Factors Affecting Mathematics Performance of Indang National High School Perceived by Grade 9 Learners - SLOLetran - TED

Factors Affecting Mathematics Performance of
Indang National High School as Perceived

by Grade 9 Learners
Undergraduate Research Project

Submitted to the Faculty of the
College of Education
Cavite State University
Indang, Cavite
In partial fulfilment
of the requirements for the course
Research in Mathematics
(BSEM 38)
CARIAGA, SHERY MAE L.

GARCIA, LARA ANGELIKA O.
LETRAN, SHAIRA LOU O.
MANAIG, KENNETH ANDREW M.
MARCELLANA, LYKA B.
RABINO, RAFAEL R.
June 2023
ABSTRACT
Mathematics is a part of our everyday lives that is why there are a lot of
teaching and learning strategies being applied to acquire learner’s interests towards
mathematics. This study aims to describe and evaluate if the student and teacher
related factors has effect in mathematics performance of grade 9 students of Indang
National High School. Descriptive-evaluative under quantitative method was used to
gather information from the respondents without having any difficulties in answering
the questions. The researchers made use of random sampling and total enumeration
sampling technique, to know the number of respondents in Grade 9, consisting of
seventy-two (72) students, thirty-six (36) students from general curriculum and thirty-
six (36) from special science curriculum. The results showed that when the
respondents were grouped according to demographic profile: (1) sex, (2)
mathematics performance, and (3) type of curriculum, the null hypothesis were failed
to reject in both student and teacher related factors. In conclusion, there is no
significant difference on student and teacher related factors in students’ mathematics
performance according to their demographic profile. The researchers therefore
recommend that when the next generation who will conduct this research to broaden
the participants and select other schools to have accurate data to be gathered.
Keywords: sex, mathematics performance, type of curriculum, student-related
factors, teacher-related factors.

INTRODUCTION
Mathematics, in general, had a negative interpretation from the perspective of
the learners. Some learners even wished for being excluded from any mathematics
related subject. When we say Mathematics, we automatically think of it as numeracy,
difficult, obscure, and of little interest to certain people. (Atteh, E. et al., 2014).
However, mathematics is more than that. Mathematics is a part of our everyday lives
that is why there are a lot of teaching and learning strategies being applied to acquire
learner’s interests towards mathematics.
Student-related factors are being demonstrated to have significant effects on
mathematics performance. A variety of studies believe that a student's attitude is an
important factor in determining whether they perform well or poorly in mathematics
(Mohamed & Waheed, 2011; Mata, Monteiro, & Peixoto, 2012; Ngussa & Mbuti,
2017). Learners with high cognitive abilities and positive attitude tend to perform
better in mathematics than those with low cognitive abilities with a negative attitude.
According to Akinsola & Olowojaiye (2008) and Mutai (2011), once an optimistic
outlook is developed it can enhance students' learning. On the other hand, a negative
outlook prevents effective learning and subsequently has an impact on performance.
In order to address this problem, this study aims to look into students' attitudes
toward learning mathematics.
Teacher-related factors have been shown to have a major impact in
mathematics performance of students in high school. There are various studies that
believe that the learner draws from the teacher’s disposition to form a student's own
attitude which may affect his/her learning outcomes (Mazana, 2020). Studies that
specifically focused on teachers’ attitude and students’ achievement in mathematics
found out that teachers’ attitude contributed to students’ academic performance and
behavior (Kele, 2018; Paksu, 2008; Ndifor, 2017). In relation to these claims and
statements above, teacher's attitude towards students in teaching mathematics
conclude that this sub-factor affects the students' performance in mathematics.
Another sub-factor is the teaching methods, it can best be defined as the type of
principal & methods used for instruction. There are many types of teaching methods,
depending on what information or skill the teacher is trying to convey. The methods
used in teaching may vary from one country to another, depending on the information
or skills being taught (Mohd Rasid, 2020; Kearney, 2019). To guarantee that every
student has an equal opportunity to learn, numerous strategies and methods are
employed. The students will perform worse than the other students if the teaching
strategy does not promote understanding.
Through this study, the researchers aimed to know if the mathematics
performance were affected by the student and teacher related factors. The
importance of this study is that it influences the learners that are affected by various
factors in a particular field or subject and can enhance learning and encourage
motivation within oneself. Further, interest and study habits under student-related
factors, and personality traits, teaching skills, and instructional materials under
teacher-related factors, which are factors toward educational matters, is essential,
which results in intense learning and excellent educational achievement.
Statement of the Problem
1. What is the demographic profile of the participants in terms of:
1.1. Sex
1.2. Mathematics performance
1.3. Type of curriculum

