.9 11.3 13.7 1.8 3.6 5.8 9.9 100.0 Thika 52.2 7.3 22.5 0.0 1.1 0.4 16.5 100.0 Nakuru 57.2 13.5 9.5 0.4 4.9 8.7 5.8 100.0 Eldoret 53.1 4.9 23.1 3.7 6.0 5.0 4.3 100.0 Kitale 53.0 25.2 11.4 0.0 2.9 2.4 5.2 100.0 Kisumu 50.5 9.2 10.2 5.3 3.0 6.9 14.9 100.0 RURAL 76.5 5.4 9.6 0.9 4.1 1.8 1.8 100.0 Kilifi 90.0 2.1 5.6 0.0 2.1 0.1 0.1 100.0 Nyandarua 78.3 2.4 4.6 6.7 6.0 1.3 0.7 100.0 Machakos 78.7 2.9 4.8 0.3 5.1 1.1 7.2 100.0 Uasin Gishu 52.2 9.9 28.3 2.8 4.5 1.4 1.0 100.0 Nakuru 84.8 5.7 4.3 0.0 3.5 1.2 0.4 100.0 Kericho 74.6 8.8 11.4 0.0 3.9 1.2 0.1 100.0 Narok 95.6 0.0 0.0 0.2 2.3 1.9 0.0 100.0 Kakamega 60.1 9.5 19.3 0.0 4.9 5.5 0.6 100.0 Kisumu 82.2 1.8 13.1 0.0 2.8 0.0 0.0 100.0 Garissa 69.1 22.9 1.2 0.2 2.7 2.4 1.5 100.0
112
Table 49: Current Market Value (Shs) per Pre-School by Source of Funding, 1995 Community Local
Authority Religious
organization NGO Private Company/
individual Companies/
Estates Other
Sources Not
Specified* Total
MAJOR URBAN 303,246 217,624 620,306 108 452,570 0 19,718 593,599 2,207,171 Mombasa 598,468 101,074 1,097,036 343 836,429 0 12,647 921,581 3,567,577 Nairobi 167,604 271,174 401,268 0 276,201 0 22,967 442,905 1,582,119 OTHER URBAN
207,991 22,683 271,376 0 298,774 0 53,070 75,899 929,793
Thika 113,750 28,571 21,429 0 5,500 0 246,429 7,229 422,907 Nakuru 443,750 0 581,375 0 1,200,375 0 0 381,625 2,607,125 Eldoret 43,791 31,873 205,779 0 43,477 0 0 243 325,163 Kitale 981,529 596 67,571 0 107,143 0 185,714 0 1,342,554 Kisumu 3,148 30,655 341,787 0 276,064 0 0 55,432 707,085 RURAL 90,755 7,018 17,558 7,071 39,496 3,502 5,842 67,592 238,834 Kilifi 52,003 438 13,186 17,254 8,919 0 11,741 297,256 400,797 Nyandarua 31,220 7,595 7,840 0 0 0 28 147,923 194,605 Machakos 93,382 5,093 9,304 0 7,836 1,087 537 19,175 136,413 Uasin Gishu 129,757 756 10,400 0 27,323 289 0 18,891 187,416 Nakuru 129,357 25,920 19,252 0 38,995 6,167 20,009 30,569 270,270 Kericho 104,824 5,556 7,604 61,756 4,287 27,750 6,255 13,965 231,996 Narok 91,151 12,667 2,667 0 0 0 364 56,303 163,151 Kakamega 97,176 795 43,400 795 199,790 0 9,991 73,605 425,553 Kisumu 76,303 34 35,575 4,120 15,918 0 480 9,559 141,989 Garissa 138,000 0 0 0 0 0 0 417,550 555,550 * = “Not Specified” is a balancing item, which is the difference between the total stated current market value and the total funding identified by source.
113
Table 50: Current Market Value (Shs) per Attached Pre-School by Source of Funding, 1995 Community Local
Authority Religious
organization NGO Private Company/
individual Companies/
Estates Other
Sources Not
Specified Total
MAJOR URBAN 1,318,307 498,052 261,005 0 312,057 0 19,048 1,809,218 4,217,687 Mombasa 2,846,971 0 357,929 0 876,886 0 57,143 3,407,786 7,546,714 Nairobi 553,975 747,079 212,543 0 29,643 0 0 1,009,935 2,553,174 OTHER URBAN
543,788 36,579 200,139 0 72,500 0 65,000 61,133 979,138
Thika 120,725 100,000 50,000 0 0 0 0 0 270,725 Nakuru 1,775,000 0 0 0 350,000 0 0 1,500 2,126,500 Eldoret 72,175 60,000 2,500 0 0 0 0 80 134,755 Kitale 981,529 596 67,571 0 107,143 0 185,714 0 1,342,554 Kisumu 9,893 58,200 489,254 0 0 0 0 174,214 731,561 RURAL 107,381 6,713 9,601 9,497 46,169 3,542 7,329 65,376 255,608 Kilifi 63,412 600 13,237 23,663 274 0 16,103 325,159 442,447 Nyandarua 48,677 5,233 6,180 0 0 0 49 159,085 219,224 Machakos 110,771 4,493 4,091 0 55 0 23 10,803 130,237 Uasin Gishu 131,253 850 11,700 0 30,739 325 0 17,753 192,620 Nakuru 175,126 42,864 5,382 0 30,693 2,273 34,324 35,212 325,873 Kericho 119,259 0 217 72,496 0 32,577 7,332 14,518 246,398 Narok 100,919 13,778 0 0 0 0 444 54,955 170,096 Kakamega 106,262 875 25,957 875 219,769 0 10,991 68,498 433,227 Kisumu 97,808 38 11,080 2,203 20,753 0 698 14,100 146,678 Garissa 0 0 0 0 0 0 0 600 600 * = “Not Specified” is a balancing item, which is the difference between the total stated current market value and the total funding identified by source.
114
Table 51: Current Market Value (Shs) per Unattached Pre-School by Source of Funding, 1995 Community Local
Authority Religious
organization NGO Private Company/
individual Companies/
Estates Other
Sources Not
Specified Total
MAJOR URBAN 58,231 149,934 707,034 134 486,486 0 19,880 300,174 1,721,874 Mombasa 15,522 127,278 1,288,657 431 825,941 0 1,111 277,009 2,535,949 Nairobi 77,451 160,130 445,304 0 333,732 0 28,326 310,598 1,355,540 OTHER URBAN
26,479 15,172 309,883 0 421,084 0 46,622 83,881 903,120
Thika 110,960 0 10,000 0 7,700 0 345,000 10,120 483,780 Nakuru 0 0 775,167 0 1,483,833 0 0 508,333 2,767,333 Eldoret 38,630 26,759 242,739 0 51,382 0 0 273 359,783 Kitale Kisumu 0 17,800 272,969 0 404,893 0 0 0 695,662 RURAL 48,256 7,799 37,897 871 22,438 3,399 2,041 73,255 195,957 Kilifi 21,285 0 13,048 0 32,196 0 0 222,132 288,662 Nyandarua 7,004 10,871 10,142 0 0 0 0 132,440 160,457 Machakos 49,241 6,614 22,536 0 27,586 3,846 1,841 40,426 152,089 Uasin Gishu 117,790 0 0 0 0 0 0 28,000 145,790 Nakuru 85,578 9,713 32,520 0 46,936 9,891 6,317 26,129 217,084 Kericho 21,822 37,500 50,075 0 28,938 0 63 10,785 149,182 Narok 47,199 7,667 14,667 0 0 0 0 62,367 131,899 Kakamega 6,319 0 217,828 0 0 0 0 124,670 348,816 Kisumu 31,030 26 87,142 8,158 5,739 0 22 0 132,118 Garissa 184,000 0 0 0 0 0 0 556,533 740,533 * = “Not Specified” is a balancing item, which is the difference between the total stated current market value and the total funding identified by source.
115
Table 52: Current Market Value (Shs) per Pre-School, Excluding Land, by Source of Funding, 1995 Community Local
Authority Religious
organization NGO Private Company/
individual Companies/
Estates Other
Sources Not
Specified Total
MAJOR URBAN 184,585 118,723 414,533 109 135,537 0 5,884 334,222 1,193,593 Mombasa 333,762 6,956 545,919 343 148,194 0 882 490,787 1,526,842 Nairobi 115,105 170,779 353,340 0 129,643 0 8,213 261,301 1,038,381 OTHER URBAN
165,160 12,131 127,084 0 132,455 0 30,660 21,250 488,740
Thika 113,750 0 14,286 0 5,500 0 232,143 86 365,764 Nakuru 710,000 0 610,200 0 1,080,600 0 0 600 2,401,400 Eldoret 32,098 17,258 138,625 0 25,785 0 0 243 214,009 Kitale 560,100 596 24,714 0 0 0 0 0 585,411 Kisumu 3,298 19,733 76,634 0 59,210 0 0 53,310 212,184 RURAL 58,973 1,452 12,780 7,255 33,551 1,513 1,885 24,351 141,759 Kilifi 47,525 467 13,265 18,404 9,257 0 524 28,039 117,481 Nyandarua 21,038 0 3,838 0 0 0 29 70,936 95,840 Machakos 64,868 926 7,093 0 5,589 725 537 10,262 90,000 Uasin Gishu 72,646 756 1,733 0 13,323 0 0 12,613 101,072 Nakuru 67,837 5,373 12,531 0 23,745 625 4,101 14,605 128,816 Kericho 90,620 0 7,511 61,756 3,917 14,417 5,699 11,140 195,060 Narok 51,757 7,212 2,061 0 0 0 364 39,333 100,727 Kakamega 69,988 0 33,927 875 196,644 0 4,428 24,294 330,156 Kisumu 34,191 35 29,139 4,265 15,459 0 497 35 83,620 Garissa 93,000 0 0 0 0 0 0 367,550 460,550 * = “Not Specified” is a balancing item, which is the difference between the total stated current market value and the total funding identified by source.
116
Table 53: Current Market Value (Shs) per Unattached Pre-School, Excluding Land, by Source of Funding, 1995 Community Local
Authority Religious
organization NGO Private Company/
individual Companies/
Estates Other
Sources Not
Specified Total
MAJOR URBAN 47,281 87,143 478,767 135 150,573 0 7,320 197,304 968,523 Mombasa 15,522 8,759 668,731 431 144,459 0 1,111 104,898 943,912 Nairobi 61,814 123,014 391,834 0 153,371 0 10,162 239,591 979,786 OTHER URBAN
26,551 12,687 174,049 0 206,474 0 47,794 106 467,660
Thika 110,960 0 0 0 7,700 0 325,000 120 443,780 Nakuru 0 0 1,017,000 0 1,801,000 0 0 0 2,818,000 Eldoret 31,630 20,395 163,830 0 30,473 0 0 273 246,601 Kitale Kisumu 0 13,800 70,969 0 82,893 0 0 0 167,662 RURAL 33,030 1,415 23,809 891 16,012 891 2,088 36,134 114,269 Kilifi 17,683 0 13,636 0 34,046 0 0 25,102 90,467 Nyandarua 5,904 0 480 0 0 0 0 78,355 84,739 Machakos 38,446 1,229 14,715 0 19,637 2,564 1,841 21,015 99,448 Uasin Gishu 45,790 0 0 0 0 0 0 16,000 61,790 Nakuru 63,173 3,905 19,680 0 29,752 1,250 6,605 10,021 134,384 Kericho 3,697 0 50,075 0 26,438 0 63 9,223 89,494 Narok 12,199 4,333 11,333 0 0 0 0 62,367 90,233 Kakamega 4,444 0 89,703 0 0 0 0 47,170 141,316 Kisumu 17,872 26 70,458 8,158 4,792 0 22 0 101,329 Garissa 124,000 0 0 0 0 0 0 489,867 613,867 * = “Not Specified” is a balancing item, which is the difference between the total stated current market value and the total funding identified by source.
117
Table 54: Distribution of Pre-Schools by Whether has Bank Account and Main Sponsor, 1995 Community Religious Private Local
Authority Other Community Non-
Community Total Total
(%) MAJOR URBAN
Owns Account
9 16 20 8 1 9 45 54 44.6
No Bank Account
13 28 14 9 3 13 54 67
Mombasa Owns Account
2 5 6 1 0 2 12 14 41.2
No Bank Account
8 8 1 2 1 8 12 20
Nairobi Owns Account
7 11 14 7 1 7 33 40 46.0
No Bank Account
5 20 13 7 2 5 42 47
OTHER URBAN
Owns Account
9 10 8 2 2 9 22 31 44.3
No Bank Account
13 10 10 5 1 13 26 39
Thika Owns Account
2 0 1 0 0 2 1 3 42.9
No Bank Account
0 1 1 1 1 0 4 4
Nakuru Owns Account
2 2 3 2 2 2 9 11 64.7
No Bank Account
1 2 2 1 0 1 5 6
Eldoret Owns Account
3 3 0 0 0 3 3 6 37.5
No Bank Account
3 3 3 1 0 3 7 10
Kitale Owns Account
1 0 1 0 0 1 1 2 28.6
No Bank Account
3 1 0 1 0 3 2 5
Kisumu Owns Account
1 5 3 0 0 1 8 9 39.1
No Bank Account
6 3 4 1 0 6 8 14
RURAL Owns Account
56 8 9 18 1 56 36 92 13.7
No Bank Account
465 34 14 56 11 465 115 580
Kilifi Owns Account
4 0 0 3 0 4 3 7 14.3
No Bank Account
25 6 2 9 0 25 17 42
Nyandarua Owns Account
24 1 1 4 0 24 6 30 40.0
No Bank Account
39 6 0 0 0 39 6 45
Machakos Owns Account
3 1 2 0 0 3 3 6 4.3
No Bank Account
119 2 5 6 0 119 13 132
Uasin Gishu Owns Account
5 0 0 0 0 5 0 5 11.1
No Bank Account
39 0 1 0 0 39 1 40
Nakuru Owns Account
9 3 2 2 0 9 7 16 16.8
No Bank 61 6 3 5 4 61 18 79
118
Community Religious Private LocalAuthority
Other Community Non-Community
Total Total (%)
Account Kericho Owns
Account 6 0 0 0 1 6 1 7 13.0
No Bank Account
42 1 1 1 2 42 5 47
Narok Owns Account
1 0 1 7 0 1 8 9 25.0
No Bank Account
15 3 0 9 0 15 12 27
Kakamega Owns Account
2 1 2 1 0 2 4 6 5.8
No Bank Account
80 6 1 10 1 80 18 98
Kisumu Owns Account
0 2 0 1 0 0 3 3 4.8
No Bank Account
38 4 0 15 2 38 21 59
Garissa Owns Account
2 0 1 0 0 2 1 3 21.4
No Bank Account
7 0 1 1 2 7 4 11
TOTAL Owns Account
74 34 37 28 4 74 103 177 20.5
No Bank Account
491 72 38 70 15 491 195 686
Table 55: Distribution of Pre-Schools by School-Feeding Arrangements, 1995 Centres With % with
Feeding Source Source as % of
those with feeding arrangements
No Feeding
Feeding FromHome
ByCentre
WFP/NSFCK Other Total From Home
By Centre
MAJOR URBAN
7 115 94.3 45 59 1 10 122 39.1 51.3
Mombasa 5 29 85.3 10 15 0 4 34 34.5 51.7Nairobi 2 86 97.7 35 44 1 6 88 40.7 51.2OTHER URBAN
14 56 80.0 19 26 1 10 70 33.9 46.4
Thika 1 6 85.7 4 0 1 1 7 66.7 0.0Nakuru 1 16 94.1 4 11 0 1 17 25.0 68.8Eldoret 3 13 81.3 4 7 0 2 16 30.8 53.8Kitale 1 6 85.7 3 3 0 0 7 50.0 50.0Kisumu 8 15 65.2 4 5 0 6 23 26.7 33.3RURAL 161 513 76.1 355 88 19 51 674 69.2 17.2Kilifi 17 33 66.0 16 9 4 4 50 48.5 27.3Nyandarua 17 58 77.3 55 3 0 0 75 94.8 5.2Machakos 0 138 100.0 111 17 3 7 138 80.4 12.3Uasin Gishu
15 30 66.7 27 3 0 0 45 90.0 10.0
Nakuru 30 65 68.4 51 9 1 4 95 78.5 13.8Kericho 17 37 68.5 26 7 1 3 54 70.3 18.9Narok 8 29 78.4 22 1 1 5 37 75.9 3.4Kakamega 27 77 74.0 17 36 0 24 104 22.1 46.8Kisumu 28 34 54.8 28 3 0 3 62 82.4 8.8Garissa 2 12 85.7 2 0 9 1 14 16.7 0.0TOTAL 182 684 79.0 419 173 21 71 866 39.1 51.3Note: WFP/NSFCK stands for “World Food Programme/National School Feeding Council of Kenya”.
119
Table 56: Distribution of Pre-Schools by Feeding Times per Day, 1995 Feeding Times Number of Centres % MAJOR URBAN 1 66 57.4 2 32 27.8 3 17 14.8Mombasa 1 28 96.6 3 1 3.4Nairobi 1 38 44.2 2 32 37.2 3 16 18.6OTHER URBAN 1 50 89.3 2 3 5.4 3 3 5.4Thika 1 4 66.7 2 1 16.7 3 1 16.7Nakuru 1 15 93.8 3 1 6.3Eldoret 1 12 92.3 2 1 7.7Kitale 1 6 100.0Kisumu 1 13 86.7 2 1 6.7 3 1 6.7RURAL 1 484 94.3 2 25 4.9 3 4 0.8Kilifi 1 32 97.0 2 1 3.0Nyandarua 1 54 93.1 2 4 6.9Machakos 1 132 95.7 2 6 4.3Uasin Gishu 1 28 93.3 2 1 3.3 3 1 3.3Nakuru 1 59 90.8 2 5 7.7 3 1 1.5Kericho 1 36 97.3 3 1 2.7Narok 1 25 86.2 2 4 13.8Kakamega 1 73 94.8 2 4 5.2Kisumu 1 33 97.1 3 1 2.9Garissa 1 12 100.0TOTAL 1 600 87.7 2 60 8.8 3 24 3.5
120
Table 57: Distribution of Pre-Schools by Whether Prepare Food, 1995 Prepare Food Don’t Prepare Total Responses % Prepare Food MAJOR URBAN 66 4 70 94.3Mombasa 17 2 19 89.5Nairobi 49 2 51 96.1OTHER URBAN 33 4 37 89.2Thika 2 0 2 100.0Nakuru 11 1 12 91.7Eldoret 9 0 9 100.0Kitale 3 0 3 100.0Kisumu 8 3 11 72.7RURAL 145 13 158 91.8Kilifi 16 1 17 94.1Nyandarua 3 0 3 100.0Machakos 27 0 27 100.0Uasin Gishu 3 0 3 100.0Nakuru 12 2 14 85.7Kericho 9 2 11 81.8Narok 2 5 7 28.6Kakamega 58 2 60 96.7Kisumu 5 1 6 83.3Garissa 10 0 10 100.0TOTAL 244 21 265 92.1
121
Table 58: Distribution of Pre-Schools Which Prepare Food by Type of Cooking Fuel, 1995 Number % Firewood Charcoal Kerosene Gas Electricity Total Firewood Charcoal Kerosene Gas Electricity Total MAJOR URBAN 7 26 9 16 7 65 10.8 40.0 13.8 24.6 10.8 100.0 Mombasa 3 5 2 5 1 16 18.8 31.3 12.5 31.3 6.3 100.0 Nairobi 4 21 7 11 6 49 8.2 42.9 14.3 22.4 12.2 100.0 OTHER URBAN 12 15 2 1 3 33 36.4 45.5 6.1 3.0 9.1 100.0 Thika 2 0 0 0 0 2 100.0 0.0 0.0 0.0 0.0 100.0 Nakuru 4 2 2 1 2 11 36.4 18.2 18.2 9.1 18.2 100.0 Eldoret 2 7 0 0 0 9 22.2 77.8 0.0 0.0 0.0 100.0 Kitale 3 0 0 0 0 3 100.0 0.0 0.0 0.0 0.0 100.0 Kisumu 1 6 0 0 1 8 12.5 75.0 0.0 0.0 12.5 100.0 RURAL 126 15 2 2 0 145 86.9 10.3 1.4 1.4 0.0 100.0 Kilifi 13 2 0 1 0 16 81.3 12.5 0.0 6.3 0.0 100.0 Nyandarua 3 0 0 0 0 3 100.0 0.0 0.0 0.0 0.0 100.0 Machakos 22 3 2 0 0 27 81.5 11.1 7.4 0.0 0.0 100.0 Uasin Gishu 1 2 0 0 0 3 33.3 66.7 0.0 0.0 0.0 100.0 Nakuru 8 4 0 0 0 12 66.7 33.3 0.0 0.0 0.0 100.0 Kericho 9 0 0 0 0 9 100.0 0.0 0.0 0.0 0.0 100.0 Narok 2 0 0 0 0 2 100.0 0.0 0.0 0.0 0.0 100.0 Kakamega 57 1 0 0 0 58 98.3 1.7 0.0 0.0 0.0 100.0 Kisumu 3 1 0 1 0 5 60.0 20.0 0.0 20.0 0.0 100.0 Garissa 8 2 0 0 0 10 80.0 20.0 0.0 0.0 0.0 100.0 TOTAL 145 56 13 19 10 243 59.7 23.0 5.3 7.8 4.1 100.0
122
Table 59: Distribution of Pre-Schools by Receipt of Milk under School Milk Programme, 1995 Attached Not Attached Grand
Total Receive
Milk Don’t
Receive Total %
Receive Receive
Milk Don’t
Receive Total %
Receive MAJOR URBAN
7 18 25 28.0 0 97 97 0.0 122
Mombasa 1 6 7 14.3 0 27 27 0.0 34Nairobi 6 12 18 33.3 0 70 70 0.0 88OTHER URBAN
5 19 24 20.8 0 46 46 0.0 70
Thika 2 0 2 100.0 0 5 5 0.0 7Nakuru 0 4 4 0.0 0 13 13 0.0 17Eldoret 0 3 3 0.0 0 13 13 0.0 16Kitale 1 6 7 14.3 0 0 0 - 7Kisumu 2 6 8 25.0 0 15 15 0.0 23RURAL 82 402 484 16.9 4 186 190 2.1 674Kilifi 5 31 36 13.9 0 14 14 0.0 50Nyandarua 0 44 44 0.0 0 31 31 0.0 75Machakos 27 72 99 27.3 4 35 39 10.3 138Uasin Gishu 7 33 40 17.5 0 5 5 0.0 45Nakuru 1 44 45 2.2 0 50 50 0.0 95Kericho 17 29 46 37.0 0 8 8 0.0 54Narok 12 17 29 41.4 0 8 8 0.0 37Kakamega 9 87 96 9.4 0 8 8 0.0 104Kisumu 4 38 42 9.5 0 20 20 0.0 62Garissa 0 7 7 0.0 0 7 7 0.0 14TOTAL 94 439 533 17.6 4 329 333 1.2 866
123
Table 60: Distribution of Pre-Schools by Request for Immunization Records and Main Sponsor, 1995 Request
Immunization Card
Community Religious organization
Private Local Authority
Other Total % Request immunization
card MAJOR URBAN
Yes 19 38 24 14 4 99 81.1
No 4 6 10 3 0 23 Mombasa Yes 8 12 3 2 1 26 76.5 No 2 1 4 1 0 8 Nairobi Yes 11 26 21 12 3 73 83.0 No 2 5 6 2 0 15 OTHER URBAN
Yes 17 15 12 7 2 53 75.7
No 5 5 6 0 1 17 Thika Yes 1 1 0 1 0 3 42.9 No 1 0 2 0 1 4 Nakuru Yes 3 4 5 3 2 17 100.0Eldoret Yes 4 4 1 1 0 10 62.5 No 2 2 2 0 0 6 Kitale Yes 4 1 1 1 0 7 100.0Kisumu Yes 5 5 5 1 0 16 69.6 No 2 3 2 0 0 7 RURAL Yes 325 25 18 53 9 430 63.8 No 198 17 5 21 3 244 Kilifi Yes 20 5 0 10 0 35 70.0 No 10 1 2 2 0 15 Nyandarua Yes 32 5 1 1 0 39 52.0 No 31 2 0 3 0 36 Machakos Yes 93 2 6 5 0 106 76.8 No 29 1 1 1 0 32 Uasin Gishu
Yes 28 0 1 0 0 29 64.4
No 16 0 0 0 0 16 Nakuru Yes 41 4 4 7 4 60 63.2 No 29 5 1 0 0 35 Kericho Yes 37 1 1 1 1 41 75.9 No 11 0 0 0 2 13 Narok Yes 6 2 0 12 0 20 54.1 No 11 1 1 4 0 17 Kakamega Yes 47 4 3 5 0 59 56.7 No 35 3 0 6 1 45 Kisumu Yes 19 2 0 12 2 35 56.5 No 19 4 0 4 0 27 Garissa Yes 2 0 2 0 2 6 42.9 No 7 0 0 1 0 8 TOTAL Yes 361 78 54 74 15 582 67.2 No 207 28 21 24 4 284 Total 568 106 75 98 19 866
124
Table 61: Distribution of Pre-Schools by Action Taken on Children who are not Fully Immunized, 1995 Number % Not
Specified No
Action Refuse
Admission Admit/
Alert Total Not
Specified No
Action Refuse
Admission Admit/
Alert Refuse admission or
admit/ alert Total
MAJOR URBAN
3 41 7 71 119 2.5 34.5 5.9 59.7 65.5 100.0
Mombasa 1 14 3 16 33 3.0 42.4 9.1 48.5 57.6 100.0 Nairobi 2 27 4 55 86 2.3 31.4 4.7 64.0 68.6 100.0 OTHER URBAN
1 18 18 33 69 1.4 26.1 26.1 47.8 73.9 100.0
Thika 0 5 1 1 7 0.0 71.4 14.3 14.3 28.6 100.0 Nakuru 0 0 12 5 17 0.0 0.0 70.6 29.4 100.0 100.0 Eldoret 0 6 1 9 16 0.0 37.5 6.3 56.3 62.5 100.0 Kitale 0 0 3 4 7 0.0 0.0 42.9 57.1 100.0 100.0 Kisumu 1 7 1 14 22 4.5 31.8 4.5 63.6 68.2 100.0 RURAL 27 289 36 322 647 4.2 44.7 5.6 49.8 55.3 100.0 Kilifi 0 21 0 29 50 0.0 42.0 0.0 58.0 58.0 100.0 Nyandarua 3 45 1 26 72 4.2 62.5 1.4 36.1 37.5 100.0 Machakos 3 46 10 79 135 2.2 34.1 7.4 58.5 65.9 100.0 Uasin Gishu 2 16 5 22 43 4.7 37.2 11.6 51.2 62.8 100.0 Nakuru 3 43 5 44 92 3.3 46.7 5.4 47.8 53.3 100.0 Kericho 10 15 8 21 44 22.7 34.1 18.2 47.7 65.9 100.0 Narok 0 17 0 20 37 0.0 45.9 0.0 54.1 54.1 100.0 Kakamega 3 49 7 45 101 3.0 48.5 6.9 44.6 51.5 100.0 Kisumu 3 29 0 30 59 5.1 49.2 0.0 50.8 50.8 100.0 Garissa 0 8 0 6 14 0.0 57.1 0.0 42.9 42.9 100.0 TOTAL 31 348 61 426 835 3.7 41.7 7.3 51.0 58.3 100.0
125
Table 62(a): Distribution of Pre-Schools by Type of Health Interventions Undertaken, 1990-1995 Growth Monitoring Vitamin A Supplement Iron Supplement De-worming Eye Checkup Ear Checkup Other TotalMAJOR URBAN 68 35 32 53 53 48 24 122 Mombasa 14 2 2 2 3 3 1 34 Nairobi 54 33 30 51 50 45 23 88 OTHER URBAN 16 8 6 17 24 20 10 70 Thika 0 1 0 0 2 2 1 7 Nakuru 2 0 0 0 7 5 1 17 Eldoret 1 1 1 1 3 2 1 16 Kitale 5 5 5 6 5 5 2 7 Kisumu 8 1 0 10 7 6 5 23 RURAL 111 30 27 75 49 48 65 674 Kilifi 13 2 1 1 1 1 3 50 Nyandarua 9 0 0 1 1 1 5 75 Machakos 21 3 3 14 8 11 7 138 Uasin Gishu 3 1 1 1 1 1 7 45 Nakuru 3 2 1 3 2 1 3 95 Kericho 10 4 4 6 5 5 4 54 Narok 6 4 3 3 4 2 0 37 Kakamega 16 8 8 21 13 13 11 104 Kisumu 25 3 3 20 10 8 20 62 Garissa 5 3 3 5 4 5 5 14 TOTAL 195 73 65 145 126 116 99 866
126
Table 62(b): Percentage Distribution of Pre-Schools by Type of Health Interventions Undertaken, 1990-1995 Growth Monitoring Vitamin A Supplement Iron Supplement De-worming Eye Checkup Ear Checkup Other MAJOR URBAN 55.7 28.7 26.2 43.4 43.4 39.3 19.7 Mombasa 41.2 5.9 5.9 5.9 8.8 8.8 2.9 Nairobi 61.4 37.5 34.1 58.0 56.8 51.1 26.1 OTHER URBAN 22.9 11.4 8.6 24.3 34.3 28.6 14.3 Thika 0.0 14.3 0.0 0.0 28.6 28.6 14.3 Nakuru 11.8 0.0 0.0 0.0 41.2 29.4 5.9 Eldoret 6.3 6.3 6.3 6.3 18.8 12.5 6.3 Kitale 71.4 71.4 71.4 85.7 71.4 71.4 28.6 Kisumu 34.8 4.3 0.0 43.5 30.4 26.1 21.7 RURAL 16.5 4.5 4.0 11.1 7.3 7.1 9.6 Kilifi 26.0 4.0 2.0 2.0 2.0 2.0 6.0 Nyandarua 12.0 0.0 0.0 1.3 1.3 1.3 6.7 Machakos 15.2 2.2 2.2 10.1 5.8 8.0 5.1 Uasin Gishu 6.7 2.2 2.2 2.2 2.2 2.2 15.6 Nakuru 3.2 2.1 1.1 3.2 2.1 1.1 3.2 Kericho 18.5 7.4 7.4 11.1 9.3 9.3 7.4 Narok 16.2 10.8 8.1 8.1 10.8 5.4 0.0 Kakamega 15.4 7.7 7.7 20.2 12.5 12.5 10.6 Kisumu 40.3 4.8 4.8 32.3 16.1 12.9 32.3 Garissa 35.7 21.4 21.4 35.7 28.6 35.7 35.7 TOTAL 22.5 8.4 7.5 16.7 14.5 13.4 11.4
