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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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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?

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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 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.

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5. Significant relationship between Pearson R, Spearman Rho, Regression
students’ mathematics performance
and teacher-related factors.
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

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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 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

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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
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

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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 interpreted as “always” which means that the teacher always
shows their smartness, confidence and firmness in making decisions. Items 3, 4, and 5
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 “often” with the weighted means of 4.48, 4.43, and 4.41 for ranks 3, 4, and
5 respectively.

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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”.
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

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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 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

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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
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

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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

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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.