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Chapter 1

THE PROBLEM AND ITS BACKGROUND

Introduction

We live in a mathematical world. Whenever we decide on a purchase, choose an

insurance or health plan, or use a spreadsheet, we rely on mathematical understanding.

The World Wide Web, CD-ROMs, and other media disseminate vast quantities of

quantitative information. The level of mathematical thinking and problem solving needed

in the workplace has increased dramatically. In such a world, those who understand and

can do mathematics will have opportunities that others do not. Mathematical competence

opens doors to productive futures. A lack of mathematical competence closes those

doors. Students have different abilities, needs, and interests. Yet everyone needs to be

able to use mathematics in his or her personal life, in the workplace, and in further study.

All students deserve an opportunity to understand the power and beauty of mathematics.

Students need to learn a new set of mathematics basics that enable them to compute

fluently and to solve problems creatively and resourcefully.

It has taken such a long time to discover the importance of Mathematics in our

world the discoveries lead us to more technological or what was called Industrial Era,

wherein the different usage of technological devices occurred. In this era, application of

Mathematics helps to develop and invent such technological devices. Through these

applications our life became easier. Nowadays, Mathematics is the key to all Sciences.

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Despite explaining more about mathematics and the proof that it’s really

important, the students today do not like this subject. They think that the Mathematics is

a boring subject, and it’s hard to understand formulas, they always say “Why should we

study Mathematics, only four major operations are enough and the rest no longer needed.

We do use graphs and formulas in our daily living.” Only if they understand the logic

behind this subject and the principles applied in different problems, if they get what

Mathematics really meant to be, they will find that it is not a boring subject, that

mathematics is an interesting one. Mathematics becomes part of our life, not only in our

academic subjects, but in all part of our integral life. We don’t see that even in simple

conversation mathematics take place. In our transportation it also occurs, and in our daily

living it definitely applied.

Background of the Study

According to Schereiber (2000) those who have positive attitudes toward

mathematics have a better performance in this subject.

Mathematics achievement has shown that the students from each major level of

Education in Asia seemed to outperform their counterparts. Many studies have examined

students’ thinking about school and their attitude toward Mathematics. Mathematics

performance involves a complex interaction of factors on school outcome. Although the

relationship between mathematics performance and students factor has been studied

widely, it is important to explore the factors that contribute students’ mathematics

performance.

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Wendy Hansen (2008) stated that boys are more likely than girls to be math

geniuses. The researcher found that neither gender consistently outpaced the other in any

state or at any grade level. Even on test questions from the National Assessment of

Education Progress that were designed to measure complex reasoning skills, the gender

differences were minuscule, according to the study.

Student engagement in mathematics refers to students’ motivation to learn

mathematics, their confidence in their ability to succeed in mathematics and their

emotional feelings about mathematics. Student engagement in mathematics plays a key

role in the acquisition of math skills and knowledge – students who are engaged in the

learning process will tend to learn more and be more receptive to further learning.

Student engagement also has an impact upon course selection, educational pathways and

later career choices.

Mathematics performance has improved, again, through expecting students to

achieve, providing instruction based on individual student needs and using a variety of

methods to reach all learners. One factor has been aligning the math curriculum to ensure

that the delivery of instruction is consistent with the assessment frequency.

This particular study attempts to determine the factors affecting mathematics

performance of Laboratory High School Students at Laguna State Polytechnic University

Academic Year 2009-2010.

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Theoretical Framework

Dweck, C. S. (1999) stated that students believe that their ability is fixed,

probably at birth, and there is very little if anything they can do to improve it is called

fixed IQ theorists. They believe ability comes from talent rather than from the slow

development of skills through learning. “It's all in the genes”. Either you can do it with

little effort, or you will never be able to do it, so you might as well give up in the face of

difficulty. E.g. “ I can't do math”. And Untapped Potential theorists, students believe that

ability and success are due to learning, and learning requires time and effort. In the case

of difficulty one must try harder, try another approach, or seek help etc.

Inzlicht (2003) stated that entity and incremental theories of ability were assessed

separately so that their separate influences could be examined; mathematics performance

was examined by controlling for prior math performance. Entity theory was expected to

be a negative predictor of performance, whereas incremental theory was expected to be a

positive predictor.

