might high-ability pupils...

No 9

Cornelia Wulff Hamrin

Kimmo Sorjonen

Chris Magnusson

Might high-ability pupils be

teachers’ headache:

the “justice” in rating?

About the authors: Cornelia Wulff Hamrin is a a senior lecturer of psychology at the Department of Occupational Health Sci-

ence and Psychology, University of Gävle. Kimmo Sorjonen is a lecturer at Karolinska Institutet. Chris Magnusson has a PhD in

psychology and psychologist.

This work is published via open access and is licensed with a Creative Commons Attribution-NonCommercial 4.0 International

(CC BY-NC 4.0) license.

Research Report No. 9

urn:nbn:se:hig:diva-33147

Distribution:

Gävle University Press

SE-801 76 Gävle, Sweden

[email protected]

Might high-ability pupils be teachers’

headaches: the “justice” in rating?

Cornelia Wulff Hamrin, Kimmo Sorjonen & Chris Magnusson

Faculty of Health and Occupational Studies Department of Occupational Health Science and Psychology

Abstract

Pupils’ grades in school are affected by several factors, including mental ability and classroom be-

haviour. The aim of the present study was to explore any age-related differences in classroom be-

haviour and academic skills with respect to higher or lower mental ability and gender among 6–11-

year-old pupils (n=194) in a Swedish school setting. Raven’s matrixes were used, and ANOVAs

were carried out. There were differences in teacher ratings in Swedish and Mathematic, partly ex-

plained by interaction effects. There were significant differences between the measurement points.

The high ability pupils´ lower teacher ratings in Mathematics, may depend on underachievement.

Keywords: Classroom behaviour, mental ability, maturation, academic skill ratings, pupils

Sammanfattning

Elevers skolbetyg beror på flera faktorer, inklusive mental förmåga och klassrumsbeteende. Syftet

med föreliggande studie var att undersöka åldersskillnader i klassrumsbeteende och skolprestationer,

hos elever 6-11 år gamla (n=194), med högre respektive lägre begåvning, i en svensk skolkontext.

Ravens matriser användes och ANOVA analyser genomfördes. Det fanns skillnader i läraraskatt-

ningar i svenska och matematik, som delvis förklaras av interaktionseffekter. Det var signifikanta

skillnader mellan mättilfällena. De högre begåvade elevernas lägre omdömmen i matematik, kan

bero på underprestation.

Keywords: Klassrumsbeteende, mental förmåga, mognad, skattningar av akademiska färdigheter, elever

Acknowledgements

This study was funded by Majblomman and the Swedish Ministry of Education and Research. The

authors also wish to thank the pupils and teachers who were involved in the project.

.

Table of Contents

Abstract 5

Sammanfattning 6

Acknowledgements 7

Introduction 1 Teacher ratings 1 The importance of mental ability for school achievement 2 Classroom behaviour and other behaviour 2 Sex differences 3 Aim 3

Method 4 Sample 4 Material 4

Mental Ability 4 Teachers’ ratings 4

Procedures 4

Results 5

Discussion 8 Limitations and conclusions 8

References 11

1

Introduction

Teachers’ ratings of pupils’ skills are affected by a great number of factors, as are pupils’ school

achievement and classroom behaviour. This study focuses on elementary school girls and boys, and

their teachers’ rating of their skills and classroom behaviour.

A pupil’s level of performance depends to a certain degree on their personal attitude towards

their ability to achieve, whether they feel they can master the situation, and whether they have a

feeling of self-efficacy. Naturally, other factors such as upbringing and intelligence are also of im-

portance (Jenner, 2004). However, Grosin (2004) has argued that the key factors for achievement

are the school climate and factors including parents’ educational and socioeconomic levels, minority

status, attitudes towards school from the home environment, and the pupil’s pre-knowledge and

understanding. He concluded that the most important aspects for success in school are the pupil’s

pre-knowledge and pedagogical and social climate factors in the school, consisting of norms, expec-

tations, and values that are focused on pupils’ needs (Grosin, 2004).