2. What are the student-related factors affecting learners' mathematics
performance in terms of:
2.1. Interest
2.2. Study habits
3. What are the teacher-related factors affecting learners' mathematics
performance in terms of:
3.1. Personality traits
3.2. Teaching skills
3.3. Instructional materials
4. Is there any significant difference on the following perceived factors
when grouped according to demographic profile?
4.1. Student-related
4.2. Teacher-related
Hypothesis
Ho: There is no significant difference on the following perceived factors when
grouped according to demographic profile.
1.1 Student-related
1.2 Teacher-related
Theoretical Framework
Theoretical framework is the structure that can hold or support a theory of a
research study. In this study, the researchers found two theoretical frameworks that
are related to the two variables of this research: student-related and teacher-related.
In this framework the researchers produce a theoretical composite to support
their studies.
The investigation is moored on the hypothesis of Affective-Cognitive
Consistency Theory by Rosenberg (1968), which states that the changes in the
individuals’ affective component will produce changes in ones’ cognitive component
so that it will bring consistency between the two components. The students’ feelings
towards the subject will affect how they perform on the subject. A student with a
negative attitude towards a subject will think that he or she will not do well in the
subject. However, a student with a positive attitude towards a subject will be
motivated to perform well because he or she thinks that he or she is capable of
achieving in that subject.
In general, students do not like mathematics. Difficulty in understanding the
subject matter and teacher related factors were the primary reasons why these
students hate mathematics. This dislike of the subject will result in a negative attitude
towards the subject. Moreover, the students who hate the subject do not like studying
the subject. More importantly, in mathematics, wherein concepts are difficult for the
students to understand, it is essential that their study habits should be developed.
Trying to study on subjects where they have negative feelings will not help them
improve their performance in the subject. Consequently, students’ performance in
mathematics will be affected because they will not have time to study the subject.
Moreover, the Self-Perception Theory by Bem (1972) supports this study. The
theory states that individuals’ actions are interpreted by the way he or she interpret
others and ones’ actions are most of the time influenced by others and not of ones’
own free will as he or she would expect. Similarly, in the case of the students
wherein, most of them think that mathematics is a difficult subject, they will tend to
have the same feelings with others. Thus, whenever they do not understand the
lessons in math, they will have the possibility of thinking that they are not alone. So,
one will justify his performance on the premise that most of the students do not like
math because it is difficult and so he does.
However, if the student feels the other way, then he would develop a positive
attitude towards the subject because he can justify why he likes the subject. With
these, the willingness of the student to learn the subject can help in developing good
study habits on the subject to which the student has a positive attitude. Nagaraju (as
cited in Mendezabal, 2013) stressed that positive attitudes and good study habits are
important factors in achieving good performance in school. It is expected that
students must perform well in school so that they will be able to meet the standards
set by DepEd in order to be promoted to the next level. Failure to do so will result in
students’ retention. However, the “No Filipino Child Left Behind Act of 2010” states
that the state should protect and promote the right of the citizens to quality education
and to take appropriate steps to make such education accessible to all. It is in this
context that students should be provided with equal opportunity to learn in school.
The teachers to ensure learning inside the classroom should address whatever are
the shortcomings of the students. Teachers have to encourage students to develop
positive attitudes towards the subject they are teaching and assist in the students’
development of good study habits. Furthermore, things that would affect their
attitudes and study habits should be minimized in order that a positive development
on the child regarding these variables may be observed. Consequently, a better
performance, especially in mathematics, may be achieved.
The root cause of this gathered data is to assess the attitudes, study habits,
and performance of the junior high school students and it is the same with this study
to evaluate the factors affecting mathematics performance of grade 9 learners
specifically in the student related variables.
Personality Trait Theory. Personality trait theory was propounded by Gordon
Allport. Trait theorists believe in the individuality and uniqueness of persons and the
measurement of traits is defined as habitual patterns of behavior, thought, and
emotion. Trait theory is focused on differences between individuals and identifying
and measuring individual personality characteristics. All the teaching processes in a
typical classroom are influenced by the characteristics and attributes that are peculiar
to the teacher, and as such, personality traits affect instructional processes. Howard
and Heinstrom presented five psychological bases for personality traits in people:
Extraversion: extraverts are adventurous, assertive, frank, sociable, and
talkative. Introverts are quiet, reserved, shy, and unsociable.
Agreeableness: the agreeableness scale is linked to self-sacrifice,
selflessness, caring, and emotional support versus hostility, indifference, self-
centeredness, and jealousy.
Conscientiousness: the conscientious is rigid, goal-focused, and career-
oriented, while the flexible person is more impulsive and easier to be persuaded
from one task to another.
Neuroticism: the persons with a tendency towards neuroticism are more
worried, temperamental, and prone to sadness. People with the alternate
extreme are emotionally stable, calm, and relaxed.
Openness: this factor relates to intellect, openness to new ideas, cultural
interests, educational aptitude, and creativity. These individuals are cultured,
aesthetic, intellectual, and open.