Guohua Peng (2002) stated that simple traditional methods gradually make the

students feel that mathematics is pointless and has little value to them in real life. It

becomes a subject they are forced to study, but one that is useless to them in real life.

Dan Hull (1999) stated that growing numbers of teachers today—especially those

frustrated by repeated lack of student success in demonstrating basic proficiency on

standard tests are discovering that most students’ interest and achievement in math,

science, and language improve dramatically when they are helped to make connections

between new information (knowledge) and experiences they have had, or with other

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knowledge they have already mastered. Students’ involvement in their schoolwork

increases significantly when they are taught why they are learning the concepts and how

those concepts can be used outside the classroom. And most students learn much more

efficiently when they are allowed to work cooperatively with other students in groups or

teams.

Conceptual Framework

The major concept of this study is focused on factors affecting Mathematics

Performance of Laboratory High School Students at Laguna State Polytechnic University

Academic Year 2009-2010.

Figure 1; shows the relationship of input variables which contain the extent of the

student-related factors and the extent of the teacher-related factors. While in the process

contains the survey, data gathering, data analysis, and data interpretation. And output

variables contain the analysis of student-related factors and teacher-related factors.

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FIGURE 1. A conceptual paradigm shows the relationship of students’ mathematics

performance in student-related factors and in teacher-related factors.

INPUT PROCESS OUTPUT

STUDENT-RELATED

FACTORS

Interest

Study Habits

TEACHER-RELATED

FACTORS

Personality Traits

Teaching Skills

Instructional Materials

Survey

Data Gathering

Data Analysis

Data Interpretation

An Analysis of student-

related factors

An analysis of teacher-

related factors

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Statement of the Problem

The study attempts to determine the factors affecting mathematics performance of

Laboratory High School Students at Laguna State Polytechnic University Academic Year

2009-2010.

Specifically, it sought to answer the following questions:

1. What is the extent of the student-related factors in terms of:

1.1 Interest

1.2 Study Habits

2. What is the extent of teacher-related factors as evaluated by the students in terms

of:

2.1 Personality Traits

2.2 Teaching Skills

2.3 Instructional Materials

3. What is the level of students’ mathematics performance?

4. Is there significant relationship between students’ mathematics performance and

students-related factors?

5. Is there significant relationship between students’ mathematics performance and

teacher-related factors?

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Hypothesis

The following are the null hypothesis of this research:

There is no significant relationship between students’ mathematics performance

and students-related factors.

There is no significant relationship between students’ mathematics performance

and teacher-related factors.

Significance of the Study

The result of the study will merit the following:

School Administrator. The result of this study could serve as a baseline data to

improve programs for school advancement.

Curriculum Planner. The result of this study will help them appraise the existing

programs in terms of the student’s needs and abilities and make changes as required.

Guidance Councilor. This study will help develop the guidance program in line

with individual needs and abilities of the students.

Facilitators. The results of this study may serve as an eye opener to create and

innovates instructional materials, and to use varied and appropriate teaching strategies.

Students. This study will help the students to develop their interest toward

Mathematics and appreciate the importance of Mathematics in their daily lives.

Parents. Who are directly concerned with the education of their children

considering school performance in different discipline.

Future Researcher. The result of this study can serve as basis for further study

on teaching learning activities and student mathematical performance.

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Scope and Limitation

This study is limited only to Laboratory High School Students of Laguna State

Polytechnic University during the Academic Year 2009-2010.

Determining the factors affecting Mathematics Performance of Laboratory High

School Students was the focus of this research. The information needed will be gathered

using the checklist style research-made questionnaire. All information and conclusions

drawn from this study were obtained only to this particular group of students.

Definition of Terms

For better clarification and understanding of the terms related to this study, the

following terms are defined conceptually and operationally.

Mathematics Performance. This refers to the degree or capacity of students’

knowledge in Mathematics.

Instructional Materials. This refers to motivating techniques that teaching materials

or equipment used. It can high technology or simple materials that can use in learning

preference.

Interest. This refers to the amount of the students’ dislike or like of particular things.

Study Habits. This refers to usual form or action of a person in studying.

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Teaching Skills. This refers to the skills of teachers in mathematics in terms of

teaching her/his lesson.

Personality Traits. This refers to the good relationship of the mathematics teachers

with the students.