With respect to brain development, girls mature earlier than boys, as reflected in their better

concentration ability and working memory capacity. Cognitively, boys have greater variations in

mental ability than girls. Boys have shown a slightly higher prevalence for externalizing problems,

and tend to have lower reading abilities at an early age compared to girls (Ingvar, 2010). At certain

ages, small sex-related differences in achievement scores for reading (Swedish National Agency for

Education, 2012b) and mathematics (Swedish National Agency for Education, 2016) have been

found between girls and boys attending compulsory school in Sweden. School achievement is es-

sential for pupils’ school satisfaction, and also has consequences for achievement and satisfaction

later in working life (Wulff, Bergman & Sverke, 2009). However, motor restlessness and conduct

problems are not appreciated in the classroom, and might contribute to poor achievement. Mental

ability may have an impact on adjustment as well as achievement.

Teacher ratings

Teachers judge their pupils’ achievements and skills both consciously and unconsciously (SOU,

1995; Wagner & Sternberg, 1985) and through stereotyping. According to the Swedish Ministry of

Education and Research (1994), “The teacher must take all available information into account with

respect to course requirements and make an overall judgment of the pupils’ skills when determining

their marks” (p16). Mental ability is also highly correlated with school achievement (Gustafsson &

Balke, 1993; Johnson, McGue, & Iacono, 2005; Smedler & Törestad, 1996; Wulff, Bergman &

Sverke, 2009). Several studies have been conducted in this field; some examples are described be-

low.

In one study among elementary school students, teachers nominated the students they considered

gifted, and these students were given special education. Afterwards, the students’ intelligence was

measured, and ratings of giftedness from parents, teachers, and self-reported data were compared.

Grades were also taken into account. Teachers’ and parents’ ratings of giftedness were rather accu-

rate, and correlated. The ratings were related to the students’ grades (Rothenbusch, Voss, Golle &

Zettler, 2018). In another study, fourth-grade students were assessed with respect to inattentive be-

haviour, both by their classroom teachers and by tutors. Also, the students were weak in mathemat-

ics, and might develop learning difficulties in mathematics. It seemed important for these children

to have tailored instruction in small groups. The tutors’ ratings were more accurate than the class-

room teachers’ (Malone & Fuchs, 2014).

There are different elementary school curricula in different countries. Hubert, Guimard, Florin,

and Tracy (2015) carried out a study among French students in nursery/elementary school. Self-

regulation was measured with a tool where the child should have a motor response to a verbal com-

mand. Achievements in mathematics and French (i.e. literacy) were measured, and IQ was assessed

with Raven’s Coloured Progressive Matrices. Self-regulation was related to school achievement,

especially mathematics. The measures were related between two time points. There were no sex

differences in self-regulation. Furthermore, literacy was important for math achievement. There

were indirect paths between the measurement points concerning the impact of self-regulation on

mathematical achievement and the impact of literacy on mathematical achievement (Hubert, et al.,

2015).

2

Teachers, students, and peers generally make judgements about students’ IQ and achievements.

Teachers’ judgements about students’ IQ are relatively accurate. A student’s self-perception and

self-judgement are based on IQ test results and teachers’ and peers’ judgements. One study found

that judgments seemed to be based more on verbal ability than mathematical ability (Pretzlik, Ols-

son, Nabuco, & Cruz, 2003). That study used two subsamples, with different ways of measuring IQ

in each; in the London subsample, IQ was measured by WISC-R (Wechsler, 1963), and in the Por-

tuguese subsample, it was measured using Raven’s Coloured Progressive Matrices (Pretzlik et al.,

2003). The focus of the present study is on differences in achievement and classroom behaviour

between pupils with higher and lower mental ability, with respect to age.