All the personality traits above are expressed in teachers’ disposition often
reflected in the pedagogical processes in form of subject mastery and questioning
behavior, which can predict students’ learning outcomes.
Theory of Education Productivity. An important finding of the Walberg et al.
large-scale causal modeling research was that nine different educational productivity
factors were hypothesized to operate vis- à-vis a complex set of interactions to
account for school learning. Additionally, some student characteristic variables
(motivation, prior achievement, attitudes) had indirect effects (e.g., the influence of
the variable “went through” or was mediated via another variable).
The importance of the Walberg et al. group’s findings cannot be overstated.
Walberg’s (1981) theory of educational productivity is one of the few empirically
tested theories of school learning and is based on the review and integration of over
3,000 studies (DiPerna et al., 2002). Walberg et al. have identified key variables that
affect student outcomes: student ability/prior achievement, motivation,
age/developmental level, quantity of instruction, quality of instruction, classroom
climate, home environment, peer group, and exposure to mass media outside of
school (Walberg, Fraser & Welch, 1986). In the current context, the first three
variables (ability, motivation, and age) reflect characteristics of the student. The
fourth and fifth variables reflect instruction (quantity and quality), and the final four
variables (classroom climate, home environment, peer group, and exposure to
media) represent aspects of the psychological environment (DiPerna et al.,
2002). Clearly student characteristics are important for school learning, but they only
comprise a portion of the learning equation.
More recently, Wang, Haertel, and Walberg (1993) organized the relevant
school learning knowledge base into major construct domains (State & District
Governance & Organization, Home & Community Contexts, School Demographics,

Culture, Climate, Policies & Practices, Design & Delivery of Curriculum & Instruction,
Classroom Practices, Learner Characteristics) and attempted to establish the relative
importance of 228 variables in predicting academic domains. Using a variety of
methods, the authors concluded that psychological, instructional, and home
environment characteristics (“proximal” variables) have a more significant impact on
achievement than variables such as state-, district-, or school-level policy and
demographics (“distal”variables). More importantly, in the context of the current
document, student characteristics (i.e., social, behavioral, motivational, affective,
cognitive, metacognitive) were the set of proximal variables with the most significant
impact on learner outcomes (DiPerna et al., 2002).
In this theory, the nine different educational productivity factors were
assessed by the researcher and some various theories more specifically in
instructions and the elements of this in quantity and quality. Furthermore, this can
support this analysis in gathering the data variables of the study.
The theories above can be utilized by the researcher to make the study
relevant and make it more effective. The theories mentioned can interpret and
explain well the purpose of the framework as well as the two variables. In student
related factors there are two variables mainly the interest and the students’ habits. In
the interest of the students can relate in self - perception theory by Bem (1972), this
can have an impact in their perception. Likewise, students' habits in their ideas or
concepts towards understanding mathematics is difficult for them and have an impact
on their performance. In teacher related factors and in the same way there are
variables that can have a relationship between the specific variables and the
mentioned theories. Gordon Allport (1955), stated in his theory personality traits and
assessed by the researchers to support their claims in teacher disposition affecting
the instructional processes. In educational productivity theory by Welberg (1981),
emphasizing on the quality and the quantity that can be interpreted in the behavior of
the learners. Relating on the variables teaching skills and instructional material it can
be the factors of the perception of the learners and also their performance.
Conceptual Framework
The researchers would like to know the factors affecting mathematics
performance of Indang National High School Perceived by Grade 9 Learners.
Figure 1: Factors affecting Mathematics Performance of Indang National High
School as Perceived by Grade 9 Learners.
The research paradigm shows the key ideas and discussion of the factors
affecting mathematics performance of Indang National High School Perceived by
Grade 9 Learners. The conceptual framework consists of three boxes: Demographic
profile, Student-Related, and Teacher-Related. The first box on the left displays the
demographic profile of the students which includes the sex, math performance -
average grade of 1st and 2nd quarter of the current school year, and type of
curriculum such as general curriculum, and special science curriculum. The second
box is student-related factors consists the interest and study habits of the students.
Finally, the third box is teacher-related factors including personality traits, teaching
skills and instructional materials. This study seeks to determine the factors affecting
mathematics performance of Indang National High School Perceived by Grade 9
Learners.
Study Limitations
This study mainly focuses on the participations of Grade 9 students of Indang
National High School. The research was conducted during school year 2022-2023.
The limitations of this study include their demographic profile which are sex
(male or female), average grade of their first and second quarter in mathematics, and
which type of curriculum they are under or included.
Significance of the Study
The findings of this study were useful to the following entities:
Students. The results of the study would provide students with valuable
information about what factors may affect their mathematics performance. They will
able to have a deep understanding that their interests and study habits in their
mathematics subject may affect their grades or performance in the said course/area.
Mathematics Teachers. The mathematics teachers, who have direct control
over the students, are the ones inside the school who can give the most accurate
assessment of their academic performance in mathematics. The goal of this study
was to persuade teachers that all pupils, disagreeable and likeable, should be given
an equal chance to succeed. This can be achieved by knowing the factors,
specifically the teacher factors: personality traits, teaching skills, and instructional
material, behind the students' mathematics performance. This study will help the
teachers to determine in which factors they need to give more focus and improve.
Pre-Service Teachers. Like for mathematics teachers, this study might be
helpful to pre-service teachers, especially if they are going to teach mathematics.
They will be able to use the information from this study to know what mathematics
teachers they should be in the future to teach their students with the highest quality
of teaching and learning.
Schools. This study may give administrators a better understanding of the
factors: student and teacher factors that may lead to improve mathematics
performance of the students. This can be achieved by informing the students and
mathematics teachers that there are factors that may affect the students’
mathematics performance. Additionally, the students and teachers would view such
initiatives as a commendable effort on the part of the institution.
Future Researchers. Finally, the findings of this study can potentially help
future researchers. This could serve as a resource for a more in-depth study.
Definition of Terms
To provide the readers of the study a greater knowledge about the research,
the following terms are conceptually and operationally defined:
Learners. This is the person or individual who is urged to gain knowledge,
skills, and understand new things through the process of learning. This is the subject
of the study who supply the needed data of the researchers.
Demographic Profile. In this study, the three demographic profiles were
conducted, these are: sex, mathematics performance, and type of curriculum.
Sex – sex is either of the two major forms of individuals that occur in
many species and that are distinguished respectively as female or male.