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Chapter 2

REVIEW OF RELATED LITERATURE AND STUDIES

This chapter presents the review of related literature and studies of the sub-topics

of this research; interest, study habits, personality traits, teaching skills and instructional

materials.

Norma Presmeg (2002) Educational Studies in Mathematics presents new ideas

and developments of major importance to practitioners working in the field of

mathematical education. It reflects both the variety of research concerns within the field

and the range of methods used to study them. Articles deal with didactical,

methodological and pedagogical subjects, rather than with specific programs for teaching

mathematics. The journal emphasizes high-level articles that go beyond local or national

interest.

Fulk (2002) stated that students with sequencing difficulties need help to

maximize their engagement and improve their retention of learning use humor,

unexpected introduction and various other attention grabbers to stimulate student’s

interest in the lesson.

http://www.springerlink.com/content/08272762649018lx/ In this article, present

results of an empirical study with 500 German students of grades 7 and 8. The study

focused on students' mathematics achievement and their interest in mathematics as well

as on the relation between these two constructs. In particular, the results show that the

development of an individual student's achievement between grade 7 and grade 8 depends

on the achievement level of the specific classroom and therefore on the specific

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mathematics instruction Interest in mathematics could be regarded a predictor for

mathematics achievement Moreover, our findings suggest that the students show hardly

any fear of mathematics independent of their achievement level.

Hanson, Katherine (2008) stated that an exploration of girls’ learning styles,

attitudes, and behaviors in math classes that also shows the importance of analyzing the

curriculum and attitudes of teachers when attempting to understand girls’ relation to

math. It attempts to discover ways to increase girls’ interest and achievement in math. It

concludes with 15 practical recommendations for the improvement of math education for

girls.

Davis-Kean (2000) analyzed how parents' values and attitudes affect children's

math performance and later interest, and how these attitudes vary by the child's gender.

They used data from a longitudinal study of more than 800 children and a large group of

their parents that began in 1987 and continued through.

STUDY HABITS

 Steinberger & Wagner (2005) distinguishes more simply among three

intelligences; the academic-problem solving; the practical intelligence; and creative

intelligence; all these three have peculiar influence to performance. Success in study does

not depend on ability and hard work but also on effective methods of study.

Individualized method of studying is adopted by every individual student, thus, a good

study habit will mean the ability to learn and make use of what one is reading or

studying. Study skills when properly embedded will help students understand their own

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potentials for intellectual growth and self-direction. It is for this reason that the strategies

of proper study habits among students should be given emphasis.

Simmons (2002) note that "good writing spawns from a close understanding of

text and great writing result from an interactive analysis and fluency with our reading."

He adds that inadequate writing is a direct result of inadequate reading and studying.

Postgraduate students are scholars in training and have the responsibility of becoming

prolific and critical writers in their disciplines and careers. The spirit of responsibility and

integrity are vital to the study habits of postgraduate students.

Richardson et al (2000) compared college students who are deaf and hard of

hearing in mainstreamed classes with hearing peers. In both studies, the students who are

deaf had comparable study behaviors to those of their hearing peers. Similarly, both

studies employed a survey design that precluded the researchers from obtaining in-depth

knowledge of participants' skills, and in particular, their use of notes as a study text.

These studies are similar to several others that attempt to survey the study habits of

normal hearing students.

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Aquino (2003) pointed out that study skills can be taught effectively only after

identifying students’ areas of weakness and levels of achievement is appropriate to their

grade level can be provided with development (or enrichment) exercises, which will

enable them to become more proficient in the skills they have already acquired or which

will help them learn new ideas.

Fielden (2004) states that good study habits help the student in critical reflection

in skills outcomes such as selecting, analyzing, critiquing, and synthesizing.

PERSONALITY TRAITS

Rohwes W. Jr. et al. as cited by Sainz (2000) further discussed the teachers need

to find ways of determining whether or not her instruction have been successful. The

procedure and method of determining such success can take the form of test of various

kinds to determine whether the students have reached the objectives they have set for

them.