127
Table 63: Distribution of Pre-Schools by Distance to Nearest Health Facility in Kilometers, 1995 Number % <2 2-3 4-5 6-10 10+ Total <2 2-3 4-5 6-10 10+ Total MAJOR URBAN 91 23 7 1 0 122 74.6 18.9 5.7 0.8 0.0 100.0 Mombasa 29 4 1 0 0 34 85.3 11.8 2.9 0.0 0.0 100.0 Nairobi 62 19 6 1 0 88 70.5 21.6 6.8 1.1 0.0 100.0 OTHER URBAN 41 20 5 3 1 70 58.6 28.6 7.1 4.3 1.4 100.0 Thika 4 2 0 1 0 7 57.1 28.6 0.0 14.3 0.0 100.0 Nakuru 12 5 0 0 0 17 70.6 29.4 0.0 0.0 0.0 100.0 Eldoret 12 1 1 2 0 16 75.0 6.3 6.3 12.5 0.0 100.0 Kitale 1 4 2 0 0 7 14.3 57.1 28.6 0.0 0.0 100.0 Kisumu 12 8 2 0 1 23 52.2 34.8 8.7 0.0 4.3 100.0 RURAL 171 176 146 133 48 674 25.4 26.1 21.7 19.7 7.1 100.0 Kilifi 10 12 10 13 5 50 20.0 24.0 20.0 26.0 10.0 100.0 Nyandarua 14 21 26 10 4 75 18.7 28.0 34.7 13.3 5.3 100.0 Machakos 29 31 29 39 10 138 21.0 22.5 21.0 28.3 7.2 100.0 Uasin Gishu 8 12 10 7 8 45 17.8 26.7 22.2 15.6 17.8 100.0 Nakuru 38 20 17 16 4 95 40.0 21.1 17.9 16.8 4.2 100.0 Kericho 13 15 12 11 3 54 24.1 27.8 22.2 20.4 5.6 100.0 Narok 7 4 8 10 8 37 18.9 10.8 21.6 27.0 21.6 100.0 Kakamega 29 34 16 20 5 104 27.9 32.7 15.4 19.2 4.8 100.0 Kisumu 11 25 18 7 1 62 17.7 40.3 29.0 11.3 1.6 100.0 Garissa 12 2 0 0 0 14 85.7 14.3 0.0 0.0 0.0 100.0
128
Table 64: Distribution of Disabilities by Gender of the Disabled, 1995 Seeing Hearing Speaking Moving
Legs Moving Arms
Mental Handicap
Total disabilities Enrolment Total disabilities/ enrolment (%)
Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls Total Boys Girls Total MAJOR URBAN
0 3 3 2 4 6 5 3 0 1 4 7 16 22 38 4,617 4,747 9,364 0.406
Mombasa 0 1 3 1 1 2 1 1 0 0 1 0 6 5 11 1,510 1,342 2,852 0.386 Nairobi 0 2 0 1 3 4 4 2 0 1 3 7 10 17 27 3,107 3,405 6,512 0.415 OTHER URBAN
13 14 8 7 10 4 18 9 3 3 14 5 66 42 108 2,493 2,545 5,038 2.144
Thika 2 0 0 0 0 0 14 8 2 2 3 2 21 12 33 197 184 381 8.661 Nakuru 1 4 1 0 3 1 2 0 0 0 3 0 10 5 15 714 717 1,431 1.048 Eldoret 1 0 3 0 2 2 0 0 0 0 1 0 7 2 9 572 549 1,121 0.803 Kitale 4 2 1 1 2 1 1 0 1 0 3 2 12 6 18 280 263 543 3.315 Kisumu 5 8 3 6 3 0 1 1 0 1 4 1 16 17 33 730 832 1,562 2.113 RURAL 99 71 132 90 141 91 68 22 26 19 104 70 570 363 933 19,454 18,059 37,513 2.487 Kilifi 8 2 22 15 32 20 6 2 0 0 17 10 85 49 134 1,885 1,635 3,520 3.807 Nyandarua 7 1 1 3 8 6 5 1 2 3 10 7 33 21 54 2,060 1,837 3,897 1.386 Machakos 8 4 9 11 11 9 9 2 4 3 17 14 58 43 101 2,802 2,735 5,537 1.824 Uasin Gishu 7 5 7 2 3 2 2 0 2 0 1 4 22 13 35 1,187 1,211 2,398 1.460 Nakuru 15 16 17 16 21 11 8 2 3 1 21 8 85 54 139 3,259 3,059 6,318 2.200 Kericho 7 10 19 14 22 8 5 1 2 0 5 1 60 34 94 1,563 1,426 2,989 3.145 Narok 9 2 12 10 1 4 6 2 2 0 5 2 35 20 55 870 658 1,528 3.599 Kakamega 14 16 24 13 28 25 11 6 9 9 15 15 101 84 185 3,836 3,684 7,520 2.460 Kisumu 21 15 16 6 15 6 13 5 2 2 11 6 78 40 118 1,385 1,429 2,814 4.193 Garissa 3 0 5 0 0 0 3 1 0 1 2 3 13 5 18 607 385 992 1.815 TOTAL 112 88 143 99 155 101 91 34 29 23 122 82 652 427 1,079 26,564 25,351 51,915 2.078
129
Table 65: Distribution of Pre-Schools by Type of Premises, 1995 Number % Own/
rented Shared with
Primary
Church Local Authority
Hall
Parents/ Employer
Hall
Open Air
Other Total Own/ rented
Shared with
Primary
Church Local Authority
Hall
Parents/ Employer
Hall
Open Air
Other Total
MAJOR URBAN
89 6 19 4 3 0 1 122 73.0 4.9 15.6 3.3 2.5 0.0 0.8 100.0
Mombasa 25 1 5 2 0 0 1 34 73.5 2.9 14.7 5.9 0.0 0.0 2.9 100.0 Nairobi 64 5 14 2 3 0 0 88 72.7 5.7 15.9 2.3 3.4 0.0 0.0 100.0 OTHER URBAN
47 7 13 1 2 0 0 70 67.1 10.0 18.6 1.4 2.9 0.0 0.0 100.0
Thika 6 0 1 0 0 0 0 7 85.7 0.0 14.3 0.0 0.0 0.0 0.0 100.0 Nakuru 9 3 4 0 1 0 0 17 52.9 17.6 23.5 0.0 5.9 0.0 0.0 100.0 Eldoret 11 1 4 0 0 0 0 16 68.8 6.3 25.0 0.0 0.0 0.0 0.0 100.0 Kitale 5 0 1 0 1 0 0 7 71.4 0.0 14.3 0.0 14.3 0.0 0.0 100.0 Kisumu 16 3 3 1 0 0 0 23 69.6 13.0 13.0 4.3 0.0 0.0 0.0 100.0 RURAL 360 193 84 5 15 17 0 674 53.4 28.6 12.5 0.7 2.2 2.5 0.0 100.0 Kilifi 17 13 11 0 1 8 0 50 34.0 26.0 22.0 0.0 2.0 16.0 0.0 100.0 Nyandarua 63 6 5 0 1 0 0 75 84.0 8.0 6.7 0.0 1.3 0.0 0.0 100.0 Machakos 88 32 16 0 1 1 0 138 63.8 23.2 11.6 0.0 0.7 0.7 0.0 100.0 Uasin Gishu
23 15 6 0 0 1 0 45 51.1 33.3 13.3 0.0 0.0 2.2 0.0 100.0
Nakuru 61 8 17 4 5 0 0 95 64.2 8.4 17.9 4.2 5.3 0.0 0.0 100.0 Kericho 37 14 0 0 0 3 0 54 68.5 25.9 0.0 0.0 0.0 5.6 0.0 100.0 Narok 18 16 2 1 0 0 0 37 48.6 43.2 5.4 2.7 0.0 0.0 0.0 100.0 Kakamega 29 58 12 0 2 3 0 104 27.9 55.8 11.5 0.0 1.9 2.9 0.0 100.0 Kisumu 18 26 13 0 4 1 0 62 29.0 41.9 21.0 0.0 6.5 1.6 0.0 100.0 Garissa 6 5 2 0 1 0 0 14 42.9 35.7 14.3 0.0 7.1 0.0 0.0 100.0 TOTAL 496 206 116 10 20 17 1 866 57.3 23.8 13.4 1.2 2.3 2.0 0.1 100.0
130
Table 66: Distribution of Pre-Schools by Type of Roofing Material, 1995 Number % Not Stated Iron / Asbestos Sheet Tiles/concrete Grass/ Makuti Total Not Stated Iron / Asbestos Sheet Tiles/concrete Grass/ Makuti Total MAJOR URBAN 1 89 31 1 122 0.8 73.0 25.4 0.8 100.0 Mombasa 0 25 8 1 34 0.0 73.5 23.5 2.9 100.0 Nairobi 1 64 23 0 88 1.1 72.7 26.1 0.0 100.0 OTHER URBAN 0 62 8 0 70 0.0 88.6 11.4 0.0 100.0 Thika 0 6 1 0 7 0.0 85.7 14.3 0.0 100.0 Nakuru 0 13 4 0 17 0.0 76.5 23.5 0.0 100.0 Eldoret 0 15 1 0 16 0.0 93.8 6.3 0.0 100.0 Kitale 0 7 0 0 7 0.0 100.0 0.0 0.0 100.0 Kisumu 0 21 2 0 23 0.0 91.3 8.7 0.0 100.0 RURAL 5 611 8 33 657 0.8 93.0 1.2 5.0 100.0 Kilifi 0 28 1 13 42 0.0 66.7 2.4 31.0 100.0 Nyandarua 0 73 2 0 75 0.0 97.3 2.7 0.0 100.0 Machakos 1 127 2 7 137 0.7 92.7 1.5 5.1 100.0 Uasin Gishu 0 43 0 1 44 0.0 97.7 0.0 2.3 100.0 Nakuru 0 93 1 1 95 0.0 97.9 1.1 1.1 100.0 Kericho 0 48 1 2 51 0.0 94.1 2.0 3.9 100.0 Narok 1 36 0 0 37 2.7 97.3 0.0 0.0 100.0 Kakamega 1 95 1 4 101 1.0 94.1 1.0 4.0 100.0 Kisumu 2 56 0 3 61 3.3 91.8 0.0 4.9 100.0 Garissa 0 12 0 2 14 0.0 85.7 0.0 14.3 100.0 TOTAL 6 762 47 34 849 0.7 89.8 5.5 4.0 100.0
131
Table 67: Distribution of Pre-Schools by Type of Wall, 1995 Number % Not
Stated Stone/ Brick/
Block Wood Mud Iron
Sheet Grass/ Reeds
Total Not Stated
Stone/ Brick/ Block
Wood Mud Iron Sheet
Grass/ Reeds
Total
MAJOR URBAN
1 101 4 5 11 0 122 0.8 82.8 3.3 4.1 9.0 0.0 100.0
Mombasa 0 31 2 1 0 0 34 0.0 91.2 5.9 2.9 0.0 0.0 100.0 Nairobi 1 70 2 4 11 0 88 1.1 79.5 2.3 4.5 12.5 0.0 100.0 OTHER URBAN
0 41 8 18 3 0 70 0.0 58.6 11.4 25.7 4.3 0.0 100.0
Thika 0 5 1 0 1 0 7 0.0 71.4 14.3 0.0 14.3 0.0 100.0 Nakuru 0 12 1 3 1 0 17 0.0 70.6 5.9 17.6 5.9 0.0 100.0 Eldoret 0 7 5 4 0 0 16 0.0 43.8 31.3 25.0 0.0 0.0 100.0 Kitale 0 3 0 3 1 0 7 0.0 42.9 0.0 42.9 14.3 0.0 100.0 Kisumu 0 14 1 8 0 0 23 0.0 60.9 4.3 34.8 0.0 0.0 100.0 RURAL 5 310 138 197 6 1 657 0.8 47.2 21.0 30.0 0.9 0.2 100.0 Kilifi 0 28 0 14 0 0 42 0.0 66.7 0.0 33.3 0.0 0.0 100.0 Nyandarua 0 24 32 19 0 0 75 0.0 32.0 42.7 25.3 0.0 0.0 100.0 Machakos 1 110 1 24 1 0 137 0.7 80.3 0.7 17.5 0.7 0.0 100.0 Uasin Gishu 0 9 14 20 1 0 44 0.0 20.5 31.8 45.5 2.3 0.0 100.0 Nakuru 0 31 43 18 3 0 95 0.0 32.6 45.3 18.9 3.2 0.0 100.0 Kericho 0 22 22 6 1 0 51 0.0 43.1 43.1 11.8 2.0 0.0 100.0 Narok 1 6 20 10 0 0 37 2.7 16.2 54.1 27.0 0.0 0.0 100.0 Kakamega 1 46 1 53 0 0 101 1.0 45.5 1.0 52.5 0.0 0.0 100.0 Kisumu 2 23 5 31 0 0 61 3.3 37.7 8.2 50.8 0.0 0.0 100.0 Garissa 0 11 0 2 0 1 14 0.0 78.6 0.0 14.3 0.0 7.1 100.0 TOTAL 6 452 150 220 20 1 849 0.7 53.2 17.7 25.9 2.4 0.1 100.0
132
Table 68: Distribution of Pre-Schools by Type of Floor, 1995 Number % Not Stated Cement/ Concrete Earth Wood Tiles Total Not Stated Cement/ Concrete Earth Wood Tiles TotalMAJOR URBAN 1 112 5 0 4 122 0.8 91.8 4.1 0.0 3.3 100.0 Mombasa 0 32 1 0 1 34 0.0 94.1 2.9 0.0 2.9 100.0 Nairobi 1 80 4 0 3 88 1.1 90.9 4.5 0.0 3.4 100.0 OTHER URBAN 0 56 14 0 0 70 0.0 80.0 20.0 0.0 0.0 100.0 Thika 0 5 2 0 0 7 0.0 71.4 28.6 0.0 0.0 100.0 Nakuru 0 16 1 0 0 17 0.0 94.1 5.9 0.0 0.0 100.0 Eldoret 0 11 5 0 0 16 0.0 68.8 31.3 0.0 0.0 100.0 Kitale 0 6 1 0 0 7 0.0 85.7 14.3 0.0 0.0 100.0 Kisumu 0 18 5 0 0 23 0.0 78.3 21.7 0.0 0.0 100.0 RURAL 5 302 335 12 3 657 0.8 46.0 51.0 1.8 0.5 100.0 Kilifi 0 26 16 0 0 42 0.0 61.9 38.1 0.0 0.0 100.0 Nyandarua 0 25 46 4 0 75 0.0 33.3 61.3 5.3 0.0 100.0 Machakos 1 80 55 0 1 137 0.7 58.4 40.1 0.0 0.7 100.0 Uasin Gishu 0 26 16 2 0 44 0.0 59.1 36.4 4.5 0.0 100.0 Nakuru 0 36 55 4 0 95 0.0 37.9 57.9 4.2 0.0 100.0 Kericho 0 29 21 1 0 51 0.0 56.9 41.2 2.0 0.0 100.0 Narok 1 11 25 0 0 37 2.7 29.7 67.6 0.0 0.0 100.0 Kakamega 1 38 60 1 1 101 1.0 37.6 59.4 1.0 1.0 100.0 Kisumu 2 18 40 0 1 61 3.3 29.5 65.6 0.0 1.6 100.0 Garissa 0 13 1 0 0 14 0.0 92.9 7.1 0.0 0.0 100.0 TOTAL 6 470 354 12 7 849 0.7 55.4 41.7 1.4 0.8 100.0
133
Table 69: Distribution of Pre-Schools by Type of Wall and Roof, 1995 Wall Roof Roof (%) Wall
(%) Not
Stated Iron / Asbestos
Sheet Tiles/concrete Grass/
Makuti Total Not
Stated Iron / Asbestos
Sheet Tiles/concrete Grass/
Makuti MAJOR URBAN
Not Stated 1 0 0 0 1 100.0 0.0 0.0 0.0 0.8
Stone/Brick/Block 0 71 30 0 101 0.0 70.3 29.7 0.0 82.8 Wood 0 3 0 1 4 0.0 75.0 0.0 25.0 3.3 Mud 0 5 0 0 5 0.0 100.0 0.0 0.0 4.1 Iron Sheets 0 10 1 0 11 0.0 90.9 9.1 0.0 9.0 Grass/Reeds 0 0 0 0 0 0.0 OTHER URBAN
Not Stated 0 0 0 0 0 0.0
Stone/Brick/Block 0 33 8 0 41 0.0 80.5 19.5 0.0 58.6 Wood 0 8 0 0 8 0.0 100.0 0.0 0.0 11.4 Mud 0 18 0 0 18 0.0 100.0 0.0 0.0 25.7 Iron Sheets 0 3 0 0 3 0.0 100.0 0.0 0.0 4.3 Grass/Reeds 0 0 0 0 0 0.0 RURAL Not Stated 5 0 0 0 5 100.0 0.0 0.0 0.0 7.1 Stone/Brick/Block 0 299 7 4 310 0.0 96.5 2.3 1.3 47.5 Wood 0 135 1 2 138 0.0 97.8 0.7 1.4 21.2 Mud 0 171 0 26 197 0.0 86.8 0.0 13.2 30.2 Iron Sheets 0 6 0 0 6 0.0 100.0 0.0 0.0 0.9 Grass/Reeds 0 0 0 1 1 0.0 0.0 0.0 100.0 0.2
134
Table 70: Distribution of Pre-Schools by Type of Structure, 1995 Wall Roof Floor % MAJOR URBAN Permanent 101 Permanent> 101 Modern> 98 81.0 Other> 3 2.5 0 Temporary> 0 Modern> 0 0.0 Other> 0 0.0 Temporary 20 Permanent> 19 Modern> 17 14.0 Other> 2 1.7 0 Temporary> 1 Modern> 1 0.8 Other> 0 0.0 Total 121 121 121 100.0 OTHER URBAN Permanent 41 Permanent> 41 Modern> 40 57.1 Other> 1 1.4 0 Temporary> 0 Modern> 0 0.0 Other> 0 0.0 Temporary 29 Permanent> 29 Modern> 16 22.9 Other> 13 18.6 0 Temporary> 0 Modern> 0 0.0 Other> 0 0.0 Total 70 70 70 100.0 RURAL Permanent 310 Permanent> 306 Modern> 228 35.0 Other> 78 12.0 0 Temporary> 4 Modern> 3 0.5 Other> 1 0.2 Temporary 342 Permanent> 313 Modern> 72 11.0 Other> 241 37.0 0 Temporary> 29 Modern> 2 0.3 Other> 27 4.1 Total 652 652 652 100.0
135
Table 71: Distribution of Pre-Schools by Source of Water, 1995 Number % Piped Stream/
River/ Dam Borehole/
Well Water
Tank/ JabiasNo
Water Total Piped Stream/
River/ Dam Borehole/
Well Water
Tank/ JabiasNo
Water Safe water (piped,borehole/ well)
MAJOR URBAN
111 2 4 0 5 122 91.0 1.6 3.3 0.0 4.1 94.3
Mombasa 30 0 3 0 1 34 88.2 0.0 8.8 0.0 2.9 97.1 Nairobi 81 2 1 0 4 88 92.0 2.3 1.1 0.0 4.5 93.2 OTHER URBAN
55 7 7 0 1 70 78.6 10.0 10.0 0.0 1.4 88.6
Thika 6 1 0 0 0 7 85.7 14.3 0.0 0.0 0.0 85.7 Nakuru 17 0 0 0 0 17 100.0 0.0 0.0 0.0 0.0 100.0 Eldoret 10 0 6 0 0 16 62.5 0.0 37.5 0.0 0.0 100.0 Kitale 5 2 0 0 0 7 71.4 28.6 0.0 0.0 0.0 71.4 Kisumu 17 4 1 0 1 23 73.9 17.4 4.3 0.0 4.3 78.3 RURAL 200 250 179 19 26 674 29.7 37.1 26.6 2.8 3.9 56.2 Kilifi 29 5 14 0 2 50 58.0 10.0 28.0 0.0 4.0 86.0 Nyandarua 27 30 11 5 2 75 36.0 40.0 14.7 6.7 2.7 50.7 Machakos 24 57 46 2 9 138 17.4 41.3 33.3 1.4 6.5 50.7 Uasin Gishu 8 10 27 0 0 45 17.8 22.2 60.0 0.0 0.0 77.8 Nakuru 36 38 8 4 9 95 37.9 40.0 8.4 4.2 9.5 46.3 Kericho 22 25 3 1 3 54 40.7 46.3 5.6 1.9 5.6 46.3 Narok 6 23 2 5 1 37 16.2 62.2 5.4 13.5 2.7 21.6 Kakamega 20 35 48 1 0 104 19.2 33.7 46.2 1.0 0.0 65.4 Kisumu 16 26 19 1 0 62 25.8 41.9 30.6 1.6 0.0 56.5 Garissa 12 1 1 0 0 14 85.7 7.1 7.1 0.0 0.0 92.9 TOTAL 366 259 190 19 32 866 42.3 29.9 21.9 2.2 3.7 64.2
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Table 72: Distribution of Pre-Schools by Type of Toilet, 1995 Number % Flush Pit Bucket No Toilet Total Flush Pit Bucket No Toilet TotalMAJOR URBAN 82 39 1 0 122 67.2 32.0 0.8 0.0 100.0 Mombasa 22 12 0 0 34 64.7 35.3 0.0 0.0 100.0 Nairobi 60 27 1 0 88 68.2 30.7 1.1 0.0 100.0 OTHER URBAN 25 44 0 1 70 35.7 62.9 0.0 1.4 100.0 Thika 4 3 0 0 7 57.1 42.9 0.0 0.0 100.0 Nakuru 10 7 0 0 17 58.8 41.2 0.0 0.0 100.0 Eldoret 5 10 0 1 16 31.3 62.5 0.0 6.3 100.0 Kitale 0 7 0 0 7 0.0 100.0 0.0 0.0 100.0 Kisumu 6 17 0 0 23 26.1 73.9 0.0 0.0 100.0 RURAL 38 615 1 20 674 5.6 91.2 0.1 3.0 100.0 Kilifi 5 35 0 10 50 10.0 70.0 0.0 20.0 100.0 Nyandarua 2 73 0 0 75 2.7 97.3 0.0 0.0 100.0 Machakos 5 132 0 1 138 3.6 95.7 0.0 0.7 100.0 Uasin Gishu 0 45 0 0 45 0.0 100.0 0.0 0.0 100.0 Nakuru 8 85 0 2 95 8.4 89.5 0.0 2.1 100.0 Kericho 7 46 0 1 54 13.0 85.2 0.0 1.9 100.0 Narok 0 34 0 3 37 0.0 91.9 0.0 8.1 100.0 Kakamega 7 97 0 0 104 6.7 93.3 0.0 0.0 100.0 Kisumu 3 55 1 3 62 4.8 88.7 1.6 4.8 100.0 Garissa 1 13 0 0 14 7.1 92.9 0.0 0.0 100.0 TOTAL 145 698 2 21 866 16.7 80.6 0.2 2.4 100.0
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Table 73: Distribution of Pre-Schools by Number of Children per Toilet Stall, 1995 Attached Not Attached All Children/ Toilet Number of Centres Children/ Toilet Number of Centres Children/ Toilet Number of Centres MAJOR URBAN 19.2 24 22.9 94 22.1 118 Mombasa 23.0 7 24.5 27 24.2 34 Nairobi 17.6 17 22.2 67 21.3 84 OTHER URBAN 28.0 23 23.8 45 25.2 68 Thika 6.9 2 29.8 5 23.3 7 Nakuru 44.6 4 22.7 13 27.9 17 Eldoret 30.3 2 20.4 12 21.8 14 Kitale 35.2 7 35.2 7 Kisumu 18.3 8 25.5 15 23.0 23 RURAL 25.8 473 28.5 172 26.5 645 Kilifi 35.9 31 46.1 8 38.1 39 Nyandarua 23.5 44 22.3 31 23.0 75 Machakos 21.6 97 26.7 38 23.0 135 Uasin Gishu 26.9 40 21.8 5 26.4 45 Nakuru 28.3 45 31.8 48 30.1 93 Kericho 28.6 46 23.4 6 28.0 52 Narok 24.9 29 10.3 5 22.7 34 Kakamega 26.2 94 34.0 7 26.7 101 Kisumu 22.0 40 33.5 17 25.4 57 Garissa 31.8 7 28.0 7 29.9 14
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Table 74: Distribution of Pre-Schools by Source of Classroom Lighting, 1995 Number % Solar Electricity Paraffin Lamps Sunlight Only Total Solar Electricity Paraffin Lamps Sunlight Only Total MAJOR URBAN 4 71 1 46 122 3.3 58.2 0.8 37.7 100.0 Mombasa 0 23 1 10 34 0.0 67.6 2.9 29.4 100.0 Nairobi 4 48 0 36 88 4.5 54.5 0.0 40.9 100.0 OTHER URBAN 7 24 1 38 70 10.0 34.3 1.4 54.3 100.0 Thika 1 3 0 3 7 14.3 42.9 0.0 42.9 100.0 Nakuru 0 11 0 6 17 0.0 64.7 0.0 35.3 100.0 Eldoret 6 3 1 6 16 37.5 18.8 6.3 37.5 100.0 Kitale 0 1 0 6 7 0.0 14.3 0.0 85.7 100.0 Kisumu 0 6 0 17 23 0.0 26.1 0.0 73.9 100.0 RURAL 41 29 2 602 674 6.1 4.3 0.3 89.3 100.0 Kilifi 0 1 0 49 50 0.0 2.0 0.0 98.0 100.0 Nyandarua 0 2 0 73 75 0.0 2.7 0.0 97.3 100.0 Machakos 0 4 0 134 138 0.0 2.9 0.0 97.1 100.0 Uasin Gishu 15 2 0 28 45 33.3 4.4 0.0 62.2 100.0 Nakuru 8 5 0 82 95 8.4 5.3 0.0 86.3 100.0 Kericho 3 4 0 47 54 5.6 7.4 0.0 87.0 100.0 Narok 0 1 0 36 37 0.0 2.7 0.0 97.3 100.0 Kakamega 13 4 1 86 104 12.5 3.8 1.0 82.7 100.0 Kisumu 1 4 1 56 62 1.6 6.5 1.6 90.3 100.0 Garissa 1 2 0 11 14 7.1 14.3 0.0 78.6 100.0 TOTAL 52 124 4 686 866 6.0 14.3 0.5 79.2 100.0
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ANNEX 7: ENUMERATORS’ REFERENCE MANUAL
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CHAPTER 1
INTRODUCTION BACKGROUND INFORMATION 1.1. With the rapid political, social and economic changes that have taken place since Independence, traditional ways of bringing up children have been affected. The society has therefore been forced to look for alternative ways of taking care of young children. Pre-schools have emerged as one of the alternatives to traditional systems of child-rearing, care and education. The Early Childhood Care and Development (ECCD) centres are expected to prepare children for formal schooling and play a custodial and socialization role now that the families cannot actively cater for the children. 1.2. The first pre-schools in Kenya began to emerge in the 1940s. They were established in urban areas to cater for European and later, Asian children. These pre-schools were well provided for, and were aimed at providing basic education for the children. The institutions were modelled after the British pre-schools of the period. 1.3. Pre-schools for African children were introduced in the large agricultural plantations and African neighbourhoods in major towns in the 1950s. The pre-schools fulfilled a custodial function. In some of the centres, basic health services and supplementary feeding were provided. A large number of children’s centres were opened during the emergency period (1953-1959), particularly in those areas most involved in the struggle for freedom. These centres provided custodial care and sometimes supplementary feeding. Children also engaged in singing and dancing at the centres. 1.4. The joint efforts of the community, government, welfare organizations and private enterprise have contributed to the fairly rapid expansion of pre-school education. A survey carried out in 1969 showed that there were 200,000 children enrolled in 4,800 day-care centres in the country with 5,000 teachers almost all of whom were untrained. In 1973, the enrolment had risen to nearly 300,000 under the care of 6,326 teachers, and to 400,000 children in 8,000 pre-schools under the care of about 10,000 teachers in 1979. By 1994, there were an estimated 952,000 children attending 19,000 pre-schools, and a teaching force of 28,000. 1.5. An ECCD centre is a “place” where a group of children aged under 6 years are under the care of an adult. In Kenya, ECCD centres are referred to by different names. The labels “day-care centres” and “nursery schools” are commonly used in the rural areas. “Day nurseries”, “kindergartens”, “play schools” and “nursery schools” are found in the urban areas. “Kindergartens” and “play-groups” are more commonly used among the wealthier urban neighbourhoods, while “day nurseries” and “nursery schools” serve the poorer urban population. “Pre-primary units” are mainly found in the urban areas and are a reception class before entry to Primary Standard One. 1.6. The general objectives of pre-school education are:
(a) To develop an informal education geared towards developing the child’s mental capabilities and his physical growth;
(b) To make it possible for the child to enjoy living and learning through play; (c) To enable the child to build good habits for effective living as an individual and a member of
a group; (d) To enable the child to appreciate his cultural background and customs; (e) To foster the spiritual and moral growth of the child; (f) To develop the child’s imagination, self-reliance and thinking skills; and
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(g) To enrich the child’s experience so as to enable him to cope better with primary school life.