Mathematics Performance – it measures the mathematical literacy of
the learners to formulate, employ and interpret mathematics in a variety of contexts
to describe, predict and explain phenomena, recognizing the role that mathematics
plays in the world.
Type of Curriculum – in this study, there are two types of curriculums were
conducted in Indang National High School (INHS), these are general and special
science curriculum.
General Curriculum – the curricular content adopted by a public
agency, or schools within a public agency, for students from pre-school to high
school.
Science Curriculum – curriculum that is based on the K to 12 Basic
Program from Grade 7 to Grade 10 except for Technology and Livelihood Education
(TLE) which shall be replaced by advanced Science subjects.
Student-related Factors – in this study, student-related factors are the factor
that may affect the learners’ academic performance in mathematics, under student-
related factors are interest and study habits.
Interest – the state of wanting to know or learn about something or
someone.
Study Habits – is an action such as reading, taking notes, holding
study groups which the students perform regularly and habitually in order to
accomplish the task of learning.
Teacher-related Factors – in this study, teacher-related factors are the factor
that may affect the learners’ academic performance in mathematics, under teacher-
related factors are personality traits, teaching skills, and instructional materials.
Personality Traits – reflects people’s characteristic patterns of
thoughts, feelings, and behaviors.
Teaching Skills – abilities teachers must develop in order to be
successful in the field of education.

Instructional Materials – are those materials used by a teacher to
simplify their teaching, also brings life to learning by stimulating students to
learn.
METHODS
This chapter presents the methodologies employed in the study. This includes
the research design, description of the participants, sampling technique, research
instruments, data analysis and ethical consideration. It provides information
regarding the participants, including who they were and the method by which they
were sampled. The purpose of the study and the factors that led to the selection of
the research design were discussed by the researchers. The methods utilized to
carry out this study are also presented, along with a description of the instruments
used for data collection. Lastly, the researcher discusses the methods that were
utilized to analyze the data.
Research Design
The descriptive-evaluative research method was used in gathering the
needed information for this study. It described the students’ demographic profile and
two factors which are student-related and teacher-related. Specifically, the
researchers utilized a questionnaire related to descriptive-evaluative research
methods which are used to gather information from the respondents without having
any difficulties in answering the questions required for them to have information
regarding factors affecting mathematics performance of Indang National High School
as perceived by grade 9 learners.
Description of the Participants
Grade nine (9) learners were selected for the study as the participants. The
participants who were chosen for this research share these characteristics: a)
student from Indang National High School (INHS), b) grade 9 learner, c) willing to
participate in the study. Grade 9 learners in INHS were classified into general
curriculum and special science curriculum. Learners in the general curriculum or