Myers and Briggs (2003) developed a personality test based on Jung's

temperaments called the Myers-Briggs Type Inventory, or MBTI.  It has gone on the

become the most famous personality test of all time. The traits are seen as opposites, and

the first set is introversion and extraversion.  Introversion refers to a tendency to prefer

the world inside oneself.  The more obvious aspects of introversion are shyness, distaste

for social functions, and a love of privacy. Extraversion is the tendency to look to the

outside world, especially people, for one's pleasures. 

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Woolfolk (2001) describes intrinsic motivation as involving internal, personal

factors such as needs, interest, curiosity, and enjoyment. A student who is intrinsically

motivated undertakes an activity “for its own sake”, because the activity itself is

rewarding. In contrast is intrinsic motivation, in which the student engages in an activity

in order to obtain a reward , or to avoid a punishment.

Gordon Allport (1998) extensively investigated the ways in which traits combine

to form normal personalities, cataloguing over 18,000 separate traits over a period of 30

years. He proposed that each person has about seven central traits that dominate his or her

behavior.

Hans Eysenck (1998) claimed that personality could be described based on three

fundamental factors: psychoticism (such antisocial traits as cruelty and rejection of social

customs), introversion-extroversion, and emotionality-stability (also called neuroticism).

TEACHING SKILLS

Tomlinson (1999) stated that teachers can differentiate content, process, and/or

product for students. Differentiation of content refers to a change in the material being

learned by a student. For example, if the classroom objective is for all students to subtract

using renaming, some of the students may learn to subtract two-digit numbers, while

others may learn to subtract larger numbers in the context of word problems.

Differentiation of process refers to the way in which a student accesses material. One

student may explore a learning center, while another student collects information from

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the web. Differentiation of product refers to the way in which a student shows what he or

she has learned. For example, to demonstrate understanding of a geometric concept, one

student may solve a problem set, while another builds a model.

http://www.teachervision.fen.com Authentic assessment, cooperative learning,

inclusion – discover a vast range of current articles about teaching methodologies, ideal

for all grades. Diversify your teaching strategies by implementing service-learning

projects and integrating technology in your classroom. These resources will help you gain

the experience and expertise you need to become a successful teacher, whether you're a

new teacher or have been teaching for many years.

According to Bloom’s Taxonomy, teachers frequently spend a great deal of

classroom time testing students through questions. In fact, observations of teachers at all

levels of education reveal that most spend more than 90 percent of their instructional time

testing students (through questioning). And most of the questions teachers ask are

typically factual questions that rely on short-term memory.

Rhodes and Bellamy (1999) stated that a teacher tells, a facilitator asks; a teacher

lectures from the front, a facilitator supports from the back; a teacher gives answers

according to a set curriculum, a facilitator provides guidelines and creates the

environment for the learner to arrive at his or her own conclusions; a teacher mostly gives

a monologue, a facilitator is in continuous dialogue with the learners

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Holt and Willard-Holt (2000) emphasize the concept of dynamic assessment,

which is a way of assessing the true potential of learners that differs significantly from

conventional tests. Here the essentially interactive nature of learning is extended to the

process of assessment. Rather than viewing assessment as a process carried out by one

person, such as an instructor, it is seen as a two-way process involving interaction

between both instructor and learner. The role of the assessor becomes one of entering into

dialogue with the persons being assessed to find out their current level of performance on

any task and sharing with them possible ways in which that performance might be

improved on a subsequent occasion.

INSTRUCTIONAL MATERIALS

Siemens (2002) stated that instructional design can be defined as “the systematic

process of translating principles of learning and instruction into plans for instructional

materials and activities”. However, there are many different definitions for instructional

design and all of them are an expression of underlying philosophies and viewpoints of

what is involved in the learning process

Heinze, Aiso (2008) stated that the development of an individual student's

achievement depends on the achievement level of the specific classroom and therefore on

the specific mathematics instruction. Interest in mathematics could be regarded a

predictor for mathematics achievement. Moreover, he suggests that the students show

hardly any fear of mathematics independent of their achievement level.

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Burgess (2000) stated that changes in society and workplace have exerted

pressure on the educational system. For instance, with increased internationalization,

growing knowledge-intensive work, and increasing use of information technology,

schools are required to produce graduates who do not only possess relevant knowledge

but also interpersonal relations and communication skills, ability to work in various

contexts, and information literacy skills.

Wang & Woo (2007) to facilitate student-centered learning, many authors suggest

the use of media and technology.