1.7. To compile enrolment statistics on ECCD centres, the Ministry of Education sends out forms to the District Education Officers in the respective districts, who in turn use Zonal Officers to collect the enrolment data from the schools e.g. nursery schools and kindergartens. A district only submits annual summary figures for the district’s early childhood education enrolment, broken down by sex of child. No ECCD centre-based data is submitted from the districts, making it impossible to verify any queries due to the nonexistence of primary data at the Ministry’s headquarters. It should also be noted that the data disseminated do not always include age of the children. There are therefore data gaps on early childhood education regarding types of services provided, ownership and sponsorship, fees structure, physical facilities and other types of investments, and health and nutritional statuses of children. 1.8. Against this background, the Ministry of Education has decided to undertake a sample survey of ECCD centres in order to create a strong database on early childhood care and development. The Ministry is undertaking an exploratory sample survey as the initial effort towards achieving this goal.
OBJECTIVES OF THE SAMPLE SURVEY OF ECCD CENTRES 1.9. The main objectives of the survey are to:
(a) Provide baseline data for planning and policy formulation of early childhood care and development;
(b) Provide a profile of ECCD services;
(c) Show trends in child enrolment and teachers and other child caregivers;
(d) Provide data on healthcare and nutrition services available to the children in the centres;
(e) Assess the physical facilities accessible to the children enrolled in the centres; and
(f) Provide a framework for designing a computerized database management system for
monitoring early childhood care and development. 1.10. The information to be collected by the sample survey include (a) enrolment by gender, age and grade; (b) teachers and their qualifications and teaching experience, other members of staff and their duties; (c) physical facilities; (d) school feeding programmes; and (e) centre’s involvement in child growth monitoring and promotion. 1.11. This manual is designed to guide interviewers in data collection exercise during the survey. It defines the survey instruments in the form of survey organization, control and flow of questionnaires to and from the field, and the main concepts used in the survey. In addition, the manual contains procedures to be followed in completing each section of the questionnaire. Geographical codes, list of sampled ECCD centres, and schedule of field operations are presented in the annex.
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CHAPTER 2
THE SURVEY DESCRIPTION AND ORGANIZATION
COVERAGE 2.1 The survey will cover 900 ECCD centres nationally. The survey will be conducted on a purposeful sample of 17 districts/urban centres representing urban, pastoralist and other rural areas. The main urban areas are represented by Nairobi, Mombasa and Kisumu; while “other urban” is represented by Thika, Nakuru, Kitale and Eldoret. Rural areas were grouped into two zones, i.e. pastoralist and “other rural”. “Pastoralist” districts are represented by Narok and Garissa. The “other rural” districts selected so as to include every province and broad ecological zones are: Nyandarua, Uasin Gishu, Kericho, Kakamega, Nakuru, Machakos, Kisumu and Kilifi districts. The list of centres that you will interview will be distributed to you in advance. NO SUBSTITUTION OF AN ECCD CENTRE WILL BE ALLOWED. 2.2 The questionnaire for this survey is divided into seven (7) main sections. The sections seek information on (i) identification and location particulars of the ECCD centre, (ii) child enrolment data, (iii) size and structure of the teaching and nonteaching staff, (iv) centre’s financial status, (v) children feeding practices, (vi) nature of health services provided at the centre, and (vii) inventory of centre’s facilities.
SAMPLE DESIGN 2.3. The administrative decisions made that dictated the ECCD sample design include that:
a) The survey should cover a sample of 900 ECCD centres; b) The survey should cover districts/municipalities representing major urban areas, other urban, plantations, settled agriculture and pastoralists; c) The sample survey design should ensure inclusion of ECCD centres by sponsor, namely, parents/community, Government (mainly local authority), religious organisation, private, welfare, NGO; and d) The sample should ensure inclusion of ECCD centres from urban slum areas.
2.4. The total number of ECCD centres included in the lists from the districts/municipalities was 6,009. Upon receipt of the lists, the first step was to organize the district/municipality lists by reported sponsor. The groupings by sponsor were then treated as strata for the purposes of the sample design. The use of the term “strata” below will refer to classification of ECCD centres by sponsor. 2.5. The second step was to distribute the recommended sample of 900 ECCD centres among the districts. This was done by distributing the 900 ECCD centres to each district by its proportion to the total number of ECCD centres in the lists from all the study areas. 2.6. The third step was to split the total district sample into the various strata. Distribution was also made proportionate to the size of each stratum. The centres were then numbered sequentially within a district starting from community-sponsored centres, then local authority, religious organizations, private, and finally other sponsors. The required sample was generated by use of systematic selection. 2.7. The basic weights, before adjustment for nonresponse, are the reciprocals of the probabilities of selection, i.e.
wij=mij/nij where
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wij is the weight in district i stratum j);
mij is the total number of ECCD centres in district i stratum j; and
nij is the sample size in district i stratum j. 2.8. In producing survey estimates, the basic weights will be adjusted for nonresponse to arrive at final adjusted weight, which is the product of the basic weight and a nonresponse adjustment factor. The procedure of calculating the nonresponse (nr) factor for each district was as follows: nrij = nij/iij where nrij = Nonresponse adjustment factor for district i stratum j; nij = Total number of originally selected ECCD centres in district i stratum j; iij = Number of ECCD centres which responded in district i stratum j. The adjusted stratum and district weights are waij = wij * nrij = (mij/nij)*(nij/iij)=mij/iij and wai = mi/ii, respectively, i.e. the total number of ECCD centres in district i divided by the number of centres which responded.
PRE-TESTS 2.9. Pre-tests were conducted within Kiambu municipality in six ECCD centres selected by the DICECE officer, and representing different sponsors, namely, community, local authority, private, and plantation. The aim was to test the survey questionnaire so that any defects could be rectified before the survey. Other objectives included testing the efficiency of the field planning, and to give useful training to the field staff. The results of the pre-tests were used to refine the survey instruments. For example, at the design stage there was insufficient knowledge of the subject matter, the universe it was to cover, the way respondents would react to problems, and the answers they were likely to give. Based on the findings of the pre-test, some parts of the questionnaire and enumerators’ reference manual were revised. The findings also assisted in knowing how long the administration of the questionnaire would take, the number of interviewers required, and in planning other field logistics.
SURVEY ORGANISATION 2.10. The sample survey of Early Childhood Care and Development is being coordinated by Ministry of Education. The District Education Officers and most of the DICECE field personnel will therefore be involved in coordination and supervision at the district level. 2.11. The field operations will take five working days, and will involve about 100 enumerators and 15 supervisors. Given the tight schedule, each enumerator is expected to collect information from 2 ECCD centres each day. Training of Enumerators 2.12. Although some people are more competent at interviewing than others, one can become a good enumerator through experience. Your training will consist of a combination of classroom training and, where time permits, practical experience. Before each training session you should study this manual carefully along with the questionnaire, writing down any questions you may have. Ask questions you might have in order to
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avoid mistakes during actual interviews. Enumerators can learn from each other to clarify issues and discuss about actual interview situations. 2.13. The first part of your training course will consist of classroom lectures, during which the questions in the questionnaire and the instructions on how to complete the questionnaire will be discussed in detail. After the lecture on a particular section, you will do role-playing exercises in which you practice by interviewing each other. One person will be the enumerator while the other will pretend to be the respondent. You may also see and hear demonstration interviews conducted in front of the class by two of the trainers as examples of the interviewing process. You will practice reading the questionnaire aloud to another person several times so that you may become comfortable with reading the questions aloud. This is a very important assignment to prepare you for the next phase of training. 2.14. You will be given tests to see how well you are progressing during your formal training period. They will test your familiarity and understanding of the questionnaire and the survey process. The final group to be employed will be selected at the end of the training course. 2.15. Your training as enumerator does not end when the formal training period is concluded. Each time a supervisor meets with you to discuss your work in the field, your training is being continued. The formal training period merely provides you with the basic knowledge and information regarding the survey questionnaires, etc. Continued observation and supervision during the fieldwork completes the training process. Again, as you run into situations which you did not cover in training, it will be helpful to discuss them with your supervisor. You are also advised to discuss such problems with your fellow enumerators, as some may be in a position to help you. Role of the Enumerator 2.16. The enumerator occupies the central position in the survey, since he or she is the only one who collects information from the respondents. Therefore, the success of this survey depends on the quality of each enumerator’s work. 2.17. In general, the responsibilities of the enumerator will include:
i) Locating the ECCD centres which are assigned to him or her by the supervisor;
ii) Conducting interviews with the headteacher, members of teaching staff, or any other person involved with the management of the centre;
iii) Checking completed questionnaires to ensure that all questions were asked and the responses
neatly and legibly recorded; iv) Returning to the centre either to interview respondents who could not be contacted during
the initial visits, and attend to appointments or finish uncompleted interviews; and v) Preparing debriefing notes for the supervisor on problems encountered, so as to assist in
analysing the data collected and in planning and executing similar surveys, e.g. on concepts and wording of questions.
2.18. These tasks will be described in more detail throughout this manual and during your training. Role of the Supervisor 2.19. Training is a continuous process. Observations and supervision throughout the fieldwork are part of the training and data collection processes. Supervisors will therefore play very important roles in continuing the enumerators’ training and in ensuring the quality of data. In summary, the role of the supervisor will be:
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i) Enlisting cooperation in cases of reluctant or difficult respondents; ii) Observing some of the enumerator’s interviews to ensure that questions are being asked in
the right manner, and the answers interpreted correctly; iii) Spot-checking some of the centres selected for interviewing to be sure that the enumerator
interviewed the right centre and that he/she conducted the survey properly; iv) Reviewing each questionnaire to be sure it is complete and is internally consistent; v) Meeting with each enumerator in his/her team on a daily basis to discuss performance and
give out future work assignments; and vi) Solving any problems that the enumerator might have, such as locating the assigned centres
or understanding the concepts in the questionnaire. Flow of Questionnaires and Forms 2.20. Questionnaires and the enumerators’ reference manuals will be issued to enumerators/interviewers and supervisors during training. The lists of centres to be interviewed will be distributed to interviewers at the close of the training session. Completed questionnaires will be collected by supervisors for onward transmission to Nairobi. The supervisors will have to endorse in the Control Form, which is part of the questionnaire, that they have edited the questionnaires before submitting them to Nairobi.
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CHAPTER 3
PRINCIPLES OF INTERVIEWING 3.1. This section of the manual gives a summary of some important points to be kept in mind when conducting personal interviews during the ECCD survey. 3.2. Interviewing is a Specialized Art: Interviewing involves two people -- enumerator and the respondent. Interviewing facilitates the obtaining of information from someone by asking questions. However, it differs from ordinary conversation in several respects:
(a) The interviewer and the respondent are strangers to each other. One of the main tasks is to gain the confidence of the respondent so that he/she is at ease and willing to answer the questions you ask.
(b) Unlike normal conversation, one person is asking all the questions and the other person
answering them. You must refrain from giving your opinion. You must not react in any way to what the respondent tells you. Never show disapproval but probe in a manner that should not offend the respondent. At all times throughout the interview you must remain neutral. However, you should show interest in the answers by nodding your head or saying something like “I see” or “Yes”.
(c) There is a strict sequence of questions that must be asked. You must always be in control of
the situation. This means you must maintain the interest of the respondent throughout the interview.
3.3. Gaining Access to the Respondent: As mentioned above, you and the respondent are strangers to each other, yet you must approach the respondent and in a very short time gain his/her confidence and cooperation so that he/she will answer all the questions. First impressions of your appearance and the things you say and do are of vital importance in gaining the respondent’s cooperation. Therefore, you must be sure that your appearance and behaviour are acceptable to the respondent and also to other people in the area in which you will be interviewing. On meeting the respondent the first thing you should do is introduce yourself, stating your name and what you want of the respondent. A good introduction might be:
“Good morning. I am Mrs Philomena Wairigu and I am from the Ministry of Education. My visit this morning is part of an evaluation of Early Childhood Care and Development centres. We are interviewing headteachers and community leaders of the Early Childhood Care and Development centres. Your centre is one of the many chosen in the country for this study. The information I get from you will be confidential. The information will be pooled together with that of other respondents and be used to obtain knowledge on the strengths and weaknesses of the current early childhood care and development systems.”
3.4. Confidentiality: If a respondent is hesitant about responding to the interview or asks what the data will be used for, explain that the information you collect from the centres will be strictly confidential, and that all information will be merged to write a report. No individual report of any ECCD centre will be released to anyone. Because some of the questions to be asked are confidential, the interview should not be conducted in the presence of visitors unless the respondent, having first learnt the nature of the survey, has no objection. Also, you should never mention other interviews or show completed questionnaires to other interviewers or supervisors in front of a respondent or any other person. 3.5. Role of Interviewer: The interviewer occupies the central position in the survey, and the ultimate outcome of the survey depends on how the enumerator conducts his/her interview. In general, the responsibilities of the interviewer will be (a) locating the ECCD centres assigned to him/her by the supervisor, (b) conducting the interview, (c) checking the completed questionnaires to ensure that all questions were asked and the responses neatly and legibly recorded, and (d) returning all completed and unused questionnaires to
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the supervisor. No mention of immediate benefits should be made to the respondent as this might prejudice response. 3.6. Neutrality: Apart from confidentiality, most people are polite, especially to strangers, and they tend to give answers that they think will please the interviewer. It is therefore extremely important that you remain absolutely neutral towards the subject matter of the interview. Do not show surprise, approval, or disapproval of the respondent’s answer by your tone of voice or facial expression. 3.7. Probing: First ask the question as it appears in the questionnaire. It can happen that the respondent’s answer to a question is not satisfactory. From what is required, his/her answer may be incomplete or irrelevant, or sometimes he/she may be unable to answer the question as put to him/her. If this happens, then asking some additional questions is required to obtain a complete answer to the original question. Asking additional questions to obtain a complete answer is called probing. The probes must be worded so that they are “neutral” and do not lead the respondent in a particular direction. Do not prompt the respondent by saying something like “I suppose you mean that.... Is that right?” In many cases, the respondent will agree with your interpretation of his/her answer, even when that is not what he/she meant. You should never read out the list of coded answers to the respondent, even if he/she has trouble in answering. Remember that the quality of data to be collected depends very much on the enumerator’s ability to probe correctly. In probing, you should ensure that the meaning of the question is not changed. 3.8. Recording Answers: Each answer must be recorded in the correct space provided in the questionnaire. Record what the respondent says, not your own interpretation/summary. Before leaving the respondent you should check to see that all required questions have been answered. Always visit the respondent with the correct forms. Never rely on taking answers in a note book for transfer later. This is a bad habit and only complicates your work. If the respondent gives answers which are relevant to later sections of the questionnaire, do not repeat the question but frame it as if you are re-confirming the earlier response. If the respondent gives an answer that contradicts an earlier response, confirm the true position. If the question requires a numerical answer, be sure to enter the appropriate number or zero if the answer is “None”. If a space is left blank, it is impossible to tell whether or not the question was asked or answered. “No answer” and “0” have very different meanings when the survey data is analyzed. 3.9. Making Appointments: You should always try to arrange beforehand for a suitable time for interviewing the respondent. You should never try to force the respondent to attend to you at a time that would obviously be inconvenient to him/her. Once a time has been set for an interview it is important that you keep the appointment. Being late for appointments inconvenience respondents and results in unpleasant situations. 3.10. Handling Reluctant Respondents: Actual refusals are rare and for most enumerators there will be no refusals. If refusals come often, you will usually find something is wrong with the way you are introducing yourself or explaining the use of the survey. The person who says he does not have time for the interview is usually trying to put you off. Ordinarily a statement such as “this won’t take very long” or “I can ask you some questions while you are working” will start the ball rolling and soon he/she will give you his entire attention. Always be honest. Never tell a respondent that the interview will take only fifteen minutes if you believe one hour will be needed. If he really does not have the time, make an appointment for a return visit. A good enumerator is proud of his ability to meet people with ease and friendliness and to secure their cooperation. 3.11. Call-Back Procedures: It is important that you attempt to interview the headteacher and the community leader/sponsor, but occasionally you may need to make a second visit if neither the headteacher nor community leader were there. Most of the questions that are contained in the questionnaire can only be answered by the headteacher (or his/her deputy) and a community leader (e.g. head of the management committee) or a person who has been associated with the centre for a long period of time. If a respondent does not know the answer to a question, ask politely who he/she thinks has the information, and obtain an interview with the suggested respondent e.g. a school teacher might not know the capital costs of the centre and thinks that the head of the management committee might know. For a physical description of the structures, it might be advisable to go round the centre with the respondent to ensure that the right
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information is obtained. Do not try to complete the questionnaire by interviewing employees or other persons who are not familiar with the centre. 3.12. Enumerator Review of Questionnaire: As soon as possible after leaving the respondent, the enumerator must check over the questionnaire carefully to see that all the answers are complete. In some cases it may be necessary to revisit the respondent for more complete information and this is the time to do so. If the respondent has not compiled numerical data on assets, employment, enrolment, salaries, etc., you can return at a time agreed between you and the respondent to collect the missing data. Under the pressure to complete an interview, some enumerators become lazy in checking over each questionnaire while the interview is fresh in their minds. This part of the job should never be overlooked. Experience has shown that most of the problems involving completed questionnaires could have been eliminated if the enumerator had made a check of the questionnaire before handing it over to the supervisor. The enumerator should therefore plan his/her workload to include some time for checking the questionnaire. 3.13. Language and Translation: Interview the respondent in the language in which he/she feels most comfortable. If he/she prefers English, do the interview in English. If the respondent is most comfortable in Kiswahili, then speak Kiswahili. If he/she speaks only another language you understand, then you can do the interview in that language. If the respondent speaks only a language you do not understand, then you must raise this problem with your supervisor. In translating and probing, be sure you do not give the answer you expect. When translating certain words, it is essential that the question is framed in such a way that it would mean the same as in the English phrasing of the questionnaire. For example, there is usually particular difficulty with the word work. In many languages, when a person is asked “Do you work?” it means “Are you employed by someone else for pay?” Try to avoid this type of misunderstanding when you are asking questions in other languages. 3.14. Ending the Interview: Once all the information has been obtained the interview should be brought to a close without undue extension. Even if the respondent is very friendly, you should always avoid overstaying your welcome. You should always acknowledge and thank the respondent for his/her time and willingness to provide you with the data. A respondent that you have favourably impressed will be willing to give additional information when his/her centre is selected for another survey.
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CHAPTER 4
CONCEPTS AND DEFINITIONS
4.1. The purpose of the ECCD Survey Questionnaire is to collect information which will be used to compile a profile of ECCD centres. More importantly the information will be used to help the Ministry of Education and NACECE in future planning of Early Childhood Development. It is important, therefore, that data collected refer to the same items or universe. Below are common definitions of important concepts used in the survey. 4.2. ECCD Centre: The unit of analysis of the survey shall be the ECCD centre. This is a place where a group of children aged under 6 years are under the care of an adult. The centre could be a classroom attached to a primary school, a church, a social or special hall, a garage, backyard, someone’s house, or under a tree. Some of the common labels used to define ECCD centres include “day-care centres”, “crèche”, “nursery schools”, “day nurseries”, “kindergartens”, “play schools”, “play-groups”, “pre-primary units”, “duksi/madrassa” and Montessori schools. For the purpose of the survey, both duksi/madrassa and Montessori are types of service. The centres are discussed below: - In a rural setting, nursery schools normally refer to programmes for children under six years while in
urban centres, the normal rational age is below four years. Nursery schools are also known as day nurseries and play groups.
- Kindergarten is a German term which refers to education programmes for young children similar to
those offered in nursery schools. - Day-care centres normally refer to centres which offer programmes for children who are under three
years of age. - Crèche refers to institutions which mainly provide care to young children aged between six months
and three years while mothers are away or at work. - Pre-primary units provide education and care to children aged 5-6 years and are normally attached to a
primary school where children gain direct entry to Primary Standard One. Such children may or may not have attended nursery school education previously.
- Pre-school is the conventional term for programmes of young children between 0 and 6 years, and encompasses all types of ECCD centres.