regular class were those in the normal educational system. Whereas, learners in the
special science curriculum or special science class (SSC) experienced being
subjected to a more advanced Science and Mathematics education.
Sampling Technique
The researchers decided to use the random sampling and total enumeration
sampling technique, to know the number of respondents in Grade 9 to be conducted
in this study. For the researchers to have precise data for getting the levels of
learner-related and teacher-related factors affecting mathematics performance.
Random sampling was used in this study. The participants from the general
curriculum were selected randomly from the population of the grade 9. This sampling
technique is a method of randomly obtaining a representative sample from a
population which can be partitioned into subpopulations (section). Researchers used
random sampling to ensure specific subgroups are present in their sample. It also
ensures that subgroups of the given population are each adequately represented
within the whole sample population of the research study.
Total enumeration sampling was also used for selecting the participants. The
entire section of grade 9 - SSC were also chosen to be the respondents of this study.
The total enumeration sampling is a method in which entails studying the complete
count of the population that possesses a specific set of parameters. The researchers
used total enumeration sampling since it opens up the possibility of seeing data from
the many extremities of population groups. Through this sampling method, it shows
the value and significance of including the entire population to be the participants of
the study.
Curriculum Population Sample Percentage
1 45 3 4
2 45 3 4
3 45 3 4
4 46 2 3
5 44 2 3
6 45 3 4
General 7 45 3 4
8 45 2 3
9 44 3 4
10 44 2 3
11 44 3 4
12 43 4 6
13 43 3 4
Total 578 36 50
Science Curriculum 1 36 36 50
Grand Total 614 72 100
Table 1: Population, Sample and Percentage of Respondents in General and Special
Science Curriculum.
Research Instruments
The research instrument consisted of two parts. The first part of the
questionnaire consists of the items that gather respondents' demographic profile,
such as their name (optional), sex, math performance - average grade of 1st and 2nd
quarter of the current school year, and type of curriculum a) general curriculum, and
b) special science curriculum.
The second part consists of the answer sheet that has two factors which are
student-related: a) interest and b) study habits, and teacher-related: a) personality
traits, b) teaching skills and c) instructional materials. In the student-related section
there are fifteen (15) questions, five (5) for interest and ten (10) for study habits,
while in the teacher-related section there are also 15 questions, 5 for personality
traits, 5 for teaching skills, and 5 for instructional materials. Students need to choose
from 1-never, 2-rarely, 3-sometimes, 4-often, and 5-always, and they need to check
the box or column that corresponds to each question.
The researchers adopted a standardized test of factors affecting the
mathematics performance of learners from Laguna State Polytechnic University
(LSPU) by Jennilyn F. Balbalosa (2010), so the instrument can be considered valid
and reliable. The questionnaire from LSPU assessed the factors that might affect the
mathematics performance of high school students.
The table below will show the scale, degree of agreement, range scale, and
verbal interpretation that will be used in data analysis.
Rating Scale Degree of Agreement Range Scale Verbal Interpretation
5 Always 4.21 - 5.00 Very High
4 Often 3.41 - 4.20 High
3 Sometimes 2.61 - 3.40 Moderate

2 Rarely 1.81 - 2.60 Low
1 Never 1.00 - 1.80 Very Low
Table 2: Scale of Results Scoring and Interpretation
Data Analysis
The following statistical tools were used for the study to arrive at a valid and
reliable answer to the problems with the percentage and weighted mean.
Percentage and Frequency Distribution was used to describe the profile of the
participants in terms of sex, math performance – average grade of 1st and 2nd
quarter of the current school year, and type of curriculum a) general curriculum, and
b) special science curriculum.
The researchers utilized mean and standard error to obtain the weighted
average for the responses to the questionnaire.
The analysis of the research was carried out in SPSS. The researchers
utilized Mann Whitney for paired comparisons and Kruskal Wallis Analysis test was
used to make comparisons of three and more groups.
Ethical Considerations
The researchers will apply the principles of ethical considerations developed
by Bryman and Bell (2007). With regard to the involvement of this study, the
respondents will not be subjected to harm in any ways. Prior to the study, a written
consent will be obtained from the respondents, the Grade 9 students of Indang
National High School. Furthermore, they have rights to withdraw from the study at
any stage if they wish to do so. An adequate degree of confidentiality will be
maintained when handling the data. Any type of misleading information, as well as
biased representation of primary data findings, will be avoided. Lastly, any type of
communication to this study will be done with honesty and transparency.