Jonassen, Peck, & Wilson (1999) stated that learning technologies should shift

their role from being conveyors of information to a means for engaging students in

thinking. More specifically, technologies should be used to pose problems to students,

provide related cases and information resources, a social medium to support learning

through collaboration and interaction, and intellectual partners to support learning by

reflecting.

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Chapter 3

RESEARCH METHODOLOGY

This chapter presents the research design, research procedure, the subject of the

study, determination of sample, research instrument and statistical treatment of data.

Research Design

This study determined the factors affecting mathematics performance of

Laboratory High School Students at Laguna State Polytechnic University. The

descriptive – correlation method was used in this study.

In descriptive method, Calmorin (1994) as cited by Bagayana (2006), wrote the

study focuses on the present condition. The purpose is to find new truth, which may come

in different forms such as increased quantity of knowledge, a new generalization, or

increased insights into factors, which are operating, the discovery of a new causal

relationship, a more accurate formulation of the problem to be solved and many others.

Since this study measured data that already exists and the number of respondents

is not large, the descriptive – correlation method of studies is best suited. As mentioned,

the student-related factors in terms of interest and study habits, and the teacher-related

factors in terms of personality traits, teaching skills and instructional materials were

generated using researcher – made questionnaire.

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Subject of the Study

The respondents in this study were the one hundred twenty six (126) Laboratory

High School Students at Laguna State Polytechnic University Academic Year 2009-2010.

Research Instrument

The main tool used in this study was a researcher – made questionnaire –

checklist. Set of questionnaire-checklist was constructed for the student respondents. The

questionnaire – checklist consisted of the students’ level of interest in Mathematics, their

study habits and their teachers’ personality traits, teaching skills and instructional

materials use in teaching as perceived by the students.

Part 1 on the questionnaire – checklist obtained the students’ level of interest in

Mathematics presented five(5) statements and the students’ study habits presented ten(10)

situations. These were given one set of five checkboxes each. The five checkboxes were

ranked as:

5 – Always

4 – Often

3 – Sometimes

2 – Rarely

1 – Never

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Part 2 obtained teacher’s personality traits, teaching skills and instructional

materials used in teaching as rated by the students. Each statement was given one set of

five checkboxes. Again the five checkboxes were ranked as:

5 – Always

4 – Often

3 – Sometimes

2 – Rarely

1 – Never

The questionnaire – checklist was presented to the adviser and expert on

Mathematics for comments, corrections, and suggestions on the content.

Research Procedure

The original title proposed by the researcher was checked, revised and rechecked

by the researcher’s adviser to maintain conformity on the subject of research. The

questionnaire-checklist that aims to draw out proper responses on the objectives of this

study was constructed. This questionnaire – checklist made by the researcher and was

presented to, analyzed and checked by the research adviser to ensure the validity of

responses it would elicit.

Permit to conduct research and study was secured of letter requesting permission

to the principal of Laboratory High School at Laguna State Polytechnic University.

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Data gathered from answered questionnaires were checked, classified , tabulated

and analyzed according to the research design described in this chapter using Microsoft

Excel and prepared for final presentation to the experts of different fields of

specialization.

Statistical Treatment of Data

Analysis Statistical Tools

1. The extent of student-related factors

in terms of:

1.1 Interest

1.2 Study habits

2. The extent of teacher-related factors

in terms of:

2.1 Personality Traits

2.2 Teaching Skills

2.3 Instructional Materials

3. The level of students’ mathematics

performance.

4. Significant relationship between

students’ mathematics performance

Weighted Mean

Weighted Mean

Mean, median, mode, skewness and

kurtosis.

Pearson R, Spearman Rho, Regression

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and student-related factors.

5. Significant relationship between

students’ mathematics performance

and teacher-related factors.

Pearson R, Spearman Rho, Regression

Chapter 4

PRESENTATION, ANALYSIS AND INTERPRETATION OF DATA

This chapter presents, analyzes and interprets the data gathered from the students

of Laboratory High School at Laguna State Polytechnic University in determining factors

affecting Performance in Mathematics.

Extent of Interest of the students in Mathematics

Table 1 shows the weighted mean of students’ interest in Mathematics. Students’

level of interest in Mathematics was rated based on the students’ self-perceived level of

preparation for the Mathematics subject, attention given to teacher’s lectures, active

participation in class, their desire to get good grades and their desire to listen to

discussions or attention class.