4.3. Ownership: In this survey, ownership is categorized as either private or public. A private ECCD centre is one which is owned by an individual or private firm while a public ECCD centre is one which is owned by the community and could also be getting support from other sponsors. 4.4. Management of the centre: The management of the ECCD centre refers to a person or persons who carry out the day-to-day administration of the centre. A committee could be elected or appointed by the community or its owners to manage the centre. For the ECCD centres attached to a primary school, a headteacher of the parent primary school could be managing the centre. The headteacher of the centre could also be managing the centre. Other managers could be religious leaders, individuals, companies, etc. 4.5. School Committee: A school committee consists of members elected by parents and is charged with the responsibility of running the school. Some of the functions of such a committee are: organizing and collecting funds and fees, matters pertaining to staff recruitment and discipline, and payment of staff salaries/wages. Usually, a pre-school attached to a primary school is served by the same committee as the primary school. However, an ECCD centre which is not attached to a primary school assumes autonomy and is expected to have its own independent school committee.
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4.6. Sponsorship: A sponsor is taken to be a community, company, organization, or individual, who contributes in cash, kind or time, for the welfare of the institution without expectations of direct personal benefit. The sponsor takes interest in the quality of the centre’s services and is therefore expected to monitor its progress. Sponsorship includes contributions by parents/guardians over and above compulsory fees fixed by the community or sponsor, but excludes contributions to private pre-schools by their proprietors. For the purpose of the survey, a sponsor contributes part or full payments for regular/operating costs of the centre e.g. teachers’ salaries, other workers’ remuneration, school feeding, etc. Sponsors include local authorities (County/ Municipal/ Town/ Urban councils), central Government, religious organizations, community/parents, private company, plantations/estates and other companies, and NGOs. 4.7. Local authorities, which include county, municipal, town, and urban councils, are created under the Local Government Act and operate under the umbrella of the Ministry of Local Government. The central Government’s involvement in early childhood development is mainly through the Ministries of Education, and Culture and Social Services. Religious organizations have pre-schools affiliated to the churches, temples and mosques, and also support some of community pre-schools. It is a common practice for nursery schools to be established on church compounds, and if necessary use church buildings as classrooms during the week. Religious organizations involved in pre-school education are mainly of Christian, Muslim and Hindu religions. Community/parents consist of people in the neighbourhood of the centre who fall within the centre’s child-intake catchment area. Harambee donations from areas that send children to neighbouring centres should also be included in the community/parents sponsorship. 4.8. Firms, cooperatives, state corporations and plantations also establish pre-schools for children of their employees. Plantations are large pieces of land where tea, cotton, sugar, tobacco, etc are grown. In the plantations/estates (mainly tea, coffee, sugar, pineapple and sisal estates), the company may provide a building, hire teachers, OR provide a plot where parents/workers could put up a building and hire teachers at their own expense. Corporations such as the railways, posts and telecommunications, National Youth Service and some big industries e.g. Pan Paper are also partners in pre-school education. 4.9. A nongovernmental organization (NGO) or Private Volunteer Organization (PVO) means a private voluntary grouping of individuals or associations, not operated for profit or for other commercial purposes but which have organized themselves nationally or internationally for the promotion of social welfare, development, charity or research through mobilization of resources. An NGO could be either national or international. A national NGO is registered exclusively in Kenya with authority to operate within or across two or more districts in Kenya. An international NGO is originally incorporated in one or more countries other than Kenya, but operates within Kenya under a certificate of registration. The main agencies which support pre-school education include Catholic Relief Services, National School Feeding Programmes, National Christian Council of Kenya, Rotary and Lions, Child Welfare Society of Kenya, Christian Children’s Fund, UNICEF, Aga Khan Foundation, and Bernard Van Leer Foundation. 4.10. Type of neighbourhood: The sample of ECCD centres will be located in urban slums or urban non-slum, and rural plantation or rural settled agriculture or rural pastoralist. A slum is an informal, unplanned and overcrowded settlement, with (a) structures of temporary material (b) poor sanitation (e.g. sewerage, water supply), (c) poor basic infrastructure e.g. access roads and health facilities, and (d) inhabited by low income households. Among the major urban centres, Nairobi has the greatest concentration of slum populations. The oldest and the largest slums, which are on government land, such as Korogocho-Kariobangi and Mathare, have some of the poorest conditions. A number of slums developed later in the west of the city, mainly Dagoretti (e.g. Kawangware, Riruta and Kangemi), while the more recent slum areas settled to the north are Garba, Githurai and Kahawa. 4.11. Over two thirds of Kenya is arid or semi-arid. The areas are characterized by (a) frequent droughts which affect supply of water, milk and other food supplies, and (b) difficult terrain and inadequate transport facilities. The majority of people who live in the dry areas are nomadic or semi-nomadic, i.e. whose main source of livelihood is from livestock and move from place to place in search of water and pasture for their livestock. Settled agricultural areas are rural areas which are neither pastoral, plantation, or forest reserves.
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4.12. Grants/Aid: Grants/aid is taken to refer to cash and material gifts/contributions by the sponsors to the centre, either for meeting recurrent expenditures (e.g. school food, chalk, electricity, water, teachers’ salaries, uniforms, charcoal/firewood/gas) and capital costs (e.g. donations of land, classrooms/learning halls, cement, books, playing equipment and utensils; construction of classrooms, kitchens and swimming pools, contribution of labour in construction). 4.13. Respondent: A respondent is any person who provides information to the interviewer. In this survey, the main respondent will be the headteacher, community leader or any other person involved with running of the ECCD centre. However, individual teachers/caregivers will be interviewed to give details of their training and teaching experience. 4.14. Supervision/Inspection: Whereas local communities are mainly responsible for the establishment and running of schools, the responsibility of supervision and inspection of schools and colleges is vested in the office of the Chief Inspector of Schools. At the district level, the school inspectors, Zonal Inspectors (formerly known as assistant primary school inspectors), and DICECE staff undertake inspection of pre-schools among their other responsibilities. Nursery School Supervisors employed by local authorities also undertake supervision and inspection of pre-schools. In some areas, the supervision is done harmoniously by the various supervisory teams. 4.15. Attachment/Linking to a Primary School: An attached ECCD centre shares the same compound with a mother primary school, and may or may not have its own headteacher. A linked ECCD centre is not in the same compound with a primary school, but is recognized by the primary school to which it is linked as a “feeder” for the purpose of Primary Standard One intake. A headteacher of a primary school attached to a pre-school normally assumes the overall responsibility of the welfare and development of both the pre-school and the primary school. A headteacher of a pre-school which is linked to a primary school assumes the overall responsibility for the centre, but would be expected to be answerable to the headteacher of the linking primary school for professional and administrative support. 4.16. Services Offered by the ECCD Centres: In many ECCD centres, active learning methods are used. Children learn through game and play. They learn about their environment, how to care for themselves, social skills, and language skills. They also learn letters of the alphabet, some words, recognition of numbers, counting, and even some mathematical operations. Teachers and parents take pride when their children speak some English or Kiswahili words even if they do not know their meaning. 4.17. A sizeable proportion of the Kenyan population is Muslim. Children in Muslim communities are introduced early into their religious life including knowledge of the Arabic alphabet in institutions known as “Chuo”, “Duksi” or “Madrassa”. Beginning at the age of three to four years, both boys and girls attend Chuo, the Quranic School, where they learn to recite the Holy Quran, receive some background to the life of the Prophet, and learn to recognize Arabic letters. When children have made sufficient progress in their studies of the Quran, they may also attend madrassa. Complete education is provided in the madrassa as the children are taught further understanding of the Quran, some history, geography, mathematics and possibly other subjects. 4.18 Madrassa have a well constituted curriculum which runs from pre-school to university level. However, the spectrum of the curriculum is not integrated with national mainstream curriculum. Duksi are institutions in which children of various ages are taught the Holy Quran only. Children are also taught the writing of alphabet, memorizing of the Holy Quran, and how to read and write some verses. 4.19. Parents who aspire for national mainstream secular education also enrol their children in other pre-schools or primary schools. This means that from an early age a child is expected to attend two institutions, usually on a daily basis. The interest to provide Islamic and formal mainstream education under one roof motivated the Ministry of Education (i.e. NACECE and DICECE) to establish pilot integrated curriculum in selected madrassa beginning 1986. The integrated programme seeks to integrate religious instruction with mainstream secular education. This is done by combining some methodological features of mainstream secular education with those of Quranic education, in an effort to make instructions more relevant to the future needs of the children.
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4.20. Land Tenure: Land tenure in Kenya can broadly be classified under the following categories: freehold, leasehold and trust land. Freehold land is a parcel of land held in perpetuity through absolute title. There is no time limit in ownership and land use is only subject to relevant existing laws, i.e. Land Planning Act, Land Acquisition Act, and the building codes. There are no restrictions on transfer. Leasehold land is a parcel of land held for a fixed term given by either a local authority or the Commissioner of Lands, normally for periods ranging from 30 to 99 years. Trust land is land held by indigenous communities under tribal arrangements (normally communal ownership), and has not been demarcated and registered. Such land is normally held in trust on behalf of the communities by Country Councils, hence the term trust land. 4.21. Current Market/Replacement Value: The survey will collect information on the market value, i.e. how much it would cost to put up the centre today. However, such a value is difficult to obtain since (a) there may be no documentary evidence, i.e. records; (b) some centres took a long time to complete and the quality of the data would therefore be affected by price changes over time; and (c) some of the materials and labour were contributed free and their value is not known. To overcome this valuation problem, the interviewer should get from the respondent the current market value of the centre, i.e. how much it would cost today if the respondent was to build an identical centre. 4.22. Rent: Rent or rental is money paid for use over a period of time of anything such as house, truck, land. 4.23. Formal Education: The current 8-4-4 education system introduced in Kenya in 1985 comprises of three main levels: primary, secondary and university. Under this system, the primary school level consists of an eight-year course covering eight grades called “standards” with Kenya Certificate of Primary Education (KCPE) terminal examination taken in Standard 8. This level is supposed to be for the age group 6-14 years. Up to and including 1965, the primary school terminal examination was taken after 8 years and was called Kenya African Preliminary Examination (KAPE) certificate. From 1966 up to the introduction of the 8-4-4 education system, the primary school terminal examination was a seven-year course leading to the Certificate of Primary Education (CPE). The KCPE and its predecessors were instituted to serve both as a terminal primary school examination and as a selection instrument for entrance into secondary schools. 4.24. Under the 8-4-4 system of education, secondary school level consists of a four-year course covering four grades called “forms” with the Kenya Certificate of Secondary Education (KCSE) terminal examination. This level is supposed to be for rational age group 14-18 years. Previously, secondary education consisted of “ordinary” secondary (four years) and “higher” secondary (two years), which did not necessarily coexist in the same school. In the lower secondary school, an optional examination titled Kenya Junior Secondary Education (KJSE) examination was taken at the end of the second year. The East African Certificate of Education (EACE) was taken at the end of the fourth year and the East African Advanced Certificate of Education (EAACE) at the end of the sixth year under the East African Examinations Council. Fourth year terminal examinations are normally referred to as Ordinary (“O”)-level equivalents, while sixth year terminal examinations are normally referred to as Advanced (“A”)-level equivalents. 4.25. University education is the apex of the formal system of education for the education and training of high level manpower for national development. Previously, the academic requirements for admission to the local public universities were based on Kenya Advanced Certificate of Education or its equivalent. However, under the current 8-4-4 system of education, admission of students is based on the Kenya Certificate of Secondary Education. After successful completion of the university undergraduate study, students are awarded a bachelor’s degree in various disciplines. 4.26. Teacher Training: From independence through 1970, candidates with primary school terminal examination certificate constituted the majority of trainees in teacher training colleges. After successfully completing their two-year training course, the trainees were graded as primary school teachers grade 3 (P3). Holders of Kenya Junior Secondary Examination (KJSE) certificate, sat after completing Form II, were trained for two years as primary school teachers grade 2 (P2), while holders of Ordinary level school certificate or its equivalent were trained for two years as primary school teachers grade 1 (P1). Holders of Ordinary level school certificate or its equivalent were trained for three years as secondary school teachers grade 1 (S1), while holders
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of higher school certificate or its equivalent were trained for one year as S1 teachers. P4 teacher training certificate holders were trained for two years and were drawn from primary school leavers who either did not have the terminal examination certificate or had not completed the primary school cycle. 4.27. ECCD-specific training: For a long time, training of personnel for pre-school education was largely carried out by the Ministry of Culture and Social Services. This function was transferred to the Ministry of Education in 1980. In 1984, the Ministry of Education phased out the previous one-year pre-service training programme for pre-school teachers, and replaced it with a two-year in-service course beginning April 1985. The training of ECCD teachers is carried out by DICECE trainers. The teachers undergo a two-year in-service course consisting of six residential sessions, alternated by five field experience sessions. The residential sessions are conducted during school holidays in the months of April, August and December. During the residential sessions, the trainees are exposed to various skills and knowledge on early childhood care and education and they are expected to practise these skills in their schools during the term time. The trainers continuously monitor the teachers during the field experience, to ensure that the teachers are able to put into practice what they have learned. 4.28. The topics covered in the six residential sessions include: child development, pre-school curriculum, health and nutrition, development and management of early childhood education in Kenya, English language, Lugha ya Kiswahili, and general knowledge. The training is carried out in 20 DICECE, and the training venues are either teacher training colleges, secondary schools or other institutions. The academic qualification required to enter the in-service course is a minimum of 15 points CPE or 30 points KCPE. Teachers who have not attained the above minimum qualifications but have sat for CPE/KCPE can join an alternative two-year course offered at Garissa, Keiyo and Samburu DICECE. There are also various short-term in-service courses conducted in the districts for teachers who have not had a chance to attend the two-year course. The courses run for a duration of five weeks and cover briefly several topics of the teachers’ main course. The participants usually receive attendance certificates. 4.29. Private organizations such as the Kindergarten Headmistresses Association (KHA) and Child Developers Programme (Montessori) training programme have organized one- and two-year training courses for their teachers, respectively. These organizations have their own training curriculum, examinations and certificates. Most of the teachers they train work in private pre-schools located in the urban areas. It should be noted that, since all the training programmes including DICECE are sponsored by different agencies, they differ in content, methodology, selection procedures, duration and cost. 4.30. The KHA, which was formed in 1973, is an association of unaided nursery and kindergarten schools in Kenya. In 1977, the KHA two-year (6 terms), women-only, full-time kindergarten teachers training programme went into operation, while a one-year (3 terms) full-time nursery teachers training course for less well-off working parents was launched in May 1986. In the two-year training course, trainees are placed singly in kindergartens offering teaching practice facilities, where they spend the morning hours working and watching the class teacher and taking one lesson per day. They are moved to a different school every four weeks in the first year, and are visited by KHA supervising tutors who evaluate their work. During the second year, trainees stay 6 weeks in each school and teach for one full day per week plus a lesson on every other day. In the afternoons, trainees meet for lectures, which are given by KHA headmistresses in the first year and by specialists in the required subjects in the second year. 4.31. In the case of the one-year, women-only KHA course, trainees are moved to different schools every four weeks for the first two terms, and after six weeks in the second term. They are also visited by KHA supervising tutors who assess them while teaching in order to evaluate their work. In the afternoons, trainees meet for lectures at the KHA premises or in a member nursery school. Lectures are given by KHA headmistresses and sometimes by specialists in a particular subject. The entry requirements for the two year course is “O”-level minimum Division 2 or C+ at KCSE or their equivalents; and minimum Division 3 or C- at KCSE or their equivalents for the one-year course. 4.32. The Montessori learning approach system of training is managed by the Child Developers’ Programme. The teacher training course is a two-year programme, consisting of one year residential training and another
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year of fieldwork. During the fieldwork, the trainees are visited by their trainers, and are awarded a certificate after successful completion of the two year training. 4.33 The Presbyterian Church of East Africa (PCEA) and the National Youth Service (NYS) also organize training programmes tailored on the DICECE training programme. The PCEA two-year programme, which started in 1990, admits committed Christians with a minimum grade of 35 points at KCPE, 15 points CPE, a pass at KJSE, minimum of Division IV or D Plain at KCSE. To be admitted to the NYS programme, an applicant must be a member of the NYS and a holder of D Plain at KCSE or its equivalent. Upon completion of the training, the trainees sit an examination set by the Kenya National Examinations Council. 4.34. Gross Salary: Gross salary is the sum of wages or salaries from employment in the ECCD centre plus all associated allowances and benefits, e.g. house allowance, before regular deductions (e.g. income tax, social security, service charges, and pension contributions) are made. The receipts should, as a rule, be of a recurring nature and payable to the staff member by the ECCD centre on a regular basis. 4.35. Grade/Class: Teachers are encouraged to group children by age, abilities and interests. However, unlike primary and secondary schools where the classes are structured into “standards” and “forms”, respectively, the early childhood care and development centres’ internal child progression system is not standardized. This is mainly because the centres offer different types of services, ranging from pure day-care to formal pre-primary units. There is therefore no defined age of entry applicable to all types of centres. The lowest class within the learning hierarchy will be considered as Class/Grade One. After completion of first year, the child is expected to progress to Class/Grade Two, and so on. 4.36. Health and Nutrition: The pre-school centre plays an important part in children’s health and nutrition. During training, teachers are sensitized on, among other things, (a) identifying factors related to childhood diseases and the necessary preventive measures; (b) identify programmes for monitoring and referral for children with health problems; and (c) establishing and promoting networking to improve family health. The teachers are then able to pick out those children who need medical care and link them with health services. The teachers should find out those children who have not been immunized and advise the parents to take them for immunizations. If many of the children have not been immunized, the teacher should contact the health officer who could use the pre-school centre for immunizations and other health services. Similar corrective measures are taken in case of children who may have disabilities, malnourishment, and other childhood diseases and deficiencies. Usually, DICECE staff and district nutritionists work together to sensitize communities on various matters relating to child health and nutrition. 4.37. Disability: A disability is a limitation in an individual’s ability to perform an activity in a manner that is considered to be normal. Impairment is an abnormality in the structure or function of a part of the body or mind. Disabilities are caused by impairments, which are in turn caused by diseases, injuries or congenital (inborn) or peri-natal conditions. Disabilities reported in the survey of ECCD centres should have had duration of at least six months. Disabilities can be: Difficulties in seeing (visual defects)
Includes all people who have difficulty in seeing and the completely blind
Difficulties in hearing Includes all people who have difficulty in hearing and the completely deaf Difficulties in speaking
Includes all people who have difficulty in speaking and those who have complete loss of speech Please exclude stammerers/ stutterers (with difficulties in pronouncing words beginning with certain letters such as B, D, G, K and V e.g. those who skip letter K)
Difficulties in moving Includes all people who have difficulty moving their limbs and trunk, or moving from place to place
Mental retardation Includes conditions which affect a person’s ability to learn, to acquire knowledge and to adapt to environment which other people of the same age and within the same environment are able to cope with
4.38. It is important that the right number of disabled children in the ECCD centres is known to enhance proper planning for their needs. Your duty is to make sure that you collect the information on disability using the best diplomacy you can bring to bear. Remind the respondents that the information will be kept
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confidential. 4.39. Immunization: The objectives of the Kenya Expanded Programme on Immunization (KEPI) is to ensure that all children are vaccinated against measles, polio, tuberculosis, tetanus, diphtheria and pertussis, by the first birthday. Primary healthcare facilities are widespread in all the districts to ensure delivery of quality immunization services throughout the country. At the age of one, a fully-immunized child should have received Bacille Calmette-Guerin (BCG) against tuberculosis and Oral Polio at birth, DPT-I and Oral Polio I at 6 weeks, DPT-II and Oral Polio II at 10 weeks, DPT-III and Oral Polio III at 14 weeks, and measles at nine months. A “booster” immunization of Polio and DPT is given after 5 years. According to the recommended immunization timetable, children entering ECCD centres should all have been fully immunized. KEPI provides immunization cards for each child which gives a record of the immunizations. 4.40. Child Growth Monitoring: Growth Monitoring and Promotion (GMP) ensure early detection of children’s development, health and nutritional problems. In GMP, children’s weight and height are taken against the age of the child and the results plotted on a graph. One of the greatest successes of GMP is its ability to detect malnutrition at its earliest stages, which helps to avert problems at lower cost. 4.41. In Kenya, the GMP programme was introduced nationally by the Ministry of Health in 1985. In 1988, the staff of NACECE and DICECE started collaborating with the Division of Family Health (Ministry of Health) in the implementation of the GMP programme. This collaboration involved selecting some of the pre-schools to be GMP centres. Since ECCD centres mainly cater for under-six year old and GMP mainly targets the same population, the centres offer unique points of intervention to the GMP programme. In all the districts, GMP is a joint venture between DICECE trainers, pre-school teachers, Ministry of Health personnel, parents, local communities, and NGOs. Although the GMP is used as a way of alerting parents to inadequate growth in their children, the prospects for subsequent treatment are not clear. 4.42. Micronutrient Deficiencies: Lack of essential vitamins and minerals frequently result in micronutrient deficiency-related diseases and disorders. Dietary deficiencies of iodine, iron, and vitamin A are important causes of poor child health and development. Iodine is required for the production of thyroxin, a major hormone in human metabolism, and the amounts of thyroxin produced determines the level of both mental and physical activity of the individual. Iron deficiency anaemia, which is caused by both inadequate intakes and through blood losses in stool, results in below-optimal performance and lack of intellectual and physical stamina. Poor intake of Vitamin A causes children to develop sight-related problems. 4.43. Iodine deficiency has been largely controlled through improvement of national capacity for iodization and mobilization of individual salt manufacturers to produce good iodized salt, and the National Health Laboratories and Kenya Bureau of Standards’ inspectors conduct spot-checks in the salt manufacturing firms and on salt sold in the market. Vitamin A and iron supplements are provided to children at risk and lactating mothers mainly through the Division of Family Health. 4.44. During training, ECCD teachers are sensitized on the importance of personal hygiene, proper environmental sanitation, encouraging private sector and plantations to provide mass treatment for their workers and their children, and the need for mass and individual de-worming using safe drugs available in the market. Common intestinal worms include roundworms, hookworms, and tapeworms. De-worming is the treatment of intestinal worms commonly found in children. Normally a team of health personnel visits centres to collect stool samples for assessing the presence of intestinal worms, and follow up with treatment or referrals of the infected children. 4.45. Eye and ear diseases, if left unchecked could result into seeing and hearing impairment. During training, ECCD teachers receive instructions on how to detect children with varying degrees of sight and/or hearing difficulties, and initiate actions with parents and health workers on the preventive and curative measures to be taken. 4.46. School Feeding: The main objective of the school feeding activities is to provide food supplements to pre-primary and primary school children in order to help improve their health and nutritional
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status and provide them the energy to participate in school, particularly in food-deficit areas. Pre-school centres have been used to provide supplementary feeding to improve the nutritional status of children and prevent malnutrition. Since the 1950s many pre-schools, for example, in central Kenya and former African estates in Nairobi were started as feeding centres which also provided some custodial care to children. In the arid and semi-arid areas and in the poorer sections of the urban community, a number of organizations provide feeding programmes in the pre-school centres. 4.47. The National School Feeding Council of Kenya (NSFCK), which was established in 1967, operates a school feeding programme for pre-primary and primary schools by providing at a minimum cost a morning drink and supplementary mid-day meal for pre- and primary school children, respectively. The programme was originally initiated by OXFAM and later CARE but is now under the control of NSFCK. The NSFCK was also instrumental in initiating the Government/WFP program but its own program differs in one important respect: only those children able to make a contribution to the cost are fed. 4.48. The Government of Kenya/World Food Programme (WFP) primary schools feeding programme was introduced in 1981 and presently covers 23 districts in arid and semi-arid areas of the country. In this context, arid districts are Wajir, Garissa, Mandera, Isiolo, Marsabit, Samburu, Turkana and Tana River. The semi-arid districts are Kilifi, Kwale, Lamu, Embu, Tharaka-Nithi, Machakos, Kitui, Mwingi, Kajiado, Narok, Baringo, West Pokot, Laikipia, Keiyo and Marakwet. WFP donates wheat, vegetables and oil which is then exchanged by the Government for maize and beans and transported to recipient schools; these staples are used for preparing mid-day meals in pre-primary and primary schools. Food aid to the arid and semi-arid lands (ASAL) districts has provided incentive to parents to enrol their children in school, encourage their regular attendance, and reduce dropouts. Due to the long cooking time required to prepare these foods, school meals are normally served during lunch break. 4.49. The School Milk Programme, which started in 1979, is designed to cover the entire country and reach each school child (with 0.2 decilitres of milk) twice a week throughout the school year. The School Milk Programme, commonly referred to as Nyayo milk, also covers pre-primary centres attached to a primary school. 4.50. Many other NGOs and Government ministries are involved in this provision. Such NGOs include Catholic Relief Services, Action Aid, Christian Children’s Fund, Plan International, World Vision, Red Cross and many religious and welfare organizations. The ministries include health, agriculture, and culture and social services. Pre-school centres run by large municipalities also provide a form of feeding programme in their centres.
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CHAPTER 5
INSTRUCTIONS FOR COMPLETING THE QUESTIONNAIRE
GENERAL INSTRUCTIONS FOR COMPLETING THE QUESTIONNAIRE 5.1. This part of the training manual is designed to familiarize you with the ECCD survey questionnaire. To effectively collect the information needed by the ECCD survey, you must understand how to ask each question, what information the question is attempting to collect, and how to handle problems which might arise during the interview. You must also know how to correctly record the answers the respondent gives, and how to follow special instructions in the questionnaire. Complete the questionnaire yourself; keep it clean; and write legibly, preferably in capital letters. 5.2. Asking the Questions: It is very important that you ask each question exactly as it is written in the questionnaire. When asking a question, be sure to speak slowly and clearly so that the person you are interviewing will have no difficulty in understanding the question. At times you may need to repeat the question in order to be sure the respondent understands it. In those cases, do not paraphrase the question but repeat it as it is written. For most of the questions, the respondent should extract the information from the centre’s registers rather than relying on memory recall. 5.3. However, if after you have repeated a question several times and the respondent still does not understand it, you may have to restate the question. Be very careful when you change the wording that you do not alter the meaning of the original question. If you paraphrase the question, please note in the margin how you asked the question, as this will assist the Ministry of Education in preparation of questionnaires and enumerators’ reference manuals for future ECCD surveys. 5.4. In some cases, you may have to ask additional questions (we call this probing), to obtain a complete answer from the respondent. If you do this, you must be careful that your probes are “neutral” and that they do not suggest an answer to the respondent. The section on principles of interviewing reminds you that probing requires both tact and skill, and it will be one of the most challenging aspects of your work as an interviewer in this survey. 5.5. Recording the Responses: In the survey of ECCD centres, all interviewers will use pens with blue ink or blue ball-pens to complete all questionnaires. Supervisors will do their work using pens with red ink or red ball pens. Enumerators should not use pencils in filling the questionnaires. There are three types of questions in the ECCD survey questionnaire: (a) questions with pre-coded responses, (b) questions which do not have pre-coded responses, and (c) filters. 5.6. For some questions, we can predict the types of responses a respondent will give. The responses to these questions, termed as questions with pre-coded responses, are listed in the questionnaire. To record a respondent’s answer, you merely circle the option’s code in the questionnaire which corresponds to the reply, and enter the option’s code in the box provided. Be careful that each circle surrounds only a single code. For example, if the response to Question 105 on whether the ECCD centre is registered is “Yes=1” circle “1” and write down “1” in the box assigned to the question. 5.7. In some cases, pre-coded responses will include an “Other, Specify = 9” category. The “9” should be circled when the respondent’s answer is different from any of the pre-coded responses listed in the question, and the actual respondent’s answer written down in the space provided. 5.8. Responses to some questions are not pre-coded. In entering the response for these questions, you must record the respondent’s answer in the space provided. Usually, you will record a number or date (e.g. year centre was established). Note that if the entry has fewer digits than the number of boxes provided, you will fill the leading zeroes. For example, a response of “11” is recorded as “011” if three boxes are provided, or if four boxes had been provided, you would record “0011”.