The importance of mental ability for school achievement

Marks and mental ability have been found to be positively related (Cattle & Horn, 1966; Gustafsson

& Balke, 1993; Kulik & Kulik, 1982; Smedler & Törestad, 1996; Thurstone, 1938). Gustafsson and

Balke (1993) reported that general mental ability was related to both school achievement and the

general ability to perform well in school. Conversely, an overview article on the differences between

high-performing pupils and pupils in the mainstream or below reported that mental ability was not

important for success in school, and that success was more influenced by home environment, moti-

vation, and teaching methods (Swedish National Agency for Education, 2012a).

Depending on theoretical framework, mental ability may be viewed as a general factor, a hierar-

chical construct, or a multifactorial construct. Verbal ability is especially important for school

achievement (Smedler & Törestad, 1996), and long-term and short-term memory has implications

for numerical ability. Processing speed seems to be crucial, in that pupils with lower mathematical

ability have lower processing speed (Bull & Johnstone, 1997). However, often just a general meas-

ure of ability is used instead of specific abilities, and this approach has been adopted in the present

study. According to Schmidt and Hunter (2004), a measure of general mental ability is more accurate

for predicting achievement than specific abilities.

Johnson, McGue, and Iacono (2005) found that genetic factors had a strong impact, and that these

factors explained a substantial proportion of behaviour and school achievement. They also reported

that inattention and disruptive behaviour often run in families. Inattention, disruptive behaviour, and

learning problems are related to lower IQ (Johnson et al., 2005). In some cases, disruptive behaviour

has been associated with high IQ and high performance among boys; and similar results have been

found among girls, albeit those with a lower performance level than the boys (Johnson et al., 2005).

The researchers proposed that these findings may be due to having too little academic stimulus in

school.

A comparative twin and control study conducted in Stockholm, Jerusalem, and an Israeli kibbutz

measured IQ (Raven’s Progressive Matrices), mathematical achievement, and language achieve-

ment at two or three measurement points. The purpose was to examine whether the influence of

genetics was reduced in certain environments. In Jerusalem the boys outperformed the girls, and in

Stockholm the girls were better than the boys. No significant differences were seen between twins

and controls (Fischbein, Guttman, & Nathan, 1999).

In another study, mental ability was related indirectly to school satisfaction and job satisfaction.

The mediating link was achievement (Wulff, Bergman, & Sverke 2009). Gifted children often end

up higher in the working life hierarchy (Judge, Higgins, Thoresen & Barrick, 1999), but some pupils

are underachievers. Heyder, Kessels and Steinmayr (2017) concluded that girls had better grades

than boys in the subject of language in secondary school. However, boys had higher scores on one

IQ test; the verbal intelligence test. The reason for boys’ lower grades might be underachievement,

since verbal ability is also important for other subjects in school. Self-efficacy, text-reduction strat-

egies, and anxiety predicted underachievement among highly gifted fourth-grade students (primary

school). Both underachievers and achievers improved their learning outcomes after an intervention

aimed at improving learning strategies. Underachievers already used learning strategies, but im-

proved their outcome when they learned how to do this correctly during the intervention (Obergries-

ser & Stoeger, 2015). One can conclude that mental ability has an impact on success in school, but

it is not the only potentially influencing factor. In addition, high mental ability generally does not

explain the gender gap in school achievement.

Classroom behaviour and other behaviour

Schools have different guidelines, cultures, and norms with respect to classroom behaviour. A re-

view article pertaining to classroom behaviour discussed how pupils could learn proper behaviour

in elementary school, since maladaptive aggressive behaviour in elementary school can persist into

3

middle school (Greer-Chase, Rhodes, & Kellam, 2002). In general, teachers have expectations of

their pupils’ behaviour. A study by Lane, Givner, and Pierson (2004) found that self-control (i.e.,

temper control) and cooperative ability were important behavioural factors for succeeding in school,

and assertiveness had a minor impact. Looking at classroom behaviour from another perspective,

Brendgen, Wanner, Vitaro, Bukowski, and Tremblay (2007) concluded that verbal abuse from

teachers had long-term consequences for the well-being of pupils that extended into young adult-

hood. Girls were found to be especially vulnerable (Brendgen et al., 2007).