RESULT AND DISCUSSION
This chapter presents and discusses the relevant results of the gathered data
to be presented in tabular terms and were analyzed and interpreted according to the
problems stated in the study.
Demographic Profile
Table 3. Demographic Profile in terms of Sex
SEX Frequency Percentage %
Male 31 43
Female 41 57
Total 72 100
The table shows the demographic data of the participants: 31 representing
(43%) of the respondents were Male and 41 representing (57%) were Female; a total
of 72 respondents (100%) were gathered.
The questionnaire was self-administered and data from Grade-9 students
were collected, of which 31 are males 41 are female a total of 72 respondents.
Regarding the sex-related terms in this table, females are the majority respondents.
The study entitled, “Women answer to online surveys substantially more frequently
than men” of Smith (2008), which may account for the overrepresentation of female
participants in this study. The result shown above was similar to the finding
conducted by Smith. It is significant to take note of the study's gender distribution
because preconceptions favoring one gender over the other could have an impact on
the findings. The data explains differences seen in students' response rates between
males and females are a result of the values of men and women acting differently in
a gendered environment. The findings of this study point to the need for caution
when assuming that response behavior to online surveys and the data they generate
have no signs of gender bias.

Table 4. Demographic Profile in terms of Mathematics Performance
Mathematics Performance Frequency Percentage %
Did Not Meet Expectation 0 0

Fairly Satisfactory 2 2.78
Satisfactory 15 20.83
Very Satisfactory 42 58.33
Outstanding 13 18.06
Total 72 100
Range: Did Not Meet Expectation: below 75; Fairly Satisfactory: 75-79; Satisfactory:
80-84; Very Satisfactory: 85-89; Outstanding: 90-100
Mean: 87
Verbal Interpretation: Very Satisfactory
The table shows general demographic data for the participants. The
frequency data shows that: There are 2 (2.78%) in the Fairly Satisfactory level, 15
(20.83%) are in Satisfactory level, 42 (58.33%) are in the Very Satisfactory level,
while 13 (18.06%) are in the level of Outstanding on their Mathematics Performance.
It demonstrates that, on average, 42 out of 72 pupils, or 58.33%, are rated as Very
Satisfactory with the mean of 87.
A number of previous studies have investigated the relationship between
college students’ learning styles and academic performance, in fact, Moeinikia and
Zahed-Babelan (2010) and Williams, Brown and Etherington (2013) confirm that
there is a positive link between learning styles and academic performance in the
university settings. Learning style is defined as the characteristics, strengths, and
preferences in the way people receive and process information (Hsieh, Jang, Hwang
& Chen, 2011). The survey's participants were Grade 9 General Curriculum and
Science Curriculum students from Indang National High School. Because they study
the most challenging math topics in the first and second quarter, grade nine students
were chosen as respondents to provide them the chance to show their enthusiasm
for learning mathematics.

Table 5. Demographic Profile in terms of Type of Curriculum
Curriculum Frequency Percentage %
General 36 50
Special Science 36 50
Total 72 100
The survey result shows the two types of curriculums at Indang National High
School; A total of 72 populations and 36 samples from the General Curriculum and
Special Science Curriculum were collected for the study.
The educational program adopted by a public organization, or the schools
that comprise that organization, for students in preschool through secondary
education is referred to as the General Curriculum. Science Curriculum aims to assist
students in developing fundamental scientific concepts and understanding about the
biological and physical components of the world, as well as the methods by which
they do so. Moreover, results from the 2015 Programme for International Student
Assessment (PISA) revealed that one in five students struggled to master enough
math or science concepts (European Commission, 2018; OECD, 2016).
Student-Related Factors Affecting Learners' Mathematics Performance
Table 6. Student-Related Factors Affecting Learners' Mathematics Performance in