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5.9. In order to ensure the proper flow of the questionnaire you will sometimes be directed to check a respondent’s answer to an earlier question. Questions of this type are called filters, and are used to prevent a respondent from being asked irrelevant and embarrassing questions. The references to “If yes” and “If no” in the questionnaire are for your own guidance and are not supposed to be read out to the respondent. For example, if a respondent replies that a centre has never been supervised/ inspected, the respondent should not be asked when the centre was last supervised/inspected. 5.10. Correcting Mistakes: It is very important that you record all answers neatly. For pre-coded responses, be sure that you circle the code for the correct response carefully, so that there is no confusion as to what the respondent’s answer is. For open-ended responses, the reply should be written legibly so that it can be easily read. If you make a mistake in entering a respondent’s answer or he/she changes his/her reply, be sure that you cross out the incorrect response and enter the right answer. Do not try to erase an answer. Just put two lines through the incorrect response. Remember that if two responses are recorded for a particular question because you had not cancelled the wrong response, it may not be possible later to determine what the correct answer was. 5.11. Checking Completed Questionnaires: After you have completed an interview, you must review the questionnaire by carefully checking the answer to each question. It is important to check that you have not omitted any question, and that all responses are legibly recorded. You should review the questionnaire before you leave the centre, so that if you need to question the respondent further, he/she will still be available. After ascertaining that the final interview is successfully concluded and that all the responses are correct, you should request the main respondent to append his/her signature, the centre’s stamp, and date. You should also write any comments about the interview that you feel would clarify the answers you recorded by putting an asterisk (*) against the question number and recording the comment at the bottom of that page. In addition, if you have any doubts about how to record an answer, feel free to write a note on the questionnaire, and then check with your supervisor.
SECTION 0: ECCD Survey Control Form 5.12. The list of ECCD centres given to you gives the name of the centre selected for the survey. You must locate this centre and enter on the top-cover of the questionnaire and location details as given on the cover page of the questionnaire, regardless of whether the centre exists or not. If the centre has moved, follow the centre if it is within the same administrative location. If you cannot locate the centre, contact your supervisor. The Ministry of Education does not expect blank questionnaires from centres that exist and are operational. 5.13. The control form is the first section of the questionnaire. Enter the name of the ECCD centre and its location, i.e. administrative district, division, and municipality (if applicable), and educational zone. The main respondent is the person who will be the main source of information regardless of whether he/she directs the interviewer to other persons who might contribute some bits of information concerning the centre. The main respondent should be the headteacher of the centre, but can direct you to the headteacher of the primary school or community leaders for additional information. If the main respondent directs you to another respondent for additional information, you should return the filled questionnaires to the main respondent after the interview(s). The main respondent should append the centre’s official stamp (if available), date, and sign the questionnaire once it is completed. 5.14. At the start of the first interview, enter the date of visit, your name, title of the main person interviewed and the interview status in the boxes provided. If there are several interviewees during the visit, record only the main person for that particular visit. The main person for that visit does not necessarily have to be the main respondent for the entire questionnaire. At the close of each visit, indicate the interview status of the concluded interview. Codes and legends for the “interview status” for each visit are given in the control form. If a particular centre does not properly fit in the “interview status” categories given, you will be expected to include it under “Other, specify” and provide sufficient details to your supervisor. 5.15. To track movement of the questionnaires and ensure that all filled questionnaires are checked/edited,
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keyed and verified, each person handling the questionnaire should enter his/her name and date in the space provided at the bottom of the control form. The field editing is expected to be done by your supervisor. All filled and blank questionnaires should be forwarded to your supervisor for onward transmission to the headquarters.
SECTION 1: Identification and Basic Information on the ECCD Centre 5.16. The purpose of this section of the questionnaire is to seek identification and basic information on the centre. The enumerator should confirm from the respondent the full name of the centre, and obtain information on the address (if any) and telephone number (if any). You are supposed to note the geographical location of the centre (district, division, municipality) and type of neighbourhood. For example, if you are conducting an interview in a centre in Kiambu municipality which is located in Kiambaa division, you would record “Kiambaa” under division and “Kiambu” under municipality. Ample spaces are provided for recording the answers. 5.17. The type of neighbourhood refers to the area the school draws its child enrolment from. The type of neighbourhood should follow the guidelines given in the section on Concepts and Definitions above. Use your own judgement to describe the neighbourhood, and put down the appropriate code. Do not be tempted to use the general categorization of a district e.g. by referring to every centre in Garissa as drawing children from nomadic/pastoralist neighbourhoods. 5.18. The date the centre was established refers to the year when the first batch of children was enrolled for early childhood care and development activities. Write the date in the space provided. Do not give the date when the structures were constructed. 5.19. The ECCD centres are inspected by the Ministry of Education and recommended by the Ministry of Health before they are registered as required by law. You should ask the respondent whether the centre is registered, and enter the appropriate response (Yes or No) to Question 105. 5.20. In this survey, ownership is categorized as either private or public. A private ECCD centre is one which is owned by an individual or private company, while a public ECCD centre is one which is owned by the community but could also be getting support from other sponsors e.g. local authorities, religious organizations and NGOs. 5.21. Question 107 seeks information on the main type of service or activity undertaken in the centre. Services offered include formal education, pure day-care (e.g. crèche and play groups), Christian religious teaching, duksi/madrassa, and integrated duksi/madrassa. If a centre is providing two or more types of services, please record the service that is offered to majority of the children. 5.22. Ask the respondent whether the centre receives on a regular basis any contributions in cash or materials (other than compulsory fees and other charges demanded by the centre from parents/guardians) and record the answer under Question 108. A once-and-for-all contribution regardless of the amount is not considered regular and the contributor would not qualify to be classified as a sponsor for the purpose of this survey. 5.23. The person who manages the centre should be the one who takes day-to-day decisions on issues such as discipline of employees and children enrolled in the centre, school-feeding, other school supplies, and the quality of services provided to the children, etc. Ask the headteacher to identify the main person or group of persons who runs the centre on day-to-day basis, and record the response to Question 110. 5.24. Questions 111 to 113 relate to the parents/school committee in charge of overseeing the development of the centre and supporting and advising the centre’s headteacher. Under Question 111, ask the headteacher whether the centre has a parents/school committee, and if yes, record its gender composition in Question 112. If the centre has a parents/school committee, ask the headteacher when the committee last met, and write down the month and year and code in the appropriate boxes.
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5.25. As described under Concepts and Definitions, some centres may be attached or linked to a primary school, while some may not have any working arrangement with a primary school. Questions 114 to 116 seek information on attachment/linkage to a primary school. Ask the headteacher whether the centre is attached or linked to a primary school and record the response under Question 114. Questions 115 and 116 should only be asked if the centre is attached to a primary school. Ask the headteacher whether he/she has attended staff meetings of the mother primary school since January 1995 and record the response under Question 115. Question 116 seeks information on whether a centre attached to a primary school share the same parents/school committee. Ask the headteacher the question and record the answer in the space provided. 5.26. Question 117 seeks information on the rental arrangements of the space used by the centre. The premises/space used by the centre could be own-premises, rented, provided by the mother primary school to which the centre is attached, or rent-free in a church building, local authority social hall, parents’ employer hall, or in the open air. Ask the headteacher for information regarding the rental arrangements of the centre and record the correct code in the space provided. 5.27. Question 118 seeks information on the hours in any one normal day when the children are required to be in the centre. A sizeable proportion of the ECCD centres retain children from morning to lunch time. However, there are full-day centres, and there could also be cases where the younger ones are released at lunch hour while the older ones are retained until late afternoon. For the purpose of the survey, the latter ECCD centre should be considered as “whole day for same group of children”. If active learning ends at noon but children stay around awaiting collection by their parents/guardians, this should be recorded under the option “morning only”. Record the appropriate code. 5.28. Questions 119-122 seek information on supervision/inspection of the centre by Zonal Inspectors, local authority Nursery School Supervisors and DICECE staff. It is also possible that the headteacher of the centre might consider his/her inspector to be the headteacher of the primary school to which the centre is linked/ attached. The questions cover (a) whether the centre has ever been supervised/inspected, (b) when last supervised/inspected, and (c) how many supervisory/inspection visits have been made since January 1994 and by whom. Ask each of the questions and record the responses in the appropriate boxes.
SECTION 2: Centre’s Enrolment 5.29. This section will collect data on child enrolment during 1990-1995. Note that enrolment is for reference period 31st May of each year. Age refers to completed years. A child aged 2 years 11 months should be considered to be two years of age and recorded in the 2-year age-group column. Sex/gender refers to whether the child is a boy or girl, specified in the questionnaire as “B” for boys and “G” for girls. 5.30. In respect of Question 201, ask the headteacher to supply you with enrolment broken down by age from her/his centre’s records. For each age, show the total enrolment and for boys and girls separately. If there is no enrolment for either boys or girls for a particular age, write “0” in the respective box. For example, in the case of 1990, if there were no children aged under two years enrolled in the centre, write “0” in the box under “B”, “0” in box under “G”, and “0” in box under “T”. As the note under the table instructs, ensure that the sum of the totals in each respective age agree with total centre’s enrolment. For example, if there a total of 10 children aged under two years, 10 children aged 2 years, 3 years, 4 years, 5 years, 6 years and over 6 years, respectively, enrolled in the centre, the centre’s total enrolment should be 70. If the total in the register differs from this figure, then there must be an error which must be reconciled before entering information for 1991, and so on. 5.31. You should also assist the respondent to extract information from records held by the centre. Remember that a register showing sex and date of birth of each child for each reference year has all the information you need to complete Questions 201 and 202. If the headteacher does not keep records and cannot therefore fill the information in the required format for reference years 1990 to 1994, you should fill the totals columns for each year in Question 201. If the records are not readily available, the enumerator should leave blank copies of tables accompanying Questions 201 and 202 for the headteacher to fill awaiting
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collection. 5.32. Question 202 asks for details only for enrolment as at 31st May 1995. If the centre organizes children into groups on the basis of age, ability, or class, obtain from the headteacher the breakdown for each age. The different grades should strictly reflect on internal centre’s promotion, such that children in Grade 1 are promoted to Grade 2 on successful completion of Grade 1. If, for example, there are 15 children aged 3 years, show the breakdown of the children by sex and age, and for each grade/class. If the centre handles the children in one group, i.e. there is no grouping by grade or class, then fill only the totals row. Ensure that the totals for 1995 in Questions 201 and 202 agree. For the purpose of this survey, the splitting of the same grade into study groups or streams is considered as one grade. 5.33. Ask the headteacher to inform you where the children proceed to after completion of the highest level in this centre, and record the appropriate response in Question 203. Graduates of the centre’s highest grade/class may be prospective candidates for progression to a centre or school that caters for the next level, e.g. pre-primary units or Primary Standard One. 5.34. Compulsory school fees charged by the centres vary from centre to centre, and also between classes/grades. Question 204 seeks information on the breakdown of fees and other levies charged by the centre in respect of each class/grade. In respect of children in First Grade/Class, show the numbers in column 1, tuition fee in column 2, building fund (if annual) in column 3, uniform fee (if paid to the centre) in column 4, etc. If the centre does not demand some charges on a compulsory basis e.g. building fund, uniform fee or transport levy, write “0” in the appropriate boxes. In case the centre does not categorize total fees charged into the listed categories, put a tick in the boxes for each item covered in the total fees. For example, if the centre charges Shs 3,600 per child per year in Grade/Class 1 and the centre does not categorize total fees by the listed charges, the enumerator should enter Shs 3,600 in row 1 under the totals column. The enumerator should further probe on the types of charges covered by the total fees, and tick in columns for, say, “tuition fee” and “children’s school feeding charges” if these were the only items covered in total fees. If there is no grouping of children into grade/class in the centre, the listed fees and charges should be entered on the first row under “Year 1”. If the listed fees and charges are common for all the grades/classes, repeat the information for all grades/classes. If the centre does not charge any fees or levies, put “00” under totals column. 5.35. Question 205 solicits information on the actions the centre takes in the case of a child who fails to pay compulsory fees and charges. Compulsory fees exclude charges by the school on optional services and facilities provided to the children, e.g. food and transport. Write code “1” if a child is allowed to continue attending the centre, and code “2” if the child is sent away from the centre until the fees are paid, etc. For a centre that does not charge any fees or levies (i.e. children do not pay fees), circle 4 and code 4 in the appropriate box. 5.36. Question 206 assesses parents/guardians ability to pay the prevailing compulsory fees and charges in respect of 1994, broken down by gender. In respect of boys, for example, write in first box the number of boys who were able to pay all the compulsory fees and charges, in box 2 the number of boys who paid some of the compulsory fees and charges regardless of the amount, and in the third box those who were unable to pay any compulsory fees and charges at all. Repeat the same process in the case of girls. Ensure that the totals agree with those given in response to Question 201. 5.37. Questions 207 and 208 are on child registration fees demanded by the centre. In Question 207, ask the headteacher on whether the centre demands a registration fee before admitting a child. If the answer to the Question is “Yes”, ask the headteacher for the amount charged per child for registration, and record the answer in the boxes provided under Question 208.
SECTION 3: Staffing of the ECCD Centre 5.38. This section attempts to get a profile of the workforce at the ECCD centre, both teaching and nonteaching. 5.39. In respect of question 301 ask the headteacher to give particular of all employees at the centre as at
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31st May, 1995. Ensure that employees who are on normal leave, sick leave/off or any other absence with permission are listed. Twelve rows are provided to record a total of twelve employees. If the number is more than twelve, use a second page with the first person on the second page assuming serial number 13, etc. If the centre is attached to a primary school and a member of staff is shared by the centre and the mother primary school, include the employee’s particulars in the table, and put an asterisk (*) against his/her name. Explain such a case in a footnote under table 301. 5.40. The table given in respect of question 301 has 9 columns. In the first column, the serial number has already been inserted and you need to do nothing about it, except in respect of a centre with more than twelve employees. Put the full name of the employee in the second column. Two names will suffice, e.g. David B. Lion. In third column give the year of birth of employee, the month and day of birth are not necessary. In fourth column write “M” or “F” to indicate the sex of the employee as either male or female, respectively. In fifth column write the date when each employee was first employed in this centre. The date should show month/year e.g. 06-1995 representing June 1995. Column 5 calls for information on the occupation of the employee. Write “teacher”, “cook”, “driver”, “cleaner”, “clerk”, etc. to indicate the main occupational categories of the employee at the centre. Any work done outside the centre, i.e. not related with the centre, should not be reported. 5.41. Columns 7 and 8 seek information on how much the employee is occupied at the centre. In column 7, put “F” if the employee works full-time and “P” if the employee works part-time. In column 8, put down the average total number of hours worked per week by the employee. In the last column, ask the headteacher to supply you with gross annual salary for each listed employee. Gross salary is the sum of wages or salaries from employment in the centre plus all associated allowances and benefits (e.g. house allowance) before regular deductions (income tax, social security, service charges, pension contributions) are made. If a teacher is on attachment at the centre and therefore only receiving a stipend, record the stipend in the “gross salary” column and put an asterisk (*) against the salary paid. Explain such a case in a footnote under table 301. 5.42. Question 302 seeks further details on teachers, which should be solicited from each individual teacher. The table below the question has 10 columns. The serial number of the teacher required in the first column should be the same as the one entered for the teacher in table 301. If in Question 301, Mr. David B. Lion was listed under serial number 5, write “05” in the first column and “Mr. David B. Lion” in the second column. In third column write the highest level of formal education the teacher attained and enter the appropriate code. Thus for a teacher whose highest grade in formal education was Kenya Certificate of Secondary Education/Cambridge Overseas School Certificate or London General Certificate of Education (GCE) - Ordinary Level, you should code “4” standing for the Secondary Education code. 5.43. In the fourth column, write down the highest teacher training certification the teacher has received at professional teacher training colleges, and enter the appropriate code in the particular teacher’s row in the table. Columns 5 through 8 seek information on ECCD-specific training. Various training programmes have been and are being offered including those under DICECE, KHA, PCEA, Montessori, and National Youth Service (NYS). The various training institutions offering this type of training and their accompanying codes are given at the top of the column. Ask the teacher on the highest ECCD course that he/she has undergone and completed, and write down the appropriate code. There are some categories of ECCD-specific training programmes which are not listed under column 5. These training programmes are of interest to this survey and are to be listed under “other, specify”. For example, if a teacher reports to have attended the six-month baby-sitters training course at Njoro, classify him/her under the “other, specify” category and write down “baby-sitter course, Njoro” in column 5. If the teacher reports to have attended more than one course, record the course that the teacher considers to be the highest. 5.44. ECCD-specific training programmes conducted by various institutions have different durations as outline in the section on Concepts and Definitions. In column 6, record the appropriate code for the duration of the training the teacher considers to be the highest. 5.45. In column 7, write down the name of the person or agency that paid the fees and other expenses for the teacher’s ECCD-specific training. In the footnote to the table, various sponsors are listed. However, the
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list is not exhaustive. Third parties who sponsor a programme which is not earmarked to the particular teacher should not be recorded. If a teacher attended a training programme sponsored by DICECE, but is aware that the DICECE training was, say, funded by UNICEF, the appropriate sponsor for the purpose of the survey is DICECE. 5.46. In column 8, write down the year in which the teacher completed the highest ECCD-specific training. Enter the last two digits of the year that the highest grade was completed. If, for example, the year was 1990, enter “90”. Teachers who are still undergoing training during school holidays should have their year of completion entered as “ongoing” in column 8. Columns 9 and 10 seek information on teaching experience. In column 9, write down the total number of complete years of experience in ECCD centres, including the current employment in the centre. For those teachers who have had intermittent ECCD-specific teaching experience, enter the total number of completed years spent in teaching in the ECCD centres. In Column 10, write down the number of years completed in non-ECCD teaching activities e.g. in primary school and secondary schools, but exclude years spent teaching in non-educational institutions, say, a secretarial college. 5.47. Data required for question 303 are for the study of turnover in employment at ECCD centres during 1990-1995, i.e. new appointments, losses (retirements, resignations, deaths, dismissals, etc), and the main respondent will be the headteacher of the ECCD centre. The information is to be recorded in the table provided, which is divided into six blocks. Each block is in turn divided into three columns for entry of data on males and females. In block 1, enter the total number of teaching staff as of 31st December for reference years 1990 to 1994, broken down into males and females. However, for the year 1995 the headteacher should give the number of teaching staff as at 31st May, 1995. In block 2, enter the number of new appointments during the year. Enter “0” if there were no new appointments. In the third block, enter transfers from your ECCD centre to another ECCD centre under the same employer during the year in question. If there were no transfers of either male or female teachers, write “0” in all the three boxes. The last three blocks should be filled with information on resignations, retirements or other losses during each reporting year. It is important to note that “other losses” include deaths, dismissals and desertions. However, teachers on normal leave, sick leave, training, maternity, or any other officially-sanctioned absence should not be considered as losses.
SECTION 4: Financing of the ECCD Centre 5.48. Although the objective of most ECCD centres may be to provide a community service rather than operating for profit, it is important to find out how the centres manage their finances. In Question 401 ask the headteacher whether the centre received any grants/aid during calendar year 1994, and record the response in the box provided. If Yes to Question 401, put down the amounts received against the source of funds/sponsor and purpose of the grant/aid in the table accompanying Question 402. The grants/aid received in 1994 but not yet utilized should also be included. 5.49. In Question 403 ask the headteacher to give a breakdown of operating costs during calendar year for the items listed in the table. The line items listed are teachers’ salaries, other workers’ remuneration, children’s food, maintenance of children’s transport, etc. The headteacher might not be in a position to provide expenses by individual line items. In this case, you are advised to record the total operating costs, and probe further to see whether it is possible to get operating costs for each line item. 5.50. Question 404 seeks information on existing facilities. In column 2, fill in the quantity of each facility, i.e. land (in hectares), number of classrooms, staff rooms, teachers’ houses, classroom chairs, classroom desks, classroom benches, classroom blackboards, and school bus/vehicle. The quantities of other listed facilities that are lumped together are not required. Column 3 seeks information on the current market value of each of the listed centre’s facilities, i.e. how much it would cost to put up or purchase the same facility today. However, such a value is difficult to obtain since (a) there may be no documentary evidence, i.e. records, (b) some centres took a long time to complete and the quality of the data would therefore be affected by price changes over time, and (c) some of the materials and labour were contributed free and their value is not known. To overcome this valuation problem, the interviewer should ask the respondent how much it would cost today if the respondent was to put up an identical facility, and enter the current market value of each listed facility in column 3. In the case of shared facilities, especially for centres attached to a primary school, record the
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proportional costs based on the area occupied by the ECCD centre vis-à-vis the primary school, if and only if the primary school and the centre are constructed using same materials. If the centre is constructed of different materials and uses its own facilities within the primary school, it should be valued as a stand-alone facility. Finally, in case of work-in-progress, ask for market value of completed works or use quantity surveyor costs, if available. The current market value of each facility entered in column 3 should be distributed in columns 4 to 10, by source/sponsor. 5.51. Ask the headteacher whether there are plans to improve the centre’s facilities and/or services within the next two years, and record the answer in the appropriate code under Question 406. If Yes to Question 406, tick the line items which are to be expanded or improved in column 2 of the table accompanying Question 407. In column 3, give the approximate number (where applicable) of the facilities/services for the line items ticked in column 2. Against each facility ticked in column 2, give an estimate of the financial requirements in column 4, and the name of the anticipated main sponsor in column 5.
SECTION 5: School Feeding 5.52. Children’s performance is enhanced by proper and regular feeding. This section attempts to investigate the extent to which children are fed during their stay in the centre. The source of food/drinks is also important. Children could carry food from home (i.e. provided by parents); or would be fed by the centre from food purchased by the centre from compulsory fees; the school could make school food fund optional; the WFP could assist the school, or feeding could be organised by the National Feeding Council; or parents could contribute and cook food at the centre. 5.53. Question 501 seeks information on whether children eat or drink anything, excluding water, during their daily stay at the centre. These include food and drinks carried by children from their homes and food provided in the centre. Answer “Yes” if the children eat or drink anything during their daily stay in the centre and put the appropriate code in the space provided. If the children eat or drink something on a regular basis, then answer Questions 502 to 507. If not, proceed to Section 6 of the questionnaire. 5.54. In the case of Question 502, ask the headteacher to give you information on how many times the children eat or drink anything during the day, and record the answer in the space provided. In the centres where children take food or drink during the day, indicate the party that finances or provides the food, and record the answer under Question 503. 5.55. Question 504 seeks information on the types of food/drinks that the children eat or drink at each feeding time. These include food and drinks carried by children from their homes and food provided in the centre. You have been given three possible choices of feeding times during the day, i.e. morning break, lunch break and afternoon break. You have also been given 12 types of possible foods/drinks that the children would take at each feeding session. You should record as may foods as possible that the majority of children take during each feeding session. If, for example, during lunch break the children take “githeri” with meat and vegetables, tick numbers 4, 6 and 8 along the lunch break row. Githeri is maize and beans stew, traditional among the Kikuyu. This is distinct from mukimo, a mix of potatoes, spinach, pumpkin leaves and maize pounded together to a mash texture. 5.56. In Question 505, ask the headteacher to provide you with an answer as to whether there is any food prepared in the centre, and record the answer accordingly. If there is food prepared in the centre, enquire on the main type of cooking fuel that is used by the centre and record the answer appropriately under Question 506. 5.57. In the case of Question 507, ask the headteacher whether the centre receives school milk (Nyayo milk) at least once a week, and record the answer in the space provided.
SECTION 6: Health Activities 5.58. Young children are susceptible to many illnesses, some of which can result with permanent damages.
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Prevention of such illnesses is an important aspect of care of children. Another important activity is to monitor whether all the children are growing normally. This section attempts to collect data for the study of growth process of children and preventive care. 5.59. Immunization: A fully immunized child will have been given Bacille Calmette-Guerin (BCG) against TB, polio (four inoculations), DPT (three inoculations), and measles. It is important to know the role the centre plays to ensure that its children are fully immunized. Questions 601 to 603 seek information on centre’s involvement in immunization. Ask the respondent whether the centre normally asks for production of health immunization record card when children first apply for admission, and record the answer appropriately. 5.60. In the case of Question 602, ask the respondent on the total number of children who were admitted in January 1995 who were fully immunized, and record the answer appropriately. Record “000” if no child was fully immunized. Do not leave blank. Question 603 seeks to find out actions taken by the centre in case of a child who applies for admission and is not fully immunized. Record the appropriate code in the space provided. 5.61. Growth Monitoring and Promotion: Continuous surveillance of children to keep track of the prevalence of stunting or wasting is very crucial if we are to develop a healthy population. Growth monitoring is the regular collection of data on weight and height of children at different ages to find out whether they are following a normal growth pattern. Interventions will be required if there is a noted increase in malnutrition. Malnourished children may also require iron and vitamin A supplementation. In addition to immunization and growth monitoring, regular medical check-ups are also important. Some of the key areas that need regular medical check-ups are eyes and ears. 5.62. In the answers table to Question 604, ask the headteacher whether the centre has ever participated in any of the activities, namely, growth monitoring, iron supplementation, vitamin A distribution, de-worming and eye/ear checks. If the headteacher reports that an activity had been carried out, record in the next two columns against the activity the date it was last provided and the code for the health provider. 5.63. In the case of Question 605, ask the headteacher to give you the distance (in kilometres) to the nearest facility, and record the answer in the space provided. In this survey, the health facilities are hospitals, health centres, dispensaries or clinics, but exclude private practitioners. 5.64. Disabilities: Some children may be slow learners due to presence of a disability. Disability is the limitation in an individual to perform an activity in a manner which is considered to be normal. Difficulties in either seeing, hearing, speaking, moving legs, moving arms, and learning comprehending/recalling are all defined as disabilities. A disability could be mild or profound. In this survey we shall not attempt to categorise between profound and mild disability. Note that some disabilities can be corrected. For example, difficulty in seeing could be corrected through prescription of eye glasses. Also note that some people could be suffering from several disabilities. 5.65. Six types of disabilities are given in answers table to Question 606. Ask the headteacher to give you the number of, say, boys with difficulties in speaking, and record the number in the appropriate box. Repeat the questions for girls. If a child has more than one disability, count him/her in as many disability categories as he/she has. For example, a boy with difficulties in hearing, seeing and speaking should be counted three times.