The students gave a unifying perception on their level of interest in Mathematics.

The item “I want to get good grades on tests, quizzes, assignments and projects.” ranked

first with an average weighted mean of 4.77. The item “I get frustrated when the

discussion is interrupted or the teacher is absent.” got the lowest rating with an average

weighted mean of 2.88.

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Table 1. Extent of Interest in Mathematics as Perceived by the Students

InterestWeighted

MeanRank

Verbal

Interpretation

1. I make myself prepared for the math subject 3.79 4 Often

2. I listen attentively to the lecture of my math

teacher.4.10 2 Often

3. I actively participate in the discussion,

answering exercises and/or clarifying things

I did not understand.

3.93 3 Often

4. I want to get good grades on tests, quizzes,

assignments and projects.4.77 1 Always

5. I get frustrated when the discussion is

interrupted or the teacher is absent.2.88 5 Sometimes

Average Weighted Mean 3.90   Often

The overall weighted mean of interest in Mathematics is 3.90. This means

students are “often” interested in this subject. Among questionnaire items, the desire to

get good grades is the most interesting to students but the desire to attend discussion

received the lowest extent of interest.

Extent of Study Habits

Table 2 shows the lists of ten (10) items about situational/action statements used

in the data gathering and the corresponding weighted means of the students’ responses

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ranked from the highest to lowest weighted mean together with the verbal interpretation.

The criteria in obtaining students’ level of study habits were based on their personal

tendency or pattern of action in studying when they are in school days.

Table 2. Extent of Study Habits as Perceived by the Students

Study HabitsWeighted

MeanRank

Verbal

Interpretation

1. I do my assignments regularly. 4.09 2 Often

2. I exert more effort when I do difficult assignments. 3.88 4 Often

3. I spend my vacant time in doing assignments or

studying my lessons.3.08 9 Sometimes

4. I study the lessons I missed if I was absent from

the class3.65 5 Often

5. I study and prepared for quizzes and tests. 4.07 3 Often

6. I study harder to improve my performance when I

get low grades.4.34 1 Often

7. I spend less time with my friends during school

days to concentrate more on my studies.2.97 10 Sometimes

8. I prefer finishing my studying and my assignments

first before watching any television program.3.10 8 Sometimes

9. I see to it that extracurricular activities do not

hamper my studies.3.37 7 Sometimes

10. I have a specific place of study at home which I 3.45 6 Often

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keep clean and orderly.

Average Weighted Mean 3.60   Often

Overall, the extent of study habits as perceived by the students themselves gained

an “often” result with an overall weighted mean of 3.60. Among each situational/action

statements or items given, the item “I study harder to improved my performance when I

get low grades.” ranked first with an average weighted mean of 4.34 but the item “I spend

less time with my friends during school days to concentrate more on my studies.” got the

lowest extent of study habits in Mathematics.

Extent of Teachers’ Personality Traits

. Table 3 shows the data on the extent of personality traits of the teachers with the

computed weighted mean, rank and interpretation. Extent of teachers’ personality traits

were ranked based on their relationship with the students, their smartness, confidence and

firmness in making decisions, their imposing proper discipline and not lenient in

following the prescribed rules, their personality with good sense of humor and their

appreciation to suggestions and opinions and their worthy of praise

Personality TraitsWeighted

Mean Rank

Verbal

Interpretation

1. Has a good relationship with the students and

teachers.4.60 1 always

2. Shows smartness, confidence and firmness in 4.58 2 always

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making decisions.

3. Imposes proper discipline and is not lenient in

following the prescribed rules.4.43 4 often

4. Has an appealing personality with good sense of

humor.4.41 5 often

5. Is open to suggestions and opinions and is worthy

of praise.4.48 3 often

Average Weighted Mean 4.50   always

Table 3. Extent Teachers’ Personality Traits as Perceived by the Students

The table reveals that item number 1 ranked first with an average weighted mean

of 4.60 and interpreted as “always” which means that the teacher always has a good

relationship with the students. The item number 2 ranked second with an average

weighted mean of 4.58 also interpreted as “always” which means that the teacher always

shows their smartness, confidence and firmness in making decisions. Items 3, 4, and 5

interpreted as “often” with the weighted means of 4.48, 4.43, and 4.41 for ranks 3, 4, and

5 respectively.