Henricsson and Rydell (2006) studied social competence and its impact on school achievement

and behavioural problems during the first six years in school, and found that internalizing and ex-

ternalizing problems were persistent characteristics through the years. The authors concluded that

positive peer interaction had some significance for positive development, and that teacher relations

had less significance (Henricsson & Rydell, 2006). In line with this, Zhang and Sun (2011) reported

a bidirectional relationship between pupils’ externalization of their problems and the subsequent

conflicts with their teachers. Internalizing problems were found to be related to subsequent conflicts

between the preschool child and the teacher. Conduct and classroom behaviour may have an impact

on pupils’ achievement in the sense that they act as a filter through which much of the learning

process occurs in the classroom.

Sex differences

There is an increasing awareness of sex differences in schools. A review article by Wernersson

(2010) presented aspects of boys’ shortcomings in predominantly Swedish schools, and concluded

that on the individual level, boys’ and girls’ differences in achievement may be explained by their

differing attitudes towards school and schoolwork. Some achievement-related sex differences might

be an extended consequence of the sex-segregated labour market of today’s society, and boys have

many potential paths into the labour market. Wernersson (2010) also concluded that boys were

struggling with their male identity. Schools were seen as a female arena, and in combination with a

negative work attitude, this did not encourage boys to engage in schoolwork. Kimmel’s (2010) re-

port on the “boy crisis” in Sweden and in America (i.e. the increasing problems that boys experience

in different areas including school) presented almost the same results. Kimmel concluded that mas-

culinity norms and stereotypes needed to change. Patterns of aggression and violence were dis-

cussed, as it was concluded that if boys have good (and non-violent) role models during their up-

bringing, they will not come to view aggressive acts as regular boyish behaviour. To conclude, there

is a gender gap in school achievement, and boys tend to mature later than girls; but a number of

potential explanations look to other aspects, such as the conflicts that boys experience regarding

their male identity.

Aim

The aim of this study was to explore sex and skill differences with respect to age/maturation and

ability in pupils attending the lower classes in a Swedish compulsory school. This is important since

teachers’ ratings have an impact on pupils’ success in school, and levels of maturation differ between

same-age pupils at the age of starting school. High ability pupils were compared to lower ability

pupils, and gender differences explored. The research questions were:

1. Are there age differences among pupils in terms of classroom behaviour?

2. Are there age differences among pupils in terms of teachers’ ratings regarding mathematics,

taken classrooms behaviour at the first measurement point into account?

3. Are there age differences among pupils in terms of teachers’ ratings regarding Swedish, taken

classrooms behaviour at the first measurement point into account?

4

Method

Sample

This study was part of a longitudinal study, approved by the ethics committee in Stockholm, in

which data were gathered at three time points (2009 and Subsequent years). The present set of par-

ticipants were drawn from a sample of 224 elementary school pupils. Three children were in special

education courses for intellectually disabled children, and were not included in the study. Parents of

20 (9.2%) of the children did not want their children to participate in the study. Pupils from three

classes of each of grades 1, 2, and 3 participated at the first data collection point; three classes from

each of grades 2, 3, and 4 participated at the second data collection point; and three classes from

each of grades 3, 4, and 5 participated at the third data collection point. In total, 94.4% of the pupils

were followed from the first to the third data collection point. At the second data collection point,

eleven children had moved, and a total of 198 children participated in the data collection. On this

second occasion, 194 children were screened using four different tests to measure any difficulties

with learning to read, write, or count, and Raven’s matrices were included.

There were some sets of incomplete data. In most cases, data existed for 197 children, but the

Raven’s matrices measurements only included data from 194 children. Drop outs were those for

whom no data existed regarding the Raven’s matrices, and comprised four children who had moved

to other schools.

Material

Follow-up data As noted above, the study had three measurement points in three consecutive years. Mental ability

was tested with Raven’s matrices, and teachers’ ratings were collected with an inventory. The

measures are described below.