SECTION 7: Centre’s Facilities 5.66. Ask the headteacher whether the centre owns the land it occupies and record appropriately under Question 701. 5.67. Construction Materials of the Main Structure: For the roof-type under Question 702, pick the relevant option and code appropriately. For the wall-type, pick the relevant option and code appropriately. Lastly, for the floor-type, pick the main material used to make the floor and code accordingly. Concrete roofs are mainly in pre-schools housed in a flat/apartment building.
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5.68. Source of Water: Ask “What is the main source of water?” This is the source from which the centre draws its water for most part of the year. Pick the main source of water out of the listed options and put down the corresponding code under Question 703. If the main source of water is not among the sources listed, specify it under “other, specify” and code 9. The listed main sources of water are: - Piped: Indicate whether piped water is provided inside the centre’s compound. - Well: A man-made shaft dug in the ground from which water is obtained. Water is drawn using
buckets. - Bore-hole: Same as the well, but deeper than a well and has pump for drawing the water into a
tank, buckets, etc. - River/Stream: It is a large natural body of water flowing in its own bed. - Dam: A reservoir formed by building a barrier across a river to hold back water and controls its
flow. - Jabias: Rain water harvested from any catchment into a hole/tank and used for domestic purposes. 5.69. Toilet Facilities: Ask “Where do children of this centre go for toilet?” Pick the relevant option and write its corresponding code in the space provided under Question 704. Note that a bucket latrine is a bucket placed in a residential area used for human excreta. It is emptied regularly. This type of waste disposal is now rare but can still be found in some urban estates. It should be noted that flush toilet is the one that uses water whether or not connected to a septic tank or sewer. Pit latrine is a hole dug in the ground covered with stone or wood with a small hole for waste disposal. 5.70. In answer to Question 705, record in the space provided the number of toilet stalls (sheds) used by the centre’s children. 5.71. Main Type of Lighting: Enter the appropriate code for lighting used in the classrooms under Question 706. Note that paraffin lamps include pressure lamp and Karabai (one made out of tin), etc, and should be coded 3. Please note that “solar” refers to harnessed sunlight. 5.72. School transport refers to transport that is used to ferry children, mainly to and from home. Record the appropriate code in the space provided under Question 707.
SECTION 8: General Remarks 5.73. The section seeks some general comments from the headteacher of ECCD centres for assisting in future planning of ECCD services. The interviewer should give the headteacher or the main respondent this section of the questionnaire to give general comments on problems faced in running ECCD centres and possible solutions.
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DISTRICT CODES District District/Municipality Code Kilifi district 102Mombasa municipality 106Nyandarua district 201Thika Municipality 206Machakos district 301Nairobi 401Nakuru Municipality 506Eldoret Municipality 507Uasin Gishu district 509Nakuru district 511Kericho district 512Kitale Municipality 513Narok district 516Kakamega district 603Kisumu district 701Kisumu Municipality 702Garissa district 801 Source: Ministry of Education, Kenya National Examinations Council, “Examination Codes for Districts and Municipalities”.
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ANNEX 8: SURVEY QUESTIONNAIRE
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REPUBLIC OF KENYA
MINISTRY OF EDUCATION
SURVEY OF EARLY CHILDHOOD CARE AND DEVELOPMENT (ECCD) CENTRES CONFIDENTIALITY Information supplied in this questionnaire is treated as confidential and its use will be restricted to statistical and planning purposes only. SCOPE The survey will be conducted in all selected ECCD centres. No substitution of an ECCD centre will be allowed. IMPORTANT CAUTION This questionnaire is divided into several subject specific sections. Ensure that you supply answers to all questions. Giving of inaccurate, false or incomplete data, deliberately or otherwise in any part of this questionnaire will lead to wrong conclusions and inaccurate planning. FOR HEADQUARTERS USE ONLY Name of ECCD Centre ________________________________ District__________________________ Division____________________________________________ Zone ___________________________ Name of Enumerator _________________________________ Name of Supervisor________________
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MINISTRY OF EDUCATION
SURVEY OF EARLY CHILDHOOD CARE AND DEVELOPMENT (ECCD) CENTRES
ECCD SURVEY CONTROL FORM
Name of ECCD Centre ____________________________________ Name of Main Respondent __________________________________ District _________________________________________________ Title of the Main Respondent ________________________________ Division ________________________________________________ Signature of Main Respondent _______________________________ Municipality (if applicable) __________________________________ Date of Main Respondent’s Signature __________________________ Zone __________________________________________________ Location ________________________________________________ Interviewer Visits 1 2 3 Date of visit Interviewer’s Name Title of Main Person Interviewed Interview Status* Next Visit: Date/ Time *LEGENDS FOR INTERVIEW STATUS 1 Completed 6 Centre could not be located 2 Partial 7 Postponed 3 Centre closed temporarily 8 Relevant personnel could not be contacted 4 Centre permanently closed 9 Other (specify) 5 Refusal: resisted after repeated attempts Field edited by: Office edited by: Keyed in by: Verified by: Name Date
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SECTION 1: IDENTIFICATION AND BASIC INFORMATION 101 Name of ECCD Centre ........................................................................................................................................................... Address ....................................................................................................................................................................................... Telephone Number: ................................................................................................................................ 102 District ....................................................... /_/_/_/
Division .................................................................................
Municipality (if applicable) ................................................... /_/_/_/ 103 Type of neighbourhood: Urban Slum=1 Other Urban=2 Pastoral=3 Plantation=4 Settled agriculture=5 /_/ 104 Year the Centre was established ......................................................................................... /_/_/_/_/ 105 Is the Centre registered? Yes=1 No=2 /_/ 106 Ownership status of the Centre Public=1 Private=2 /_/ 107 What is the main service/education offered by the Centre? Formal education=1 Pure day-care=2 Christian religious teaching=3 Duksi/Madrassa=4 Integrated Duksi/Madrassa=5 Other, specify=6 /_/ 108 Over and above the compulsory fees and other charges paid by parents/guardians, does the Centre receive any cash or material assistance from other sources on a regular basis?
Yes=1 No=2 /_/ 109 If Yes to Question 108, who was the main sponsor (source of assistance) in 1994? Parents/Community=1 Religious organisation=2 Private individual(s)/Company=3 Plantations, estates and other companies=4 County/Municipal/Town/Urban council=5 Central Government=6 NGO=7 Other, specify=9 /_/
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110 Who manages the Centre on a day-to-day basis? Headteacher-employee of the Centre=1 Headteacher-owner=2 Committee=3 Headteacher of primary school=4 Religious leader=5 Other, specify=9 /_/ 111 Does the Centre have a parents/school committee? Yes=1 No=2 /_/ 112 If the Centre has a parents/school committee, what is its composition? Males /_/_/ Females /_/_/ Total /_/_/ 113 If the Centre has a parents/school committee, when did the committee last meet? (month/ year) /_/_/_/_/ 114 Is the Centre attached or linked to a primary school? Attached=1 Linked=2 Not attached or linked=3 /_/ 115 If the Centre is attached to a primary school, has the headteacher of the Centre attended any staff meeting of the primary school since January 1995? Yes=1 No=2 /_/ 116 If the Centre is attached to a primary school, do the Centre and the primary school share the same parents/school committee? Yes=1 No=2 /_/ 117 From where does the Centre operate? Own premises=1 Rented premises=2 Shared classrooms with a primary school=3 Uses church=4 Local authority social hall=5 Parents-employer hall=6 In the open or under a tree=7 Other, specify=9 /_/ 118 Could you indicate how long the children stay in the Centre? Whole day=1 Morning only=2 Afternoon only=3 Other, specify=9 /_/ 119 Whom do you consider to be your authorized supervisor/inspector? Primary school inspector=1 Zonal inspector=2 DICECE staff=3 Nursery school supervisors=4 Headteacher of the primary school to which the Centre may be linked/attached=5 Other, specify=9 /_/ 120 Have you ever been supervised/ inspected? Yes=1 No=2 /_/ 121 If Yes to Question 120, when were you last supervised/inspected? (Month/year) /_/_/_/_/ 122 Who made the most supervisory/inspection visits since January 1994? No visits=1 Schools Inspector=2 Zonal Inspector=3 DICECE staff=4 Headteacher of the primary school to which the Centre is linked/attached=5 Nursery school supervisor=6 Other, specify=9 /_/
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SECTION 2: ENROLMENT 201 What was the Centre’s enrolment as at 31st May of each year, for the last 6 years by age and sex of the child? Year Age of children in completed years Under 2 years 2 3 4 5 6 Over 6 Total B G T B G T B G T B G T B G T B G T B G T B G T 1990 1991 1992 1993 1994 1995 * Ensure that totals are consistent. 202 What was the Centre’s enrolment by grade or class as at 31st May 1995 by age and sex of child? Grade/class Age of children in completed years Under 2 years 2 3 4 5 6 Over 6 Total B G T B G T B G T B G T B G T B G T B G T B G T 1 2 3 4 Total * Ensure that totals are consistent. 203 After the children complete the highest grade/class offered at this Centre, what type of educational institution do the graduates proceed to? Pre-primary=1 Primary school (standard 1) =2 Other, specify=9 /_/
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204 Enter details in Kenya Shillings (Shs) of fees and other levies paid by parents per child per year for reference year 1994. Enter “00” if a particular column does not apply to your Centre. Grade/class Number of
Streams in each
grade/class
Tuition fees Building fund
Uniform fees
Textbooks and
stationery charges
Children’s school feeding charges
Centre’s transport
levy
Repairs & maintenance
fund
Other annual fees & charges*
Total per student per
year
1 2 3 4 * Other annual fees & charges may include caution money, PTA compulsory funds, games kit, activity fee, medical fees, etc 205 Which of the following actions is taken against a child who fails to meet part or whole of compulsory fees and charges? Allowed to continue at the Centre=1 Sent away from the Centre=2 Assisted through Harambee/ donations/ sponsorship=3 Children do not pay fees (i.e. not applicable) =4 Other action, specify=9 /_/ 206 Give a breakdown of the number of children by ability to pay compulsory fees and charges as at the close of 1994. STATUS Boys Girls Total Completed Made partial payment Made no payment at all Total 207 Does the Centre charge a registration fee? Yes=1 No=2 /_/ 208 If Yes to Question 207, how much is the registration fee per child? KShs /_/_/_/_/
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SECTION 3: STAFFING 301 Could you supply particulars of all employees, including both teaching and nonteaching staff, working for this Centre as at 31st May 1995. Include staff on leave, sick, or undergoing in-service training as at 31st May 1995. Serial Number Name of
employee Year of birth Sex (M/F) Date of
appointment (month/year)
Main type of work
Status of work: Full time (F) Part-time (P)
Hours worked per week
Gross salary per month
(KShs) 1 2 3 4 5 6 7 8 9 10 11 12 * Put a note if the employee is shared by the Centre and the mother primary school, if applicable.
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302 Please give particulars of the Centre’s teaching staff as at 31st May 1995. Interview each teacher to ensure accuracy of responses. Include staff on leave, sick, or undergoing in-service training.
Serial Number (The same number used in Question 301 above)
Name Highest educational attainment
TRAINING TEACHING EXPERIENCE (YEARS)
Below CPE=1 CPE/KCPE=2 KJSE=3 “O” Level/ KCSE=4 “A” Level=5 University graduate=6
Highest teacher training attained
HIGHEST ECCD-SPECIFIC TRAINING
None=1P4=2 P3=3 P2=4 P1=5 S1=6 Approved teacher=7
Training Programme/course
Duration Name of sponsor***
Year of completion
ECCD related (including at this
Centre)
Other teaching experience
None=1DICECE=2 KHA*=3 Montessori=4 Ministry of Culture=5 PCEA=6 NYS=7 Islamic Integrated=8 Other, specify=9
N/A**=1 Five weeks=2 One year=3 Two years=4 Other, specify=9
* KHA= Kindergarten Headmistresses Association ** N/A refers to a teacher who has had no ECCD-specific training *** Sponsors include Local Authorities, Religious Organisations, Company, the Centre itself, DICECE, parent/self, and private individuals.
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303 Please give information on teaching staff as required in the table below. Include teaching staff on leave, sick, or undergoing in-service training. Year Total number of teaching staff on 31st
December New appointments during the
year Transfers during the
year Resignations during the
year Retirements during the
year Other losses*
M F T M F T M F T M F T M F T M F T1990 1991 1992 1993 1994 1995 * Other losses include deaths, dismissals, desertions, etc. SECTION 4: FINANCING 401 During 1994, did the Centre receive any grants/aid in cash or kind (other than compulsory fees paid by parents/guardians)? Yes=1 No=2 /_/
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402 If Yes to Question 401, please write down the amount received during 1994 in KShs against each of the listed purpose and source, including grants/aid received but not yet utilized. PURPOSE SOURCE
Central Government
Local authority
PTA/ Community
Religious organization
Private company/individual
NGO/Donor agency
Other source
Total
1 Building 2 Furniture and Equipment 3 General Maintenance 4 Textbooks 5 Other teaching or learning
materials
6 Other purpose (please specify)
1 2 3 4 TOTAL
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403 Please give operating costs in KShs during 1994 for each of the following items: Line Item SOURCE OF FUNDS Central
Government Local authority
PTA/ Community
Religious organization
Private company/individual
NGO/Donor agency
School fees/levies
Other source
Total
1 Teachers’ salaries 2 Other workers’
remuneration
3 Children’s food 4 Maintenance of
children’s transport
5 Teachers’ teaching materials
6 Rent, electricity, telephone and water
7 Other, specify Total
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404 Please give estimated current market value of existing facilities in the ECCD centre in KShs for each of the listed facilities by the appropriate sponsor.
Centre facilities Quantity (for land put area in hectares)
Current market value
(KShs)
Indicate the amount contributed by each sponsor for each facility (in KShs) Parents/Community Local
Authority Religious
Organization NGO Private
company/individual Plantations and other
estates
Other sponsor, specify
Land Classrooms Staff rooms Teachers’ houses Classroom chairs Classroom desks Classroom benches Classroom blackboards School bus/vehicle Other structures (e.g. kitchen, toilet, etc)
Other major construction (e.g. swimming pool, etc)
Cabinets and drawers Teaching and learning aids Games/playing equipment Kitchen equipment and utensils (cooker, jikos, plates, spoons, cups, pots, pans, knives, etc)
Other furniture and equipment, specify below:-
1 2
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405 During 1994, did parents/community contribute free labour for the development of this Centre? Yes=1 No=2 /_/ 406 Do you have any plans to expand or improve your Centre’s facilities or services within the next two years? Yes=1 No=2 /_/ 407 If Yes to Question 406, what are your priority areas? FINANCING PRIORITIES Tick where
applicable Approximate number, if applicable
Estimated financial requirements
Name of main anticipated sponsor
Training of teachers Building classrooms Building teachers’ houses Increasing teachers’ salaries Increasing other workers’ salaries Introducing children’s feeding Introducing children’s transport Teaching materials and playthings
Furniture and equipment Other, specify: 1 2 3 4 408 Does your Centre operate its own bank account? Yes=1 No=2 /_/
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SECTION 5: SCHOOL FEEDING 501 Do the children eat or drink any meals, snacks or drinks during their stay in the Centre? Yes=1 No=2 /_/ 502 How many times each day do the children eat or drink any food or drink? /_/ 503 Who normally provides the food or drinks or snacks? Children carry food from home=1 By the Centre from compulsory fees=2 By the Centre from optional fees=3 World Food Programme=4 National School Feeding Council=5 Local church=6 Community=7 Other, specify=9 /_/ 504 What type of food or drinks or snacks do the children usually eat or drink at each meal break? Tick where applicable. Time TYPE OF FOOD/DRINK
1 2 3 4 5 6 7 8 9 10 11 12 Morning break
Lunch break
Afternoon break
Milk=1 Uji (porridge)=2 Tea/fruit juice=3 Githeri=4 Rice=5 Vegetables=6 Ugali=7 Meat=8 Fruits=9 Bread=10 Biscuits=11 Other, specify=12 505 Does the Centre prepare any food or drink on the premises (in a kitchen or open air)? Yes=1 No=2 /_/ 506 If Yes in Question 505, what is the main type of cooking fuel used by the Centre to prepare children’s food? Firewood=1 Charcoal=2 Kerosene=3 Gas=4 Electricity=5 Other, specify=9 /_/ 507 Does the Centre receive milk under the School Milk Programme at least once a week? Yes=1 No=2 /_/
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SECTION 6: HEALTH 601 Does the Centre normally ask for production of health immunization record card when children first apply for admission? Yes=1 No=2 /_/ 602 How many children who were admitted in January 1995 were fully immunized? /_/_/_/ 603 What action does the Centre take in case of children who apply for admission and are not fully immunized? Admit and no action=1 Refuse admission=2 Admit but alert parents/health personnel=3 Other action, specify=9 /_/ 604 Have any of the following health promotion and/or intervention activities listed in the table below been carried out in this Centre between 1990 and 1995? Answer for as many activities as have taken place. ACTIVITY Whether this Centre participates
Yes=1 No=2
When was it provided last? (month/year) Who was the health provider?
Growth monitoring Vitamin A supplementation Iron supplementation De-worming Eye check-up Ear check-up Other, specify 1 2 3 Health provider: Central Government clinic/dispensary=1 Local authority=2 Missionary clinic/dispensary=3 Private doctor(s) =4Religious organisation=5 NGO=6 Other, specify=9 605 How far is the nearest health facility (hospital, health centre, dispensary, or clinic) from this Centre in kilometres? /_/_/
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606 In the table below, give the number of children who were suffering from the listed disabilities in June 1995. Sex Number of children with difficulty in: Mentally handicapped Seeing Hearing Speaking Moving legs Moving hands/arms Boys Girls Total Note: In Question 606, record a child several times if he/she has multiple disabilities e.g. hearing and moving legs. SECTION 7: CENTRE’S FACILITIES 701 Does the Centre own the land it occupies either freehold or leasehold? Yes=1 No=2 /_/ 702 What are the construction materials of the main building? Roof: Iron/asbestos sheet=1 Tiles/ concrete=2 Grass/makuti=3 Other, specify=9 /_/ Wall: Stone=1 Brick/block=2 Wood=3 Mud=4 Iron sheets=5 Grass/reeds=6 Other, specify=9 /_/ Floor: Cement/concrete=1 Earth=2 Wood=3 Tiles=4 Other, specify=9 /_/ 703 From which source does the Centre get its water from? Piped=1 Stream/river=2 Borehole=3 Dam=4 Well=5 Jabias=6 Other, specify=9 /_/ 704 What is the main type of toilet facility available for use by the children? Flush=1 Pit=2 Bucket=3 Other, specify =9 /_/ 705 If the answer to Question 704 is pit, flush or bucket, please indicate the number of stalls (sheds) used by the children. /_/_/ 706 What is the source of classroom lighting? Solar=1 Electricity=2 Paraffin lamps=3 None of the above=9 /_/ 707 Does the Centre operate transportation for its children? Yes=1 No=2 /_/
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SECTION 8: GENERAL REMARKS 801 In order to assist in future planning of ECCD services, please indicate the problems you face in running this Centre. Could you also suggest practical solutions to these problems?
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ANNEX 9: REPORT OF THE PROJECT IMPLEMENTATION PLAN: MONITORING AND EVALUATION COMPONENT
187
KENYA EARLY CHILDHOOD DEVELOPMENT PROJECT
REPORT OF THE PROJECT IMPLEMENTATION PLAN: MONITORING AND EVALUATION
COMPONENT
by
John T. Mukui
Report Prepared for the World Bank and the Ministry of Education, Nairobi, Kenya
April 1996
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ACKNOWLEDGEMENTS
I thank Mr Jotham A. Mwaniki (former director, Central Bureau of Statistics) for his assistance in the preparation of the report. The draft report received useful comments from Mrs Mary Njoroge (Ministry of Education headquarters), Mrs Margaret Kabiru (NACECE), Mrs Anne Njenga (NACECE) and Mr Jimmie Katabwa (Central Bureau of Statistics).
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KENYA EARLY CHILDHOOD DEVELOPMENT PROJECT
REPORT OF THE PROJECT IMPLEMENTATION PLAN: MONITORING AND EVALUATION COMPONENT3
SECTION 1: INTRODUCTION
1.1 BACKGROUND 1. The goal of the Kenya Early Childhood Development (ECD) Project is to improve the quality of life of the young Kenyan children, particularly in the poor and disadvantaged areas. Specific goals include improvement of the quality of existing ECCD centres; improving access to ECCD services by the poor; and enhanced sustainability of past and new investments in ECCD. The Kenya Government/World Bank project consists of two core components (Improved Teacher Performance/Training; and Community Mobilization and Information, Education and Communication), and three pilot components (Health and Nutrition, ECD Community Grants, and Pre-school to Primary School Transition). 2. The Kenya Early Childhood Education Project has targeted 24 districts for its project interventions. In some districts, the project will not cover all areas within a district, but will target assistance to pre-schools in some disadvantaged areas. For example, in Kiambu, Nyeri and Nairobi, the project interventions will focus on plantations, Kieni division, and slums, respectively. To assist the Ministry of Education in selecting the areas within a district where the project interventions will be implemented, it will be necessary to compile baseline information on socioeconomic profiles of each participating district. 3. The monitoring and evaluation (M&E) activity would have four goals: (a) to track the supply of inputs in the project; (b) to monitor project outcomes e.g. increased participation especially by disadvantaged groups, and improved quality of ECCD services; (c) to evaluate the impact of the project and its components on measures of child outcomes e.g. cognitive, social and physical development; and (d) to build capacity within the Ministry of Education for data collection, analysis, processing, and utilization for informed decision-making. 1.2 TERMS USED 4. Monitoring is “the periodic oversight of the implementation of an activity which seeks to establish the extent to which input deliveries, work schedules, other required actions and targeted outputs are proceeding according to plan, so that timely action can be taken to correct deficiencies detected”4. 5. Evaluation is the systematic and objective examination of an ongoing or completed project or programme, its design, implementation and results, with the aim of determining its efficiency, effectiveness, impact, sustainability, and the relevance of the objectives. An ex-ante evaluation can also precede implementation, and is used to determine the results and accomplishments of an activity, and also serves as an important reference for the mid-term evaluation (i.e. during implementation) and ex-post evaluation (i.e. after project interventions have been completed).
3. The budget estimates and implementation timetable for the monitoring and evaluation component and special studies have been deleted. Footnote five was not in the original text. 4 See, UNICEF, A UNICEF Guide for Monitoring and Evaluation: Making a Difference, New York, 1991.
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6. The distinction between monitoring and evaluation is important, since in practice these are quite separate activities. Monitoring is a routine activity which relates directly to measurable indicators of inputs and outputs as a check for management that implementation is proceeding according to plan; while evaluation involves assessing how the project or policy measures are causing certain effects and impacts, and separating this causally from other factors influencing the effects. Monitoring and evaluation also differ in their frequency and in the extent of analysis required. Typically, evaluation occurs much less frequently and involves a much greater degree of analysis. 7. Inputs are resources provided for an activity, and include cash, supplies, personnel, premises, equipment, and training. The processes are organizational operations of a continuous and supporting nature (e.g. personnel procedures, administrative support for a project, distribution systems, information and management systems) that transform inputs into outputs. Outputs are the specific products, goods or services that an activity is expected to deliver as a result of receiving the inputs. Outcomes generally refer to people’s response to a programme. Impacts are the long-term effects of the project/programme on the people and their surroundings. 1.3 FRAMEWORK AND INDICATORS 8. The impact of the project on child outcomes can be viewed as a series of production processes involving different inputs and outputs. The ultimate output is the cognitive, social and physical development of the child. The project inputs into the child outcomes would include teaching staff (number and quality), academic curriculum, school and classroom facilities, learning materials, school feeding and health interventions, and community involvement (if enhanced by the project), among others. 9. The non-project inputs into child quality can be divided into four categories: child-level factors (age, sex, birth order, innate ability of the child, etc); household-level variables (household size, parental age, parental occupation, family income, educational status of other household members, and other indicators of socioeconomic status of the family); community-level variables (e.g. availability and quality of existing pre-school and health infrastructure); and environmental variables (e.g. climate, soils - due to their impact on incidence of disease and micronutrient deficiencies). 10. Intermediate outputs of the project would include: the total number of children enrolled, increased enrolment from disadvantaged communities, and the overall quality of ECCD services provided. Output indicators would include: increased enrolment especially for children from disadvantaged communities, improved quality of teaching materials and classroom facilities, increased levels of parental and community participation in ECCD activities, and improved coverage of immunization and feeding programmes. 11. Finally, indicators of impact of ECCD services on child outcomes would include: letter and word recognition, language and arithmetic skills, reading skills, and intelligence test scores (cognitive development); age of entry into primary school and grade progression in primary school (primary school readiness); anthropometry (weight, height, age) and sensory motor skills (physical) development; and peer group interaction and classroom participation (socio-emotional development). 12. The logical framework for monitoring and evaluation will be based on two important assumptions: that change in the relevant factors outside the control of the project will be negligible, and that there are causal linkages between inputs and outputs. The first assumption is difficult to sustain due to a host of natural factors, e.g. drought may render the best laid-down school feeding programme ineffective. 13. The causal linkage between inputs, outputs and effects (IF ... THEN relationship) assumes that the inputs are necessary and sufficient to achieve the outputs or impact. For example, the main ECD project components (health and nutrition, teacher training, improved provision of ECCD facilities, and community mobilization) are the necessary ingredients to achieving the desired child outcomes (e.g. cognitive and socio-emotional development, readiness for entry to primary school, etc). Even in cases where the internal
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logic of cause-and-effect is well developed through theory and practice, community and parental response may act to frustrate the causal logic. For example, a comprehensive child feeding programme will be expected to lead to increased enrolment from disadvantaged communities. However, if the parents then find it unnecessary to give their children breakfast and/or dinner, school feeding becomes a substitute for meals taken at home, and the overall nutritional status of the children might not change5. 14. The write-up on monitoring and evaluation will follow three steps: (a) a narrative summary of input, output and impact indicators for various project interventions; (b) listing of objectively verifiable indicators; and (c) means of verification (i.e. sources of information and data collection techniques). The indicators should be measurable, objective (mean the same to everyone), valid (measure what they claim to measure), verifiable (can be checked), and sensitive (reflect changes in the situation), hence the reference to “objectively verifiable indicators”. 1.4 CONSULTANT PERSONNEL 15. The composition of the district monitoring and evaluation team should replicate the national team, comprised of ministries of education, health, culture and social services, agriculture, and water, under the chairmanship of the District Education Officer. The national team will include lead NGOs in the sector, while the district teams will include local leaders and the NGOs operating in the participating areas. The DICECE officer, who will also be the secretary to the district team, will be responsible for the day-to-day supervision of project activities at the district level. He/she will be supported by a team of officers and data entry/coding clerks. 16. At the national level, three professionals, namely, sampling expert, systems analyst and a statistician will be required. While the systems analyst and statistician will be required during the lifetime of the project, the sampling specialist will be deployed as and when necessary. 17. The sampling specialist will be responsible for (a) constructing the sampling design to be used in selection of representative areas, control groups, and communities where the respondents will be selected from; (b) setting procedures for estimation of sample weights and sampling errors; (c) assisting the systems analyst in the computerization of sampling procedures and weights; and (d) preparing sampling chapter for the various evaluation reports. 18. The systems analyst will be responsible for (a) designing of a data flow system between the field and the project headquarters; (b) designing data entry procedures for all forms and questionnaires to be used in monitoring and evaluation; (c) training data entry personnel; and (d) designing data processing and tabulation procedures. 19. The statistician will be in charge of the monitoring and evaluation function. He will be responsible for (a) ensuring that all systems and personnel in monitoring and evaluation operate smoothly; (b) designing the various data collection instruments in consultation with the systems analyst and the project implementation team; (c) analysing data and preparing technical reports; (d) training personnel in data collection procedures and supervising data collection; (e) liaising with the project monitoring unit on progress and making recommendations on necessary actions to ensure success of the monitoring and evaluation function; and (f) preparing reports to be used in the overall evaluation of the IDA-supported project.