Extent of Teaching Skills

Table 4 presents the extent of teaching skills acquired by the teachers in

Mathematics as perceived by the students. The overall weighted mean of the teachers in

terms of teaching skills is 4.41 which is interpreted as “often”.

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Table 4. Extent of Teaching Skills as Perceived by the Students

Teaching SkillsWeighted

Mean Rank

Verbal

Interpretation

1. Explains the objectives of the lesson clearly at

the start of each period.4.51 2 always

2. Has mastery of the subject matter. 4.70 1 always

3. Is organized in presenting subject matters by

systematically following course outline.4.40 4 often

4. Is updated with present trends, relevant to the

subject matter.4.46 3 often

5. Uses various strategies, teaching aids/devices

and techniques in presenting the lessons.3.96 5 often

Average Weighted Mean 4.41   often

Looking closely at the table item per item, it was observed that the “The teacher

has mastery of the subject matter” has the highest average weighted mean among the five

items and interpreted as “always” followed by the item “The teacher explains the

objectives of the lesson clearly at the start of each period” also interpreted as “always”.

Items “The teacher is updated with present trends, relevant to the subject matter” , “The

teacher is organized in presenting subject matter by systematically following course

outline”, and “The teacher uses various strategies, teaching aids/devices and techniques

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in presenting the lessons” interpreted as “often” with the average weighted means of

4.46, 4.40 and 3.96 for ranks 3, 4. and 5 respectively.

Extent of Instructional Materials used by the Mathematics teachers

Table 5 presents the extent of instructional materials used by the teachers in

Mathematics. It shows that the teachers “always” used chalk and blackboard in

explaining the lessons with an average weighted mean of 4.93. The teachers used

workbooks/textbooks and materials for project development interpreted as “sometimes”

with the average weighted means of 3.45 and 2.55 for ranks 2 and 3. The teachers used

articles interpreted as “rarely” with an average weighted mean of 2.48. Lastly, used of

power point presentation got the lowest extent of instructional materials with an average

weighted mean of 1.49 interpreted as “sometimes”.

Table 5. Extent of Instructional Materials used by the Mathematics Teachers

Instructional MaterialsWeighted

Mean RankVerbal Interpretation

1. Chalk and blackboard in

explaining the lessons.4.93 1 always

2. workbooks/textbooks 3.45 2 sometimes

3. PowerPoint presentations (visual

aids)1.49 5 never

4. articles 2.48 4 rarely

5. materials for project development 2.55 3 sometimes

Average Weighted Mean 2.98   sometimes

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The overall extent of instructional materials used by the Math teachers as

perceived by the students gained “sometimes” result with an overall average weighted

mean of 2.98. This means that the teacher in Mathematics sometimes uses instructional

materials.

Level of Performance of Students in Mathematics

Table 6 presents the level of performance of Laboratory high school students in

Mathematics in terms of some measure as mean, median, mode, standard deviation,

skewness and kurtosis. The grades presented are the means of the grades of students-

respondents in third grading period obtained through documentary analysis of Form 138

provided by the adviser.

Table 6. Level of Performance of Students in Mathematics

Statistics  Value Verbal Interpretation

Mean 88.23 Satisfactory

Median 89.00 Satisfactory

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Mode 91.00 Very Satisfactory

Standard Deviation 4.84

Kurtosis 2.10 Relatively Steep/leptokurtic

Skewness -1.13 Skewed to the left/negatively skewed

Table reveals that the mean performance of students in Mathematics was

“satisfactory” with an average of 88.23 median of 89 mode of 91 and standard deviation

of 4.84. The skewness of the level of students is -1.13 which, which skewed to the

left/negatively skewed while kurtosis is 2.10, which is leptokurtic or has a relatively

peaked distribution.

It reveals that several of the students really wanted the subject of Mathematics.

Only few of the students got low and the rest got the high grades.