terms of Interest and Study Habits.
Student-Related Factor
Standard Verbal
INTEREST Mean
Error Interpretation
1. I make myself prepared for the
3.43 0.086 High
math subject
2. I listen attentively to the lecture
4.18 0.093 High
of my math teacher.
3. I actively participate in the
3.5 0.136 Moderate
discussion, answering
exercises and / or clarifying
things I did not understand.
4. I want to get good grades on
tests, quizzes, assignments 4.69 0.076 Very High
and projects.
5. I get frustrated when the
discussion is interrupted or the 2.8 0.121 Low
teacher is absent.
Total Mean 3.72 0.102 High
STUDY HABITS
1. I do my assignments regularly. 4.32 0.102 Very High
2. I exert more effort when I do
4.06 0.095 High
difficult assignments.
3. I spend my vacant time in
doing assignments or studying 3.04 0.116 Moderate
my lessons.
4. I study the lessons I missed if I
3.67 0.137 High
was absent from the class
5. I study and prepared for
3.93 0.101 High
quizzes and tests.
6. I study harder to improve my
performance when I get low 4.38 0.098 Very High
grades.
7. I spend less time with my
friends during school days to
3.03 0.127 Moderate
concentrate more on my
studies.
8. I prefer finishing my studying
and my assignments first
3.51 0.130 High
before watching any television
programs
9. I see to it that extracurricular
activities do not hamper my 3.39 0.126 Moderate
studies.
10. I have a specific place of study
at home which I keep clean 4 0.140 High
and orderly.
Grand Mean 3. 73 0.110 High
Legend: 1.00 – 1.80 Very Low; 1.81 – 2.60 Low; 2.61 – 3.40 Moderate; 3.41 – 4.20
High; 4.21 – 5.00 Very High
The student’s mathematical performance is impacted by a number of factors.
These elements are split into two groups, including students' interests and study
habits. As stated by Landicho, R. (2021), the different factors that affect the student’s
mathematical performance are study habits and interest which can be considered as
under student-related factors.

Furthermore, in learning, study habits are important because it is the learners'
effective way on how they improve their academic performances. There are a lot of
different types of study habits and it may vary from one student to another. In relation
to the study of Sakirudeen and Sanni (2017), study habits such as notes taking, use
of library, and time allocation has a significant relationship in the student’s academic
performance in mathematics.
In the study, five scenarios were presented to the participants to gauge their
interest in studying mathematics. The data collection reveals that the respondents
have a "High" outcome in some circumstances and a "Very High" result in another,
demonstrating how vital the interest of learners is in studying Mathematics.
Table 6 presented the results of how the respondents’ interest affected their
performance towards Mathematics. Based on the data gathered, only option three
got the Very High with the mean score of 4.69 and this shows that learners got
interested in Math to have good grades. On the other hand, two among the five
options had a mean interpreted as High. Specifically, these interests are preparing
for the Math subject with 3.43 calculated mean and with a mean score of 4.18 which
is listening attentively during class. As a result, among any factors that affect the
interest of the respondents towards Mathematics, (4) having good grades in exams,
quizzes, assignments and projects is the main factor that affects their interest in
Mathematics.
Moreover, the students were also given ten options to identify which among
them are the suitable habits for them. Among the provided study habits, five got High
mean and only two got Very High mean. These options show the factors that affect
the student’s mathematical ability.
Table above presents the top study habits that students use in order for them
to improve their academic performance in Mathematics. The two study habits are (1)
I do my assignments regularly with a 4.32 mean score and (6) I study harder to
improve my performance when I get low grades with a mean score of 4.38. The
results show that among the ten study habits, the respondents’ top habits are
accomplishing their take home activities or assignments and also performing well in
order for them to obtain good grades which is related to the abovementioned result in
Interest. On the other hand, Table 6 also shows that among the ten answers, five of
them were identified as “high” and those five are considered as some of the study
habits of the participants namely; (2) I exert more effort when I do difficult
assignments with mean score of 4.06, (4) I study the lessons I missed if I was absent
from the class with 3.67 mean, (5) I study and prepared for quizzes and tests having
3.93 weighted mean, (8) I prefer finishing my studying and my assignments first
before watching any television programs with 3.51 mean score, and (10) I have a
specific place of study at home which I keep clean and orderly with a mean of 4. This
shows that among the study habits, learners prioritize effort, preparation, and even
the study area. Among these five study habits, the top habits that got the highest
mean is (10) I have a specific place of study at home which I keep clean and orderly,
meaning study area is one of the most important factors as well in accordance with
the learners’ study habits.
Many factors are associated and considered to be part of students’ academic
performance in Mathematics, but not all are effective to each learner. According to
Landicho (2021) there are various factors that contribute to the students’
Mathematics performance. Student-related in both factors with a grand mean of 3.73
and standard error 0.110 which interpreted as Very High. This indicates that in
achieving good performance the learners must apply the best study habits that apply
in their learning and they must create a strong interest towards the subject in order
for them to perform well.