5 The ability of child nutrition programs to improve the nutrition of individual children depends on how households choose to allocate resources among their members. The interventions may be neutralized by reallocations of the resource away from the child; or may not be (fully) reallocated away, a phenomenon called the intra-household ‘flypaper effect’ because the transfer ‘sticks’ to the child (see, Hanan G. Jacoby, ‘‘Is There an Intrahousehold ‘Flypaper Effect’? Evidence from a School Feeding Programme,’’ The Economic Journal, Volume 112, Number 476, January 2002). Flypaper is a paper coated with a sticky and often poisonous substance for killing flies.
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1.5 CAPACITY BUILDING 20. The monitoring and evaluation function will be undertaken using a participatory approach between communities, pre-schools, and the project implementing personnel. The approach involves collecting information from the respective respondents, sharing the results of the analysis with the beneficiaries, and reorienting implementation on the basis of discussions with beneficiaries. At the pre-school and community levels, a participatory implementation, monitoring and evaluation approach will assist in generating ownership of the project, and contribute to capacity building among the Government and other implementing staff. Community capacity building includes improvement of dialogue around results, group liaison, general management, and other attributes of participatory community development. 21. At project entry, record-keeping procedures will be initiated for the purpose of improving documentation and planning capacity at the local level, as the basis for introduction of monitoring procedures, and to continuously generate data that will be used for evaluation during and after the life of the project. It is expected that the record-keeping, analytical expertise, data management systems, and the use of statistics as a basis for informed decision-making will outlive the project, thereby contributing to long-term capacity building.
SECTION 2: THE MONITORING COMPONENT 2.1 INTRODUCTION 22. Monitoring the supply of inputs, outputs and child outcomes will be done continuously, and would contain precise dates of events. The main data collection instrument would be a child card where the child-specific events will be recorded e.g. a running health and immunization record, attendance and reasons for absence from school, results of any cognitive or social assessment performed on the child, etc. Two copies of the pre-printed card will be maintained by the ECCD-centre: one copy of the card would be kept at the centre, and the other copy would be kept by the child’s parents. 23. The child card will have advantages over most data collection instruments since it will focus on the status of a particular child. For example, conventional growth monitoring is often criticised for only capturing cross-sectional “nutrition status” rather than “growth monitoring” since the data is not by individual child. The child cards will provide data that will be useful for a wide range of studies, and will enable remedial actions to be taken on an individual child. 24. The children covered by the child cards will change in the course of time. Some factors may include dropping out of the pre-school system, movement to a pre-school outside the project, movement to a pre-school within the project, death, graduation to primary school, etc. An appropriate system of updating the management information system in light of such occurrences has to be developed. 25. The second type of monitoring instrument will be the admission register, which falls under the general category of “opportunistic monitoring”6. The admission register will be used to record information on (a) the child (age, sex, immunization history, anthropometrics at admission, birth order of the index child, disability, etc); and (b) household-based data (household income, parents’ occupations, education status of other household members, etc). 26. The participating ECCD-centres will also maintain pre-school registers, which will contain information on (a) who is its main sponsor; (b) linkage/attachment to a primary school; (c) year the pre-
6. Opportunistic monitoring refers to the household- and community-level variables since the admission of the child provided the opportunity to obtain data on a host of indicators, including its primary use in understanding some of the factors behind the index child’s outcomes.
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school was established; (d) school hours (morning only, afternoon only, whole day); and (d) registration status. Continuous record of events will include (a) summaries of enrolment/attendance by age, sex, and grade (if there is grading); (b) teachers by gender, training received and when, emoluments per month, educational attainment, date of appointment, etc; (c) child feeding, growth monitoring, and health interventions conducted - e.g. de-worming, immunization, eye/ear check up, vitamin A supplementation; (d) supervisory visits to the centre; (e) physical facilities - building, land, furniture and equipment; and (f) operating costs. In short, the centre register will mainly consist of (a) summary information from the child card e.g. enrolment, growth monitoring and health interventions; and (b) pre-school-level variables e.g. teachers, teaching materials, feeding, and capital and operating expenses. 27. The monitoring system will also include project inputs e.g. finances, manpower, transportation and space, and equipment and supplies. The categories of project inputs should also be broken down by program component (e.g. teacher training, health and nutrition, etc). It is important to determine the data to be maintained, and which categories of inputs will be important for monitoring purposes. Collection of data for monitoring purposes will require the development of uniform forms for recording flows of inputs into the project. 28. The sequence of events to be followed in both monitoring and evaluation will broadly fall under preparatory and implementation activities. The preparatory activities will include (a) the study of current formats used during service delivery and for monitoring and evaluation; (b) preparation of draft questionnaires, formats for monitoring and evaluation, and computer programs to analyse the information; (c) seminar to discuss the draft questionnaires and forms and prepare final drafts; (d) pre-testing of forms and computer programs; and (e) finalization of forms and computer software. The main activities will include (a) printing and despatch of forms/questionnaires; (b) training for data collection and data entry; (c) data collection and supervision; (d) retrieval of filled forms; (e) data processing and analysis; (f) report preparation and dissemination/feedback loops; and (g) review of progress, improvement of data collection procedures, and remedial action in project implementation. 2.2 DATA COLLECTION 29. Information on child’s family background would be collected only once, either upon a child’s admission in an ECCD centre or at the time of the centre’s induction into the project (for children already enrolled in the centre). Child cards would be updated continuously, and would give precise dates of events (such as immunization, anthropometrics). Centre registers, wall charts and other summary data formats would be updated monthly. 30. Headteachers of ECCD centres participating in the project will be responsible for maintaining the child cards for each of their pupils. Centre registers and wall charts will be maintained by the headteacher or other centre’s workers. The DICECE staff at the district, divisional, and zonal levels will be used for monitoring purposes. 2.3 TRANSMISSION AND USE OF MONITORING DATA 31. Each quarter, the ECD officer or DICECE officer-in-charge would extract information from the child cards and centre registers in his/her area, and take it to the DICECE office. The information would be entered in a computerized database at the DICECE office. Every quarter, the DICECE office would transmit the information electronically to the Monitoring and Evaluation office in the MOE pre-school section, who would maintain a national database of ECCD-enrolled children and ECCD centres. It is recommended that optical scanners that recognize “bubbles” be used for data entry as it would considerably reduce the time lag between data collection and production of outputs based on the data. 32. There are several ways in which the Management Information System (MIS) could be used for district planning purposes. First, trends in enrolments by age group, socioeconomic group, and gender, could be calculated for the entire district as well as zones within the district. This would indicate progress
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that the district and its divisions were making in expanding access to and improving equity in the provision of ECCD services. Likewise, trends in immunization rates, anthropometric indicators, and child assessment indicators would provide important evidence on the progress (and weaknesses) of the project in specific areas. Comparisons of enrolment rates and other indicators across centres participating in various components of the project and those not participating in these components, with appropriate controls for other variables, would indicate the marginal effects of different project components on projects outcomes. 33. Second, a system will be set whereby the DICECE officer will supply certain aggregated information and profiles back to each of the centres in the district. For instance, centres would receive information on how their enrolment trends, nutritional status or community mobilization efforts compare against other centres in the district. The identification of an ECCD centre’s weaknesses and strengths would permit centres to deploy their resources differently or to target their ECCD services more narrowly to specific age, sex or socioeconomic groups. This is an extremely important aspect of the monitoring component, and one whose importance cannot be overemphasized. 34. Third, the national database would be helpful in evaluating the impact of specific project inputs on projects outcomes, like national enrolments, teacher quality, and participation in ECCD by low income groups. The monitoring data would also supplement the mid-term and ex-post project evaluations. To the extent that some centres reporting monitoring data would be ones where the project components would only be phased in later, one would have a control group of centres not (yet) exposed to project intervention(s). 35. Finally, monitoring and evaluation will be used as a basis for remedial action through (a) assistance and referral for individual child or pre-school where a problem is identified, and (b) to redirect the project activities where necessary. 36. The data collected will be tabulated by, say, district and participating/control areas. The district summary sheets will be shared with the respective districts. The monitoring information will be used in the quarterly project newsletter to be compiled by the project staff. The newsletter will be the main vehicle to inform the original data providers about project problems and results. Seminars will also be held once a year to discuss reports based on the data and to map out future directions. 2.4 ORGANIZATION AND MANAGEMENT 37. At the national level, the overall manager of the component would be the Senior Education Officer in charge of Monitoring and Evaluation within the MOE pre-school section. He/she would chair an M&E working group, whose membership would include representatives from NACECE, Ministry of Health, Central Bureau of Statistics, NGOs active in preschool education, and technical consultants. 38. At the district level, a steering committee for M&E would be established under the chairmanship of the DEO, and would include the District Statistical Officer (DSO), Education Officer (EO), School Inspectors, Area Education Officer (AEO), Teacher Advisory Centres’ (TAC) tutors, the DICECE M&E Officer, and representatives of parents’ committees, teachers’ committees, and NGOs. This committee would oversee all M&E activities in the district. The DSO would be an important actor in this activity, since he/she is responsible for collection and management of all data at the district level. In addition to data collection, management and analysis, the DSO will also assist in dissemination of monitoring information to the District Education Board and the District Development Committee.
SECTION 3: EVALUATION COMPONENT 39. The evaluation function will be undertaken using a variety of complementary approaches. The first activity will be the compilation of baseline information on the project areas in order to understand the opportunities and threats to project success that may emanate from particular environments. At project
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entry, baseline surveys and focused group discussions with project beneficiaries will be undertaken using participatory rapid appraisal techniques. The purpose of the focused group discussions will be to understand the status of ECCD services within the participating communities, and to generate community ownership of the project. This will also contribute to long-term sustainability of the project. 40. The second part of the evaluation function will seek to add to the stock of knowledge on the ECCD sector through (a) a census of pre-schools in Kenya, and (b) a pre-school module tagged to the national household welfare monitoring survey conducted by the Central Bureau of Statistics. 41. The evaluation function would also include action-oriented analysis of project effects and impact, and compare these with baselines, targets and objectives, and changes in control areas. It would therefore supply information on the extent to which the defined target groups will be benefitting from project interventions, in line with the assumptions underlying project design. Such evaluation will overlap with monitoring and also use the database generated by the monitoring activity. 3.1 BASELINE INFORMATION ON THE PROJECT DISTRICTS Outputs and Scope 42. The main outputs from the baseline information reports will be (a) lists of ECCD centres in the participating districts by name, location (zone), enrolment by year/sex, sponsor, year established, etc; (b) identification of specific areas, pre-schools and communities to benefit from the project interventions; (c) identification of control group areas for the evaluation component of the M&E function; and (d) introduction of the concepts of monitoring and evaluation in relation to the IDA-project. 43. The Government has created new districts since the 1989 population census. However, most of the statistics and data refer to the “old” districts. There is therefore a need to prepare data disaggregated by the current districts wherever possible. 44. One of the crucial study areas is to delimit the boundaries of the new administrative areas to avoid conflict/overlap of responsibility. It will also be important to classify different areas within a district by agro-ecological zones, as indicators of economic potential. The baseline information will consist of (a) broad statistical information e.g. agro-ecological zoning, infrastructural inventory, population, health and nutrition indicators, etc; and (b) information relating to the education sector e.g. pre-schools, primary schools, polytechnics, etc. 45. There is also need for more documentation on the structure and functioning of ECCD in the districts/municipalities. The technical report should detail the roles of the various partners engaged in the provision of services to early childhood care and development, and regulations/bye-laws governing the operations of the ECCD centres. The partners include Ministries of Health and Culture and Social Services, local authorities, religious organizations, PTA/community, among others. 46. Under each partner involved in the provision of services to ECCD centres, details will include type and level of support (e.g. provision and payment of teachers, school feeding, child health, cash grants, etc); and regulations governing registration, management, staffing, and supervision of the ECCD centres. In the case of local authorities and the Ministry of Culture and Social Services, the report should include the role of Community Development Assistants/Officers (CDA/CDO) in provision of services, and in the development and administration of ECCD centres. The report should indicate areas of mutual support/overlap between CDA/CDO, local authority Nursery School Supervisors, and DICECE staff. Other issues to be covered include coordination of supervision/inspection of ECCD centres by the various partners involved in ECCD issues, and areas that would need to be addressed to make the ECCD services more efficient. 47. The institutionalization of a data management information system will require a complete count of
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all ECCD centres in every district/municipality. The Ministry of Education field staff should liaise with local authorities, the Ministry of Culture and Social Services, and any other body that approves new ECCD centres to prepare updated lists of pre-schools. Possible Sources of Information 48. A major source of district-level infrastructure data is the District Infrastructure Inventory prepared by the District Development Officer (DDO) of each respective district, under the Rural Planning Department (RPD) of Ministry of Planning and National Development. The infrastructure inventory contains information on location, condition and utilization of infrastructure facilities. The infrastructure inventory is a valuable input in the preparation of district development plans, as the database is used to support arguments for the need to construct or maintain particular facilities in different locations and sub-locations in a district. 49. The inventory schedules are completed by the district head of the Ministry responsible for the facility being surveyed. The completed infrastructure schedules should have: (a) clear description of the nature and function of the facility, (b) location of the facility, (c) careful evaluation of the extent to which the facility is utilized, and (d) specific statements on the condition of the facility and what improvements are necessary to maximise the facility’s service delivery. 50. The facilities included in the infrastructure inventory are: (a) Roads (classified and unclassified) and airfields; (b) Primary schools; (c) Secondary schools; (d) Service and training institutions (teachers’ training colleges, Colleges of Arts and Technology or
Harambee Institutes of Technology, medical training centres, farmers’ training centres, village polytechnics, crafts centres, district development centres, etc.);
(e) Water facilities; (f) Health facilities (hospitals, health centres, clinics/dispensaries, maternity centres, nursing homes,
mobile clinics, etc.); (g) Cattle dip; (h) Livestock holding grounds and auction facilities; (i) Grain storage facilities (off-farm); and (j) Cooperative societies (coffee factories, milk collection and cooling stations, housing cooperatives,
savings and credit societies, etc.) 51. Other sources of information include the Central Bureau of Statistics (CBS). The CBS is mandated to collect data on a variety of social and economic indicators. Recent surveys include two rounds of the national household welfare monitoring survey (1992, 1994) and specialised modules on child health and nutrition, and education. The results are given by district. The CBS will also be expected to provide demographic data (total population, population age 0-6 years, population densities, etc) and other relevant information from other surveys and censuses. 52. The Farm Management Handbook published by the Ministry of Agriculture in 1983 is the most
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detailed source of information on agro-ecological zones. Although sub-division of districts has segmented the agro-ecological zones, it is possible to prepare agro-ecological maps of the new districts in the ECD Project areas using the Farm Management Handbook. 53. In the early 1990s, district welfare monitoring surveys were conducted by the Ministry of Planning and National Development with the support of UNICEF in the UNICEF’s Child Survival and Development (CSD) districts. The district reports would be useful sources of a wide variety of social indicators in the respective districts. 54. The District Development Plans (1994-96), prepared by the Rural Planning Department of the Ministry of Planning and National Development, contains data on district infrastructure and district-specific development plans to be undertaken during the Plan period. 55. The Health Information System (HIS) in the Ministry of Health collects data on incidence of disease, malnutrition, and coverage of the Kenya Expanded Programme of Immunization (KEPI). The data are given by district and province. The Division of Family Health also has a database on the incidence of diseases e.g. diarrhoea, and micronutrient deficiencies (e.g. vitamin A, iron and iodine). 56. It should be noted that none of the above-mentioned sources maintains comprehensive data on pre-schools. It is therefore the responsibility of caregivers and sponsors in the pre-school sector (e.g. local authorities, Ministry of Culture, Ministry of Education and other partners) to provide the requisite statistics on pre-schools. Responsibility for Data Collection 57. The activity will be undertaken in the first quarter of the first year of project implementation. The activity will be coordinated by the respective district education office, with active support of the members of the District Executive Committee (DEC) and the District Planning Unit (DPU). The DEC is headed by the District Commissioner (DC) and its membership is dominated by district departmental heads of each line ministry. The main objective of the DPU is to serve as a secretariat to the DEC for day-to-day coordination of planning and implementation work in the district. The members of DPU are the District Development Officer (chairman), District Statistical Officer (secretary), programme officers, physical planner, and quantity surveyor. The principal collaborators at the district level will be the District Statistical Officer, District Development Officer, and District Health Officer. The collection of information available at the ministries’ headquarters will be coordinated from the Ministry of Education headquarters. 58. Draft Outline of the District Reports Introduction Physical Description
Location and Size Topography and Ecology Administrative Units
Demographic Profile
Population Size Population Structure Population Distribution and Density
Economic Profile
Agro-ecological Zoning Land Use Patterns Major Economic Activities
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Employment Social and Economic Infrastructure
Health Facilities Educational Facilities Roads Water Supplies Electricity
Welfare Indices
Income and Consumption Profiles Indicators of Housing, Water and Sanitation Pockets of Rural and Urban Poor
Health and Nutrition
Infant Mortality Incidence of Disease Nutrition Immunization
Education
Primary School Education Secondary School Education Polytechnics
Profiles of Pre-schools
Growth in Establishment of Pre-schools Pre-schools by Type of Neighbourhood Ownership of Pre-schools Registration Management of Pre-schools Supervision of Pre-schools Enrolment in Pre-schools by sex, age, sponsor Profiles of Pre-schools’ Personnel Financing of Pre-schools Feeding and Health Interventions Inventory of Facilities (premises, water, sanitation, and source of lighting) Lists of Pre-Schools
3.2 BASIC GUIDELINES IN SAMPLE DESIGN Selection of Participating and Control Areas 59. The district baseline information will be used to select participating and control areas for assessing project impact (i.e. if what actually happened as a result of the project interventions differs from what would have happened without the project). In identifying disadvantaged areas, it is important to use observations on, say, type of housing (roofing, wall and floor materials), physical facilities, and income levels (if known). In the case of Nairobi, for example, slums could be used as a proxy for disadvantaged areas. In Kieni and Nyamira, administrative locations could be used if they have broadly similar socioeconomic profiles based on informed opinion. 60. Clear guidelines should be prepared to assist in selection of participating areas, e.g. what is a “slum” or a “plantation”. The enumerators’ reference manual for the 1995 sample survey of ECCD centres defined plantations as large pieces of land where tea, cotton, sugar, tobacco, etc are grown. In the
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plantations/estates (mainly tea, coffee, sugar, pineapple and sisal estates), the company may provide a building, hire teachers, OR provide a plot where parents/workers could put up a building and hire teachers at their own expense. A slum was defined as an informal, unplanned and overcrowded settlement, with (a) structures of temporary material, (b) poor sanitation (e.g. sewerage, water supply), (c) poor basic infrastructure e.g. access roads and health facilities, and (d) inhabited by low income households. The identified slums or plantations should also be carefully studied, as they may differ in socioeconomic development. This is especially true of plantations, where large differences may exist between plantations within the same district. 61. After identifying the disadvantaged areas in the selected project districts, the participating areas will be selected, leaving out the other disadvantaged areas as control areas. However, not all pre-schools in the disadvantaged areas may qualify for all project interventions due to differences in endowment. There is therefore need for stratification by, say, sponsor, before selection of participating pre-schools. 62. Theoretically, the participating and control areas (a) should have initial homogeneous socioeconomic profiles; (b) reactions of each group should have no influence on the other; and (c) should be responsive to the treatments (project interventions). However, common knowledge shows that no two areas can be perfectly homogeneous. In the statistical design of experiments, there are some inherent pitfalls in selection of areas for the purpose of measuring outcomes of project intervention between participating and control groups: (a) The resources provided by the project may crowd out resources currently provided by other
partners in the participating areas into pre-schools in the control areas, thereby affecting the outcomes in both participating and control groups.
(b) If communities and caregivers in the control areas contiguous to the participating areas learn about
the project interventions (e.g. health and feeding programmes), the parents in the control groups might enrol their children in the participating areas, thereby magnifying the impact of the project interventions on enrolment. Even if the participating and control areas are far apart, there could be increased enrolment in the participating areas from the neighbouring areas outside of the control groups.
(c) The educational aspects of the project components (e.g. food preparation guidelines) could filter to
pre-schools in the control areas, through personnel in the Ministry of Education and other forums of interaction between the caregivers e.g. teacher training.
(d) Due to a host of extraneous factors, progress in the control groups over the lifetime of the project
may not replicate what would have happened to the participating groups if the latter did not receive the project interventions.
(e) If the participating and control groups are close to each other, there may be compensatory rivalry
(i.e. social competition) which may motivate the control groups to attempt to reduce the effects of the project interventions by undertaking the activities directly or through other possible agencies.
(f) The intensity of project interventions among the project beneficiaries in the participating areas may
not be uniform. 63. Despite the above-mentioned problems inherent in experimental design (i.e. use of participating and control groups), the procedure has been extensively used in social research, medicine and agriculture. The problems cited above are for the monitoring personnel to take into account in the design, execution, and interpretation of the results. In addition, the results of the data from the control groups in the disadvantaged areas will assist in extending the project into new areas. If research is conducted only in participating areas, there is a danger of long-term neglect of other areas due to lack of information on other needy areas initially excluded from the project. Finally, the results based on data from the non-participating
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areas (control groups) would be useful to MOE’s efforts in seeking financial and other support from other collaborators in the provision of ECCD services. Selection of ECCD Centres for the Sample Survey 64. The unit of analysis for the survey shall be the ECCD centre. The sample survey of ECCD centres will have two main objectives: (a) to provide representative district and national estimates of various indicators related to pre-school care and education e.g. enrolment, teachers, etc; (b) to assist in designing a computerized database management system for monitoring and evaluating early childhood care and education; (c) to build capacity within the Ministry of Education for data collection, analysis, processing, and utilization for informed decision-making; and (d) to measure project outcomes by comparing progress through occasional surveys on participating and control groups. Since a common questionnaire will be administered on both sample frames, the sample selection would need to be created simultaneously. 65. The first activity in the selection of the national sample will be the creation of a sampling frame, by compiling complete lists of ECCD centres from all districts and municipalities showing the following information: name of ECCD centre, Division and Zone in which the centre is situated, sponsor, and address. The list from each district/municipality will then be organized by reported sponsor. The groupings by sponsor will then be treated as strata for the purpose of sample design. The second step will be to distribute the recommended total sample of ECCD centres between the districts and municipalities using a common sampling fraction (e.g. 10%). 66. To monitor project outcomes, ECCD centres will be selected using a purposeful sampling design that is intended to characterize service delivery in different environments and management/sponsorship systems. 67. At the beginning of project implementation, areas will be delineated by socioeconomic profiles. For example, the project will provide support in slum areas of Nairobi. It would therefore be necessary to identify all the major slum areas within the boundaries of Nairobi regardless of whether they will be included in the project. The slum areas which will not be included within the project will form the control groups in the sampling design. In Kieni division of Nyeri district, the selection of administrative locations could be the first stage, while administrative divisions could be used in, say, Nyamira district. Area selection is preferable to simple random selection since it will reduce travel expenses when planning and executing the survey. A complete list of all ECCD centres in the representative and control group areas will constitute the sampling frame. 68. The required sample of ECCD centres within the selected plantations, clusters, locations or divisions will be selected through stratified random sampling using the reported sponsor as strata. A higher sampling fraction compared to the national sample, say, 20%, will be used on the lists of ECCD centres in the participating and control groups areas. The selected number of ECCD centres in the participating and control areas should be large enough to ensure a sufficient number of children by single years (2, 3, 4, 5, 6, >6) in each study district/area to allow for analysis of project outcomes by age cohort. 69. Some ECCD centres may be duplicated in the national sample and in the samples drawn from the participating and control areas. Such centres will only be interviewed once during field data collection. However, data from the national sample and the participating/control areas will be analysed separately. 70. The sample survey will generally replicate the survey instruments used in the 1995 sample survey. However, the questionnaire and the enumerators’ reference manual will be amended in light of the experience gained in the field and during data processing. In addition, it is important to (a) prepare working definitions of some key concepts (e.g. an ECCD centre and sponsor) as this would be important in selecting ECCD centres that would benefit from the project interventions; and (b) prepare an accurate list of all ECCD centres in the participating districts.