Mental Ability

Mental ability was measured by Raven’s matrices, a non-culturally-biased intelligence test battery

in which education and background are of minor importance (Raven, 2000). The teachers were not

informed of the test results. The response scale was divided into five levels. The mean was 3.16. In

our analyses the variable was reversed so that high values represented high mental ability. Mental

ability was dichotomized into those at or below the 75th percentile (low, n=176) and those at or

above the 90th percentile (n=18). The percentile 10–75 was coded 0 and the percentile 90 and above

as 1.

Teachers’ ratings

Classroom behaviour

Teachers’ ratings of classroom behaviour were measured on Likert scales with 1 indicating good

behaviour/lack of difficulties and 5 indicating bad behaviour/existing difficulties (some items were

reversed). Items from Teachers questionnaire were used. The questionnaire was constructed for this

study. Classroom behaviour (as is an established concept), consisted of five items (the ability to sit

still, the ability to concentrate, aggressive behaviour, ability to comprehend instructions, and the

ability to control behaviour and emotions). Classroom behaviour had a Cronbach’s alpha of .83 for

the first and second data collection points and .81 at the third data collection point.

Skills

The teachers rated the pupils’ skills on a five-point Likert scale. The items were reversed, 5 is indi-

cating high skills. Teachers’ ratings of mathematics and Swedish (a mean of the reading and the

writing item). Teachers’ ratings were measured at all time points (The Teacher questionnaire was

used).

Procedures

Descriptive data analyses were carried out in order to calculate means. The means are presented in

Figures 1–3. A time × mental ability × sex analysis of variance (ANOVA) was performed with

teacher ratings in mathematics and Swedish as dependent variables, respectively. The impact of

classroom behaviour at the first data collection was also examined as an interaction term.

5

Results

The teachers’ ratings of the pupils’ classroom behaviour are shown in Figure 1. There seemed to be

a peak at the second measurement point for both girls and boys. Classroom behaviour had improved

at the last measurement point for all groups. However, there were minor differences in means be-

tween girls and boys. Single means, not repeated ANOVA.

Figure 1. Teacher ratings of classroom behavior at the measurement points. Note: Girls and boys with low and high mental ability respectively. Sd time 1: girls lo= 0.82, girls hi=1.06; boys lo=1.02, boys hi=1.11. Sd time 2: girls lo=0.86, girls hi=1.28; boys lo=1.07, boys hi=1.07. Sd time 3: girls lo=0.89, girls hi=1,17; boys lo=0.96, boys hi=1.09

Table 1 presents the results for rated skills in mathematics. There was no significant main effect of

time. However there were significat two-way intercations (time*classroom behaviour, time*gen-

der), and a tendency of a interaction time*ability. There was also a significant three-way interaction.

In Figure 2 means are presented and it is shown that high ability pupils have lower skills in ma-

temathic than lower ability pupils according to teatcher ratings. However the teacher rated skills in

mathematic were increasing with time above all for high ability pupils.

Table 1. Teacher ratings in Mathematics

Wilks’ Lambda F df sig eta

time .994 .407 2, 145 .666 .006

time*classroom behaviour .909 7.244 2, 145 .001 .091

time*ability .962 2.874 2, 145 .060 .038

time*gender .954 3.531 2, 145 .032 .046

time*ability*gender .931 5.365 2, 145 .006 .069

0

0.5

1

1.5

2

2.5

3

time 1 time 2 time 3

classroom behaviour

girls lo boys lo girls hi boys hi

6

Figure 2 Teacher ratings of Mathematics at the measurement points.