Significant Relationship of the Mathematics Performance of the Students in

Student-related factors and Teacher-related factors

Table 7 presents the significant relationship of the factors affecting Mathematics

Performance of Laboratory High School. As seen on the table, the Pearson r of the five

(5) factors such as Interest, Study Habits, Personality Traits, Teaching Skills and

Instructional Materials have high degree of correlation but the t revealed the lesser value

of 2.01. It means that there is no significant relationship to Mathematics performance of

the students.

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Table 7. Significant Relationship of the Mathematics Performance of the Students in

Student-related factors and Teacher-related factors

Variables df T-Computed T- value Interpretation

Interest

113

0.544326 2.10 not significant

Study Habits -0.465262108 -2.10 not significant

Personality Traits -0.095499 -2.10 not significant

Teaching Skills 0.984864987 2.10 not significant

Instructional

Materials -1.043867038-2.10

not significant

The table reveals that the interest, study habits, personality traits, teaching skills

and instructional materials do not affect the Mathematics performance of the Students of

Laguna State Polytechnic University.

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Chapter 5

SUMMARY, CONCLUSION AND RECOMMENDATION

This chapter presents the summary of findings; the conclusions made and the

recommendations offered.

Summary

This study was conducted in Laguna State Polytechnic University, Siniloan,

Laguna, with a total of one hundred fifteen respondents of laboratory high school.

Descriptive method was used in this study. The researcher used a checklist-questionnaire

method in order to reveal the relationship of the variables.

The special problem was conducted to determine the factors affecting

Mathematics Performance of Laboratory High School Students at Laguna State

Polytechnic University Academic Year 2009-2010. It aims to find out the appropriate

answers to the following questions: What is the extent of the student-related factors in

terms of interest and study habits? What is the extent of teacher-related factors as

evaluated by the students in terms of personality traits, teaching skills and instructional

materials? What is the level of students’ mathematics performance? Is there significant

relationship between students’ mathematics performance and student-related factors? Is

there significant relationship between students’ mathematics performance and teacher-

related factors?

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Through this problems stated, the researcher came up with the following null

hypothesis: Ho There is no significant relationship between the students’ mathematics

performance and student-related factors in terms of interest and study habits. Ho There is

no significant relationship between students’ mathematics performance and teacher-

related factors in terms of personality traits, teaching skills and instructional materials.

After administering the questionnaire, the researcher used weighted mean and

rank to determine the extent of student-related factors in terms of interest and study

habits; and extent of teacher-related factors in terms of personality traits, teaching skills

and instructional materials. Mean, median, mode, standard deviation, skewness, kurtosis

were used to determine the level of performance of students in Mathematics. And to test

the significance of input and output variables, pearson-r were used.

Conclusions

Based on the data gathered, the overall weighted mean of level of interest in

mathematics was 3.90 and interpreted as “often”. Study habits had an average weighted

mean of 3.60 and also interpreted as “often”. Personality traits had an average weighted

mean of 4.50 and interpreted as “always”. Teaching skills had an average weighted mean

of 4.41 and interpreted as “often”. Instructional materials had an average weighted mean

of 2.98 and interpreted as “sometimes”.

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In terms of level of performance of the students in mathematics, the students

obtained the mean grade of 88.23 with verbal interpretation of “Satisfactory” and

standard deviation of 4.84.

Through the test of significance, the researcher came up with the following

conclusion; there is no significant correlation between student interest in mathematics

and their performance in mathematics. Their computed z-value is 0.54 which is less than

the tabular z-value of 2.10 at α = .05. There is no significant correlation between study

habits and their performance in mathematics. The computed z-value is -0.47 which is less

than the tabular z-value of -2.10 at α =0.05. This means that the performance of the

students in mathematics does not affected by the student-related factors in terms of

interest and study habits.

There is no significant relationship between teacher-related factors such as

personality traits, teaching skills and instructional materials and the performance of the

students in mathematics. Their computed z-values are -0.10, 0.98 and -1.04 which are

less than the tabular z-value of -2.10, 2.10 and -2.10 respectively. Thus, teacher-related

actors do not affect the performance of the students in mathematics.

Recommendations

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Based on the conclusions made, the following recommendations are given: that a

more concentrated research on relationship to Mathematics be made by the future

researchers to determine a more focused result on the relationship; that teachers use more

interactive teaching techniques that would boost interest in mathematics; that a more

thorough research on study habits be made by future researchers to determine its effect on

student performance.