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71. The national survey will use demographic data from the 1989 population census to compute, say, enrolment rates. However, since it will not be possible to estimate population in, say, plantations (in Kiambu) or slums (in Nairobi), enrolment rates in the participating and control group areas cannot be computed. 72. During the life of the project, some operating ECCD centres may close while new ones may be started. The sample design must therefore allow for entry and exit of centres from the initial sample frame. However, entry and exit are also outcomes that need special studies, since they may be due to the project interventions. For example, a pre-school in a participating area which does not receive project support for not meeting the inclusion criteria may experience an exodus of enrolled children to the supported pre-schools, or increased demand for pre-school education may make it necessary to start new pre-schools if the existing facilities prove inadequate. Selection of Participating Communities 73. A community is defined as a body of people organized into a political, municipal or social unit, or a body of persons living together and practising community good. In this project, the ECCD centre is taken as a community good. 74. Communities will be selected for the project interventions and for the monitoring and evaluation function. After the ECCD centres are selected, their immediate catchment areas will be taken to represent the community. During project entry, participatory rapid appraisals will be undertaken to determine the status of pre-school education in the respective communities, current problems encountered, plans to solve the problems, and how the communities intend to address those problems. The appraisals will target community leaders, headteachers of pre-schools, pre-school committees, and headteachers of primary schools, and will mainly be based on focused group discussions. The focused group discussions will be held in participating areas, and exclude the control areas. Selection of Households from the Participating Communities 75. The sample for the community-based household survey will have two components: (a) households in participating communities with pre-school age children, whether in- or out-of-school, and (b) households with pre-school age children attending pre-school in both participating and control areas. The first component will only be undertaken in year 1. The sample frame for the first component will be prepared by compiling household listings from the participating communities. The information to be collected during the listing will be the name of household head, whether the household has a pre-school age child, and whether the household has a child in pre-school. The final listing will only include households with a pre-school age child. In order to enlist cooperation of the respective communities, the listings should be prepared by local residents. 76. The households with pre-school age children where none is enrolled in pre-school will be treated as control households, while those with at least one pre-school age child enrolled in pre-school will be included in the treatment groups. Equal random samples of households will be drawn from the two household listings. 77. Data will be collected on household characteristics (e.g. household composition, incomes and expenditure, physical facilities, etc), particulars of pre-school age children (e.g. age, sex, birth order, whether attending pre-school, etc), individual cognitive tests (counting, letter recognition, sociability, etc) on pre-school age children, health and nutrition (immunization, anthropometric measurements, incidence of disease, etc), and reasons why not in pre-school, if applicable (e.g. disability, lack of awareness, lack of fees, distance to pre-school, etc). 78. The second component will consist of households with pre-school age children attending pre-school in both participating and control areas and will be undertaken in year 1, and updated in year 3 and year 5 of
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the project. The survey will use a similar questionnaire to that used on pre-school age children whether in- or out-of-school in the participating areas. The first round sample of households with pre-school age children attending pre-school will be common in both components of the survey. 79. During sample design, care should be taken since new households will become eligible members of the sample frame (with new births or net migration), while others will outgrow the project (when the last born is above pre-school age). An appropriate system of replacing the leavers with the entrants should be designed and the sample be updated before each survey is undertaken. Selection of Households for the National Sample 80. A national household-based survey will be conducted as a module to the National Household Welfare Monitoring and Evaluation Survey (NHWMES) conducted by the Central Bureau of Statistics using the National Sample Survey and Evaluation Programme (NASSEP). NASSEP is a multi-purpose sampling frame covering most of the districts in Kenya, except Garissa, Wajir, Isiolo, Marsabit, Samburu, and Turkana districts and the whole of North Eastern province. The sample clusters are based on the results of the 1989 population census. 81. The NHWMES currently covers about 10,000 households. The 1979 population census reported 1.32 children per household in the 0-6 years and 0.74 in the 3-6 years. Due to changing fertility patterns, the comparable ratios based on the 1989 population census were 1.21 and 0.69 children per household, respectively. The ratios are likely to have declined further in the intervening seven years since the 1989 population census was undertaken. The household survey is therefore likely to enumerate about 7,000 children in the age group 3-6 years and about 12,000 in the 0-6 year age bracket. 82. The household survey based on the NASSEP frame, to be conducted in June 1997, would generate national aggregates on variables such as enrolment ratios by single years of age, incidence of disease, immunization coverage, nutrition status (anthropometric), fees paid to pre-schools, attendance in last two weeks (if survey conducted during school term), and distance from home to pre-school. The particulars of the pre-school age children would also be analyzed jointly with other data collected in the main NHWMES, e.g. on household characteristics, household expenditures, household incomes, housing, water and sanitation, and education levels of the other members of the household. 83. The results of the household-based survey (e.g. enrolment ratios) would be compared with national estimates based on the national survey of ECCD centres. However, such comparison will only be limited to the NASSEP districts since the ECCD survey would cover all the districts, while the household survey will only cover the NASSEP districts. 84. The results of the national and community-based household surveys could be compared for project areas that correspond to administrative districts. However, such comparison may not be possible for areas selected generically (e.g. plantations, slums) due to the difficulties in overlaying the respective sample frames. 3.3 NATIONAL SURVEY OF EARLY CHILDHOOD CARE AND EDUCATION CENTRES 85. Because of the fundamental role played by ECCD centres, and their centrality as a foundation for formal education, the centres have been the subject of several studies. However, baseline data for planning, policy formulation, and monitoring of early childhood education are inadequate. Available information indicates that in 1994, about 924,000 children were attending 18,487 pre-schools with a teaching force of 26,625. These statistics are neither comprehensive nor totally reliable. There are also major information gaps regarding types of services provided, the actual number of teachers and their qualifications, their salaries, teaching materials, equipment, physical facilities, centres’ management, school fees, financing, and sponsorship.
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86. Current and reliable information is therefore required to formulate sound policies on the development and management of early childhood care and development. Various Government bodies, institutions and organizations have become aware that the starting point in planning for ECCD centres is the collection of comprehensive statistics about their actual size and structure in terms of facilities, enrolment, teaching staff, etc. 87. The Ministry of Education compiles statistics submitted by District Educational Officers (DEO) on number of pre-schools, child enrolment, and number of teachers in the pre-schools. The DEOs collect these statistics through their field officers such as DICECE and Zonal Officers. These statistics give good estimates on the number of pre-schools, enrolments and number of teachers in these institutions. 88. Nevertheless, there are some data gaps/limitations regarding number of institutions, enrolment, teaching force, types of services provided, ownership and sponsorship, fees structure, physical facilities and other types of investments, and health and nutritional status of children. Some of major gaps and weaknesses of these statistics are:
(a) No facility-based and financial data are submitted from the districts.
(b) The data disseminated do not always include age of children, which is a very important variable in analysing education statistics.
(c) The reported statistics on pre-schools are not compiled on the basis of any official
guidelines, as exemplified by the following cases: (i) there is no standard definition of an ECCD centre; (ii) although pre-school statistics refer to number of “trained” and “untrained” teachers, there is no standard classification scheme of pre-school teachers, and such categorisation is therefore at the discretion of the field officers who compile the statistics; and (iii) unlike statistics on primary and secondary schools which are based on a single reference period (March of the index year), there is no standard reference date for statistics of pre-schools. The wide annual variations in the statistics on pre-schools are therefore likely to be a statistical illusion due to lack of guidelines in compiling the statistics.
(d) Reported enrolment data behave in an erratic manner e.g. they show oscillating trends for
some districts and municipalities. 89. There is therefore need for reliable and comprehensive database on pre-school education. In this regard, the Ministry of Education commissioned several studies of these centres in May 1995 so as to provide a comprehensive database. One of the studies involved conducting a sample survey of 906 ECCD centres in 17 districts/municipalities representing urban, pastoralist, and other rural areas. The main urban areas were represented by Nairobi and Mombasa; while other urban areas were represented by Kisumu, Thika, Nakuru, Kitale and Eldoret. Rural areas were grouped into two zones i.e. pastoralist and other rural. Pastoralist districts were represented by Narok and Garissa. The other rural districts - selected so as to include every province and broad agro-ecological zone - were Nyandarua, Uasin Gishu, Kericho, Kakamega, Nakuru, Machakos, Kisumu, and Kilifi districts. 90. A new national sample survey covering 10% of all ECCD centres in every district/municipality will be undertaken in June 1998. The list of centres from each district/municipality will be stratified by sponsor before the final selection of the sample. The sample survey will generally replicate the survey instruments used in the 1995 sample survey. However, the questionnaire and the enumerators’ reference manual will be amended in light of the experience gained in the field and during data processing of the 1995 survey. 91. However, the Ministry of Education feels strongly that it would be more useful to conduct a census rather than a sample survey of ECCD centres. A census would provide the first complete national database
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of ECCD education. However, before undertaking the census, the Education Act would need to be amended to give legal recognition to pre-school education and to make the data collection legally enforceable. A census would also serve to compliment the MOE’s existing computerized database on primary and secondary schools. 92. Scope of Work The main variables to be generated by the survey shall include the following: 1. Location code for various groupings (districts and areas) included in the project. 2. Population size of community/village: total and 0-6 year old population. 3. Main sponsors: e.g. municipal council, county council, town council, urban council, religious
organization, private companies, plantations, estates, private individuals, parents/ community association, other NGOs.
4. Whether the pre-school is (a) attached, (b) linked, or (c) not related to a primary school. Do the
pre-school and the primary school share the same school committee? 5. Year the school was established. 6. Enrolment history: 1992, 1993, 1994, 1995, 1996, 1997. Enrolment broken down by: (a) boys, girls,
and (b) age group, 1, 2, 3, 4, 5, 6 and >6 years old. 7. Number of teachers, gender of teacher (male, female). 8. Number of teachers trained. Who provided training? (a) Government (b) private 9. Training received by teachers: (a) 5-week course (b) six month course (c) one-year course (d) two-
year course (e) others, specify. 10. Teacher’s emoluments per month. 11. Educational attainment of teachers (for each teacher: primary, secondary and postsecondary).
Years of teaching experience. How long has she/he been teaching in the pre-school centre? 12. School hours: (a) morning only (b) whole day 13. Of the children presently enrolled, how many are unable to pay fees? 14. Does pre-school provide feeding? What is provided? How many times a day? 15. If feeding provided, source: (a) pre-school (b) parents (c) WFP (d) other organizations. 16. Does the school conduct growth monitoring? If yes, by whom? 17. Has any of the following health interventions been conducted and by whom? (a) De-worming, (b)
immunization, (c) eye/ear check up, (d) vitamin A supplementation. Health providers for each of above may include: Government clinic/dispensary, mission clinics, private doctors, NGOs, religious organizations.
18. Who do you consider to be your supervisor? (a) DICECE (b) Headteacher of primary school (c)
others, specify.
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19. Who made supervisory visits in last year: (a) no visit, (b) DICECE, (c) pre-school supervisor, (d)
headteacher, (e) others, specify? How many visits in the last year? 20. How many children presently enrolled have disabilities (e.g. problem of vision, hearing, etc.)? 21. Is the pre-school registered (yes, no)? If yes, what is the registration number? 22. Who is in charge of managing the pre-school (a) Pre-school committee (b) headteacher (c)
headteacher of primary school, (d) NGO, (e) others, specify? 23. What is the composition of the management committee? 24. Does the management committee have a bank account? 25. Estimate the cost of the school facility: (a) building materials, (b) land, (c) furniture and equipment.
Indicate if cost of labour was contributed by community. 26. Source of funds for construction of pre-school and its facilities? (a) Harambee/parents, (b) NGO,
(c) religious organization, (d) private, (e) others, specify. 27. Source of funds for operating costs? (a) Parents, (b) sponsors, (c) others, specify. 28. Estimate of monthly operating cost/breakdown by (a) teachers’ salaries, (b) food, (c) school
materials, (d) maintenance, (e) others, specify. Survey Output 93. Prior to the launching of the sample survey, the consultants will be required to prepare the Sampling Design, Questionnaire and Survey Manual including data quality control mechanisms, and Coding Instructions. The survey results will be summarized in a report that provides a descriptive analysis of the characteristics of ECCD centres in the representative districts and areas. The main topics to be covered by the report shall include (but not limited to) the following: 1. Profile of ECCD service provision by groups and by main sponsors. 2. Trends in enrolment by age group. Proportion of 0-3, 3-6 year old in the community currently
enrolled in the ECCD centre. 3. Pupil-teacher ratio. 4. Teacher/caregiver profiles: gender, age, education, training, experience, turnover rates, working
hours. 5. Teachers’ training profiles: who trains, how long, cost of training. 6. Cost of setting up and operating ECCD centres:
(a) Capital cost - land, building, furniture, equipment, kitchen. (b) Operating cost – teachers’ salaries, food, school materials.
7. Source of funds for capital cost, and for operating cost. 8. Health and nutrition services provided - what services, how often.
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9. Supervision of ECCD centres - who, how often? 10. Profile of ECCD centre management. 11. Profile of ECCD centre’s financing. Database Management System 94. The output shall also include a system design for collection and retrieval of data on ECCD centres nationwide. The design shall include a computerized database management system to be installed at the Ministry of Education (MOE) Pre-School Division. The main types of information shall consist of variables from the sample survey. 3.4 COMMUNITY-BASED SAMPLE SURVEYS OF HOUSEHOLDS 95. The variables to be collected in the sample of households in the participatory areas will include (a) particulars of each household member (name, age, sex, marital status, education, occupation, income); (b) child variables in addition to age and sex (birth order, if enrolled in pre-school, date of enrolment, language skills, arithmetic skills, reading skills, intelligence test scores, distance to school, etc); (c) health and nutrition for each pre-school age-child (weight, height); (d) immunization history (vaccine, date and place immunized); (e) sickness: whether the child had any sickness which stopped him/her from going to school for at least a day during the two weeks preceding the interview; (f) whether the child has the pre-school project’s child card (the interviewer should carry a sample and show it to the parent or child); (g) physical facilities (main house: roofing, wall and floor materials, total area, number of rooms including living room, source of water, fuel type, source of lighting, type of toilet, distance to health facility); (h) how long the child stays in school each day; and (i) source of food while at school (provided in school, carry from home, none). 96. A survey of cognitive development of children 3-6 years attending pre-school will form the participating groups while those children of the same age bracket not attending pre-school will act as the control group. The children in the participating and control groups will be based on areas where the project interventions will be implemented. The number of children in the samples from the participating and control groups will be selected on the basis of “probability proportional to size”. The data collected will include cognitive development, psycho-social adjustment and psychomotor development of children in- and out-of-preschool, in order to obtain a broad picture of the impact of organized early childhood education. 97. In the first round, the community based survey will have two components: (a) households in participating communities with pre-school age children, whether in- or out-of-school, and (b) households with pre-school age children attending pre-school in both participating and control areas. The second component of the survey will be updated at year 3 and year 5 of the project. 98. In the first year, 2,000 households will be selected from each sub-sample, i.e. (a) with pre-school age children attending pre-school in participating areas, (b) with pre-school age children not attending pre-school in participating areas, and (c) with pre-school age children attending pre-school in control areas, making a total of 6,000 households. In years 3 and 5, the sub-sample (b) will be dropped. 99. Field enumeration will be supervised by the DICECE offices, while data collection will be undertaken by professionals in the field of early childhood education who are familiar with cognitive and other tests. The draft survey instruments (questionnaire, control forms, and enumerators’ reference manual) and dummy tables will be prepared by the statistician, systems analyst, and other professionals in the field of early childhood education, with the active support of NACECE and pre-school section in the Ministry of Education headquarters. A pilot survey will be undertaken before finalization of the survey instruments
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and dummy tables. 3.5 SAMPLE SURVEY OF HOUSEHOLDS BASED ON THE NATIONAL SAMPLE FRAME 100. In case of the variables to be collected in the national household survey as a module attached to NHWMES, it is assumed that household composition and other household particulars, household incomes and expenditures, and physical facilities will be collected as a part of the main NHWMES questionnaire. Therefore, the module will contain only particulars about the child, namely, birth order, whether the child is enrolled in a pre-school, date of enrolment, name of the pre-school, and health and nutrition (weight, height, immunization history -- vaccine and date, sickness in the last two weeks, and whether the child has the pre-school project child card). 101. The second round of the NHWMES conducted by CBS in 1994 collected the following information: (a) Particulars of household members -- occupation and income, enrolment including pre-school,
education costs by categories (school fees, uniform, books, transport, school feeding); (b) Health (incidence of illness, health facility visited, health costs); (c) Household income and expenditure; (d) Holding, amenities and housing characteristics (land holding, livestock ownership, type of main
residential structure, source of water, fuel, light, and toilet); (e) Assets; and (f) Child survival (birth order under mother, ever attended growth monitoring, immunization history,
breast-feeding and supplementary feeding, anthropometry). 102. The CBS questionnaire contains most of the information required by MOE in relation to early child care and education data that can be collected using a national household-based survey. The MOE and CBS should cooperate so that a special report on education and its relationship with other household and individual characteristics is prepared. 103. The CBS will be conducting the third round of the NHWMES in June 1997. The Ministry of Education and CBS should work closely during the preparation of the survey instruments (questionnaire and enumerators’ reference manual) to ensure that the interests of the ECD project are catered for. After data is collected, MOE should have access to the clean data for analysis and report preparation. 104. The NHWMES is also expected to be repeated in 1999 and 2001. MOE and CBS should cooperate so that the data generated in the survey rounds serve the interests of the ECD project, and that a special technical report on early childhood issues is prepared on each round.
SECTION 4: CLIENT CONSULTATION 105. The project will mount a client consultation study to compliment the establishment (ECCD) and household-based surveys. The community study will apply participatory rapid appraisal consisting of simple questionnaires and focused group discussions. The main objectives of the client consultation study will be to create awareness, act as a community needs assessment, and introduce simple record keeping. 106. The community survey will use two instruments of data gathering: (a) baseline survey using a simple questionnaire, and (b) participatory information gathering, analysis and dissemination, or focused group
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discussions, to implement and appraise the implementation of the project. This would also foster active collaboration between project staff and the communities through (a) gathering of information (baseline data, community’s resource base, etc.); (b) analysis of the data to meet project goals and objectives; and (c) dissemination of the information to the community through training, community meetings, counselling, and community-designed projects7. 107. For the purpose of focused group discussions, the community could be drawn from community leaders, pre-school teachers and headteachers, pre-school committees, headteachers and teachers of primary schools, and parents with children 3-6 years whether in- or out-of-pre-school. The information flow in participatory rapid appraisal is supposed to empower the community to be “subjects” trained to find solutions to their problems and to eventually take control of the project. The methodology is therefore expected to be cost-effective during implementation and provide a simple and early process of donor disaffiliation. 108. For focused group discussions to create ownership of the project among the participating communities, the information gathering should be initiated before project implementation, and be conducted at regular intervals, say, every year. 109. The record-keeping procedures could include: (a) detailed minutes of pre-school committee meetings, (b) accounts, (c) stock and utilization of inventory, (d) enrolment and attendance registers, (e) personnel records, (f) action plans, and (g) custody of pre-school records. Such records could improve the planning capacity at the local level, as well as be of use during evaluation of the ECD project. The record-keeping should therefore be designed to serve local needs and the needs identified for the ECD project evaluation. 110. There will be different questions fielded to different groups in the pre-schools and in the local communities. These should include: headteachers and teachers of pre-schools, pre-school committees, headteachers of primary schools, parents/guardians with children in pre-school, parents/guardians with pre-school age children not attending pre-school, and community/religious leaders. 111. HEADTEACHERS OF PRE-SCHOOLS (a) Pre-school facilities: (a) main structures: roofing, wall and floor materials, total area, number of
classrooms including staff rooms, kitchen/store; (b) learning and teaching materials, both quality and quantity: sources and adequacy; (c) play facilities; (d) furniture by type; (e) health and safety: distance to health facility, environmental conditions; (f) source of water, fuel type, source of lighting, type and number of toilets
(b) Length of children’s stay in pre-school each day (c) Source of food while at school (provided in school, carry from home, none) (d) General purposes of pre-school education (e) Child admission criteria: age, health, religious or other affiliation, immunization (f) Pre-school’s catchment area (g) Personnel: teaching and nonteaching, number and qualifications, remunerations, and workload
7 See, for example, John T. Mukui, Christine M. Guchu and Jackson M. Muriithia, Employment Creation for Youth: USAID Component, Final Evaluation Report, prepared for CARE-International in Kenya and USAID, August 1995, for an evaluation of the application of the so-called Participatory Information Gathering and Dissemination (PIGAD) implementation and evaluation methodology.
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(h) Records kept: enrolment, personnel, accounts, physical facilities, inventory of equipment,
inventory of teaching materials, school feeding, health interventions, admission registers, etc. Uses and custody of records
(i) Child progression: grading and transition to the next higher-level education institution; number of
children who proceeded to the next-level education institution; wastage within the pre-school; the relationship with the nearest primary school (administration, sharing materials and facilities, admission of children to primary school, teaching and other forms of consultation)
(j) Proportion of 0-3, 3-6 year old in the community currently enrolled in ECCD centres (k) Assistance received from parents, NGOs, school committees (if any), community leaders,
supervisory, and health and nutrition; whether involves the community and parents in the development of the pre-school
(l) Problems faced in running the pre-school, and action plans to ease the cited problems (m) Fees paid: level, difficulties in collection (n) Action plans to improve pre-school service delivery (o) Headteacher’s particulars: age, sex, marital status, qualifications, teaching experience, roles and
duties 112. TEACHERS OF PRE-SCHOOLS (a) Objectives of pre-school education as perceived by pre-school teachers (b) Class enrolment, workload and congestion: number of children sharing desks; sitting arrangements
and comfort (c) Classroom setting: degree of active participation by children in the learning process (d) Main reasons for non-attendance (illness, fees, parental attitudes to pre-school education) (e) Interactions between teacher and parents/guardians: homework, sickness, discipline, etc (f) What subjects are taught, whether the children sit examinations and the aim of the examinations (g) Job satisfaction: pay and its regularity, workload, support from headteacher and parents,
community appreciation, interest in the career (h) Personal future plans: training, change of career, change of pre-school, and reasons for each (i) Supervision of pre-school teachers (j) Level of education (academic, teacher training, ECCD-specific training, other) 113. PRE-SCHOOL COMMITTEES (a) Land for the pre-school: who provided; rates and who pays (b) Future development plans: does the size and tenure of the land influence future development plans
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(c) Purpose of pre-schools, what you think should be taught and what you think should be the
language(s) of instruction (d) Visits to pre-school other than for committee meetings: what for, how often (e) Role of parents in pre-school: financing, labour, curriculum, management (f) Fees paid: level, who decides on the level, difficulties in collection (g) Committee: composition, duties and functions, regularity of meetings, method of election, teacher
representation in the committee, tenure of office, extent to which past actions plans approved by the committee have been implemented
(h) Demand for organized pre-school care and education: adequacy of physical facilities and teachers
to meet demand, proportions left out, and community’s response to solve unmet demand (i) Teachers salaries: levels and disparities (j) Problems experienced by committee or individual committee members in carrying out their
responsibilities (k) The staple foods in the community, especially those consumed by 0-6 year old children 114. HEADTEACHERS OF PRIMARY SCHOOLS (a) Attachment/linkage: whether respondent considers the pre-school to be an integral part of the
primary school; sharing of physical facilities (buildings, teaching materials) and teachers; opinion on attachment arrangements with pre-school
(b) Role of primary school headteacher in pre-school: allocation of duties, supervision (c) Participation of pre-school teachers in primary school staff meetings (d) Sources of materials to the pre-school and their adequacy, suitability and relevance (e) Type of syllabus/curriculum and teaching methods used in pre-school: their adequacy, suitability
and relevance; any problems related to syllabus/curriculum and teaching methods (f) Pre-school children readiness for Primary Standard One (g) Main purpose of organized pre-school education and whether necessary for progression to Primary
Standard One (i) The number of children admitted to Primary Standard One this year: who had gone through pre-
school, who had not gone through pre-school (j) Impression of relationship between primary and pre-school teachers 115. PARENTS/GUARDIANS WITH CHILDREN IN PRE-SCHOOL (a) Name, sex, age and relationship to respondent; child’s birth order to the real mother; if not real
mother, what happened to the real mother?
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(b) Health: immunization history (why child has not received particular vaccinations, where applicable); where child is usually taken when it falls sick
(c) Regular caregiver: who (mother, father, grandmother, nurse-maid, etc) (d) Childcare: what girls should be taught at home, by who, and when (e) Childcare: what boys should be taught at home, by who, and when (f) Playing and games: which, with whom, how often, with what (balls, marbles, toys, beads, etc), and
perceived importance; whether boys and girls play together; whether boys and girls should play together
(g) Whether respondent plays with the child (h) Pre-school education: why sent the child to pre-school, what good things the child has learnt in
pre-school, what bad things child has learnt in pre-school; own children attending, ever attended or missed pre-school education
(i) Whether pre-school education puts too much demand on parents (fees, materials, time, forgone
child household chores) (j) Mother/guardian bio-data: name, age, sex, marital status, education, training, occupation,
employment status, land ownership, area cultivated, own monthly income and sources, spouse’s monthly income and sources
116. PARENTS/GUARDIANS WITH PRE-SCHOOL AGE CHILDREN NOT
ATTENDING PRE-SCHOOL (a) Name, sex, age and relationship to respondent; child’s birth order to the real mother; if not real
mother, what happened to the real mother? (b) Health: immunization history (why child has not received particular immunization, where
applicable); where child is usually taken when it falls sick (c) Regular caregiver: who (mother, father, grandmother, nurse-maid, etc) (d) Childcare: what girls should be taught at home, by who, and when (e) Childcare: what boys should be taught at home, by who, and when (f) Playing and games: which, with whom, how often, with what (balls, marbles, toys, beads, etc), and
perceived importance; whether boys and girls play together; whether boys and girls should play together
(g) Whether respondent plays with the child (h) Pre-school education: own children that have ever attended pre-school; why the index child does
not attend pre-school, whether child misses anything by not attending pre-school, whether many children from the neighbourhood attend pre-school, reasons why children in neighbourhood do not attend pre-school
(i) Whether respondent plans to take children younger than the index child to pre-school and why
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(j) Mother/guardian bio-data: name, age, sex, marital status, education, training, occupation, employment status, land ownership, area cultivated, own monthly income and sources, spouse’s monthly income and sources
117. HEALTH FACILITIES SERVING THE PARTICIPATING AREAS (a) Particulars of the health institution: type (health centre, clinic, dispensary, hospital); sponsor
(central Government, local authority, religious organization, company, private); condition of buildings, cleanliness, furniture, toilets; water availability, telephone and electricity; own transport; services offered by the health centre; population served and approximate radius from the health facility; capacity utilization (under-, over-utilized); staffing; any mobile clinics
(b) Children: common childhood diseases in the community; how identified by the health institution;
provisions for handling the diseases/problems; ability to cope with all the children; whether nursery schools ever refer children to the institution and the common diseases/problems referred; health programmes organized by the health institution for child health: programme, regularity, degree of utilization by the community and pre-schools, and fees charged if any; general impressions on the state of child health and nutrition in the community.
SECTION 5: SPECIAL STUDIES 118. In addition to monitoring and evaluation activities described above, there will be need for special studies to (a) address policy development issues, (b) deal with operational research issues, and (c) evaluate any specific issues or problems not (adequately) covered by the regular M&E activities. It is difficult to list the special studies in advance. However, one special study could focus on the delivery of community funds and other forms of community support. It would, for example, be useful to find out whether community support is additive or simply crowds out existing sources, and how the funds are utilized.