Note: Girls and boys with low and high mental ability respectively. Sd time 1: girls lo=1.05 , girls hi=1.41; boys lo=1.01, boys hi=0.98. Sd time 2: girls lo=1.04, girls hi=1.04; boys lo=0.86, boys hi=1.03. Sd time 3: girls lo=1.01, girls hi=0.92; boys lo=0.95, boys hi=1.51

Table 2 presents the results for rated skills in Swedish. There was no significant main effect of

time. However, there were significant two-ways interactioneffects of time*classroom behaviour

and time * gender. There is a tendency for a three-way interaction time*ability*gender. In Figure 3

means are shown and high ability pupils had lower teacher rated skills in Swedish than low ability

pupils at measurement point (time) two and three. For high ability girls, teacher rated skills in

Swedish were decreasing with time.

Table 2 Teacher ratings in Swedish


time .996 .323 2, 145 .725 .004

time*classroom behaviour .940 4.648 2, 145 .011 .060

time*ability .997 .183 2, 145 .833 .003

time*gender .943 4.371 2, 145 .014 .057

time*ability*gender .962 2.880 2, 145 .059 .038

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5


Mathematic


7

Figure 3 Teacher ratings of Swedish at the measurement points.

Note: Girls and boys with low and high mental ability respectively. Sd time 1: girls lo=0.87 , girls hi=1.09; boys lo=1.05, boys hi=0.80. Sd time 2: girls lo=0.95, girls hi=1.28; boys lo=1.01, boys hi=1.17. Sd time 3: girls lo=0.89, girls hi=1.43; boys lo=0.97, boys hi=1.69

Table 3 presents the results for rated skills in mathematics, separated by gender. There were main

effects of time, however more a tendency among the girls. There were two-way interaction effects

time*classroom behaviour, however more a tendency among the boys. There was a significant two-

way interaction among the boys time*abiity.

Table 3 Teacher ratings in Mathematics girls and boys


girls

time .924 3.035 2, 74 .054 .076

time *classroom behaviour .825 7.833 2, 74 .001 .175

time*ability .984 .604 2, 74 .549 .016

boys

time .911 3.361 2, 69 .040 .089


time*ability .806 8.290 2, 69 .001 .194

Table 4 presents the results for rated skills in Swedish, separated by gender. There were no signifi-

cant main effect of time, and no significant interactions among the girls. Among boys there is a

significat two-ways intercationeffects time*classroom behaviours.

Table 4 Teacher ratings in Swedish girls and boys


girls

time .969 1.182 2, 74 .313 .031


time*ability .964 1.382 2, 74 .257 .036

boys

time .994 .206 2, 69 .814 .006


time*ability .960 1.427 2, 69 .247 .040

0

1

2

3

4

5


Swedish


8

Discussion

The main purpose was to examine sex and skill differences with respect to age/maturation and ability

in pupils attending the lower classes in a Swedish compulsory school. Overall, the high-ability stu-

dents had lower rated skills than pupils with lower ability according to mean differences. There were

significant two-way interactions effects time*classroom behaviour, time*gender in both Mathemat-

ics and Swedish, and a three-way interaction (time*ability*gender) in Mathematics. For girls and

boys respectively, there was a main effect of time in Mathematics, and a two-way interaction effect

time*classroom behaviour in Mathematic. Just for boys there was a two-way interaction effect

time*classroom behaviour in Swedish. Further, there was a two-way interaction among the boys

time*ability in Mathematic. Classroom behaviour seems to improve by time with respect to means.

Time seems to have an impact on the pupils´ teacher rated skills, as well as their classroom be-

haviour at the first measurement point. However, there were no main effect of classroom behaviour,

just for time. There were minor differences with respect to gender as were seen in the time*gender

interactions and when examine girls and boys respectively. There were minor differences with re-

spect to mental ability. According to multiple regression analyses, mental ability and classroom be-

haviour at the first measurement point and classroom behaviour at the second point explained teach-

ers’ ratings of the pupils’ skills in both Swedish and mathematics. However, if the pupils thought it

was fun with those subjects was not a significant explanatory factor (Wulff Hamrin & Magnusson,

in manuscript).

