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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 been long time to discover the importance of Mathematics in our world. And these
discoveries lead us to more technological or what so called Industrial era, wherein the different
usage of technological devices occur. In this era, application of Mathematics helps to develop
and invent such technological devices. Through these applications our life became easier. Now a
day, Mathematics is the key to all Sciences.
Despite explaining more about mathematics and the proof that it’s really important, the
students today don’t 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.

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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.
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.

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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.
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 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.

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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.
INPUT PROCESS OUTPUT
STUDENT-RELATED
FACTORS
Interest
Study Habits
An Analysis of student-
Survey related factors
TEACHER-RELATED
Data Gathering
FACTORS
Data Analysis An analysis of teacher-
Data Interpretation related factors
Personality Traits
Teaching Skills
Instructional Materials
FIGURE 1. A conceptual paradigm shows the relationship of students’ mathematics performance
in student-related factors and in 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?
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.

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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.
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.

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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.
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
INTEREST
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 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

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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 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.
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.

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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 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

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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
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.
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.

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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.
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

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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
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.

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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.
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 Weighted Mean
in terms of:
1.1 Interest
1.2 Study habits
2. The extent of teacher-related factors Weighted Mean
in terms of:
2.1 Personality Traits
2.2 Teaching Skills
2.3 Instructional Materials
3. The level of students’ mathematics Mean, median, mode, skewness and
performance. kurtosis.
4. Significant relationship between Pearson R, Spearman Rho, Regression
students’ mathematics performance
and student-related factors.
5. Significant relationship between Pearson R, Spearman Rho, Regression
students’ mathematics performance
and teacher-related factors.

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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.
Table 1. Extent of Interest in Mathematics as Perceived by the Students
Weighted Verbal
Interest Rank
Mean Interpretation
1. I make myself prepared for the math subject 3.79 4 Often
2. I listen attentively to the lecture of my math
4.10 2 Often
teacher.
3. I actively participate in the discussion,
answering exercises and/or clarifying things 3.93 3 Often
I did not understand.
4. I want to get good grades on tests, quizzes,
4.77 1 Always
assignments and projects.
5. I get frustrated when the discussion is
2.88 5 Sometimes
interrupted or the teacher is absent.
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

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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 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
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
Weighted Verbal
Study Habits Rank
Mean 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
3.08 9 Sometimes
studying my lessons.
4. I study the lessons I missed if I was absent from
3.65 5 Often
the class
5. I study and prepared for quizzes and tests. 4.07 3 Often
6. I study harder to improve my performance when I
4.34 1 Often
get low grades.
7. I spend less time with my friends during school
2.97 10 Sometimes
days to concentrate more on my studies.
8. I prefer finishing my studying and my assignments 3.10 8 Sometimes
first before watching any television program.
9. I see to it that extracurricular activities do not
3.37 7 Sometimes
hamper my studies.
10. I have a specific place of study at home which I
3.45 6 Often
keep clean and orderly.
Average Weighted Mean 3.60 Often
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

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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
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
Weighted Verbal
Personality Traits
Mean Rank Interpretation
1. Has a good relationship with the students and
4.60 1 always
teachers.
2. Shows smartness, confidence and firmness in
4.58 2 always
making decisions.
3. Imposes proper discipline and is not lenient in
4.43 4 often
following the prescribed rules.
4. Has an appealing personality with good sense of
4.41 5 often
humor.
5. Is open to suggestions and opinions and is worthy
4.48 3 often
of praise.
Average Weighted Mean 4.50 always
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

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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”.
Table 4. Extent of Teaching Skills as Perceived by the Students
Weighted Verbal
Teaching Skills
Mean Rank Interpretation
1. Explains the objectives of the lesson clearly at
4.51 2 always
the start of each period.
2. Has mastery of the subject matter. 4.70 1 always
3. Is organized in presenting subject matters by
4.40 4 often
systematically following course outline.
4. Is updated with present trends, relevant to the
4.46 3 often
subject matter.
5. Uses various strategies, teaching aids/devices
3.96 5 often
and techniques in presenting the lessons.
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 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

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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
Weighted
Instructional Materials Verbal Interpretation
Mean Rank
1. Chalk and blackboard in
4.93 1 always
explaining the lessons.
2. workbooks/textbooks 3.45 2 sometimes
3. PowerPoint presentations (visual
1.49 5 never
aids)
4. articles 2.48 4 rarely
5. materials for project development 2.55 3 sometimes
Average Weighted Mean 2.98 sometimes
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

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Median 89.00 Satisfactory
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.
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 0.544326 2.10 not significant
Study Habits -0.465262108 -2.10 not significant
Personality Traits -0.095499 -2.10 not significant
Teaching Skills 113 0.984864987 2.10 not significant
Instructional
-2.10
Materials -1.043867038 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?
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.

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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”.
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.

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Recommendations
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.