We have no legitimate reason to include behaviour or maturation in the judgments of pupils’

skills in Sweden. According to Greer-Chase, Rhodes, and Kellam (2002), maladaptive behaviour

from an early age will persist throughout higher grades in school. Well-behaved students might be

expected to also perform well, but this is not always true; Johnson, McGue, and Iacono (2005) found

the opposite in some cases, especially among boys. Moreover, Sternberg (1997) made a distinction

between intelligence and intelligent behaviour. External behaviour is not always significant for in-

ternal talents. Grosin (2004) highlighted the influence of school climate on pupils’ achievement

possibilities. Improving the school climate might also have a positive impact on conduct, as it may

provide an environment in which it is easier for teachers to handle maladaptive behaviour among

the pupils.

Another finding in the present study was that the high-ability pupils had lower rated skills than

the pupils with lower ability. This is a contradiction to some previous research (see e.g. Rothenbusch

et al., 2018). Worth to notice is that the teachers were unaware of the pupils’ scores on the test of

mental ability.The present results suggest that a low-rated skill might stem from underachievement,

especially among boys, depending on psychological factors; this is in line with previous work (Hey-

der, Kessels & Steinmayr, 2017; Obergriesser & Stoeger, 2015). Previous research has found boys

to have poorer achievement and marks than girls in school (Ingvar, 2010; Kimmel, 2010; Werners-

son, 2010). One explanation might be that boys mature later, and another is that this has to do with

expectations concerning boys’ behaviour. In this respect, it might be regarded as a gender role con-

flict; boys are expected not to do their schoolwork (Ingvar, 2010; Kimmel, 2010; Wernersson, 2010).

A common view is that ability depends partly on genetic factors and partly on environmental

factors. However, according to previous research, mental ability and marks are positively related

(Bull & Johnstone, 1997; Fischbein et al., 1999; Gustafsson & Balke, 1993; Kulik & Kulik, 1982;

Smedler & Törestad, 1996; Sternberg, 1997; Sternberg & Jarvin, 2003). Moreover, a lack of inat-

tention or emotional disturbance will increase achievements (Henricsson & Rydell, 2006). Having

a supportive school context also increases performance (i.e. Grosin, 2004). Motivation, teachers,

learning strategies, and the home environment have all been found to be important for success in

school (Swedish National Agency for Education, 2012a).

Limitations and conclusions

A strength of this study is that it is based on longitudinal data, which made it possible to take into

account aspects such as pupils’ maturation and its consequences. However, the study could only

report on possible relations, and is limited with respect to causation. Moreover, the study examined

only a selection of possible variables; there are a number of other factors that might be of importance,

but these were beyond the present scope.

These results raise some questions for future research, for example regarding the role of pupils’

maturity and the importance of teachers’ expectations and misconceptions with respect to behaviour.

In Sweden there are nine years of compulsory school (from about age 6 to 15). Education at the

9

upper secondary and tertiary levels is voluntary, but parents cannot refuse to let their children attend

compulsory school. It is possible that maturation should be taken into account in deciding when a

child should start school.

11

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tional and Public Health Sciences 2011.

2. The Doll, the Globe and the Boomerang - Chemical Risks in the Future, Introduced by a Chinese

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3. Divergences in descriptions of the internal work environment management, between employees

and the management, a case study. Katarina Wijk and Per Lindberg. Department of Occupational

and Public Health Sciences 2013.

4. Energy and nutrients from horse manure - Life-cycle data inventory of horse manure management

systems in Gävleborg, Sweden. Jay Hennessy and Ola Eriksson. Department of Engineering and

Sustainable Development 2015.

5. Prospects for biodiesel in Gävleborg County: Feedstock and production. Pontus Norell.

Department of Building Engineering, Energy Systems and Sustainability Science 2019.

6. Biogas value chain in Gävleborg: Feedstock, production and use. Muhammad Arfan.

Department of Building Engineering, Energy Systems and Sustainability Science 2019.

7. Social inclusion through segregation? Liya Kalinnikova Magnusson and Jeremias Rosenqvist.

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tainability Science 2020.

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