Teacher-Related Factors Affecting Learners' Mathematics Performance
Table 7. Teacher-Related Factors Affecting Learners' Mathematics Performance in

terms of Personality Traits, Teaching Skills, and Instructional Materials.
Teacher-Related Factor
Standard Verbal
PERSONALITY TRAITS Mean
Error Interpretation
1. Has a good relationship with
4.56 0.097 Very High
the students and teachers
2. Shows smartness, confidence
and firmness in making 4.58 0.098 Very High
decisions.
3. Imposes proper discipline and
is not lenient in following the 4.29 0.109 Very High
prescribed rules.
4. Has an appealing personality
with good sense or humor.
5. Is open to suggestions and
opinions and is worthy of 4.61 0.078 Very High
praise.
Total Mean 4.50 0.094 Very High
TEACHING SKILLS
1. Explains the objectives of the
lesson clearly at the start of 4.78 0.063 Very High
each period.
2. Has mastery of the subject
matter
3. Is organized in presenting
subject matters by
systematically following course
outline.
4. Is updated with present trends,
relevant to the subject matter.
5. Uses various strategies,
teaching aids/devices and
techniques in presenting the
lessons.
Total Mean 4.60 0.085 Very High
INSTRUCTIONAL MATERIALS
1. Chalk and blackboard in
explaining the lessons.
2. Workbooks / textbooks 3.44 0.135 Moderate
3. Power point presentations
3.42 0.149 High
(visual aids)
4. Articles 2.40 0.153 Moderate
5. Materials for project
3.72 0.133 High
development
Grand Mean 4.22 0.101 Very High
Legend: 1.00 – 1.80 Very Low; 1.81 – 2.60 Low; 2.61 – 3.40 Moderate; 3.41 – 4.20
High; 4.21 – 5.00 Very High
Teacher-related factors have been shown to have a major impact in
mathematics performance of students in Grade 9 Learners. Table 7 shows the
Teacher-Related factors affecting learners' mathematics performance including
personality traits, teaching skills, and instructional materials.
The influence of teachers' personality traits on the performance of Grade 9
learners in Mathematics was examined. The data revealed that the personality traits
associated with teachers had a high mean and standard error, indicating a strong
presence of these traits within the sample. The study found that a majority of
students expressed motivation when their teachers demonstrated openness to
suggestions and opinions, as well as when they were deserving of praise. Students
reported high mean scores and low standard errors for these traits. Additionally,
some students were motivated by teachers who exhibited qualities such as
intelligence, confidence, and firm decision-making, while others were motivated by
positive relationships established with their teachers. These factors also received
relatively high mean scores. Furthermore, certain students found motivation when
their teachers had an appealing personality combined with a good sense of humor,
while others were motivated by teachers who imposed appropriate discipline and
adhered strictly to prescribed rules. These factors received slightly lower mean
scores but were still significant.
Overall, the results indicate that a significant proportion of students display
high motivation when their teachers possess positive personality traits. The study
suggests that teachers should focus on being receptive to students' suggestions and
opinions, deserving of praise, and should work on establishing good relationships
with their students and other teachers. This implies that mathematics teachers should
actively seek students' input and maintain positive interactions within the classroom
and school environment.
Khalilzadeh et al. (2021), emphasized the importance of teachers who
possess traits such as duty, discipline, consideration, competence, and achievement
striving. These qualities were found to strongly influence students' desire to engage
in activities for the purpose of learning, exploring new ideas, and developing
knowledge.
The study suggests that teachers' conscientiousness personality trait is
strongly associated with students' motivation, particularly intrinsic motivation. Intrinsic
motivation refers to the internal drive and interest in learning and exploring new
things. This implies that conscientious teachers who effectively display discipline,
consideration, competence and direct their impulses can foster a greater incentive for
students to engage in diverse learning activities. By understanding the relationship
between conscientiousness, motivation, and academic achievement, educators can
further enhance teaching practices and create an environment that fosters students'
intrinsic motivation and overall success.
Next, the study examined how teachers' teaching skills influenced Grade 9
learners' academic performance in Mathematics. The data indicated a significant
presence of these teaching skills, as reflected by high mean scores and standard
errors. Students were most motivated when the lesson objectives were clearly
explained. Furthermore, a few students found motivation when the teacher
demonstrated subject matter mastery, were organized in presenting the subject
matter, used various instructional strategies and aids, and stayed updated with
relevant trends. Consequently, these findings suggest that teachers' teaching skills
have a positive impact on students' motivation in Mathematics. Clear objective
settings are the vital factor that contribute to students' motivation and potentially
enhance their academic performance in Mathematics.

Hanushek et al. (2021) conducted a study to examine the impact of teacher
skills on student performance in various countries. He indicates a positive
relationship between teaching skills and student performance. Interestingly, the
correlation between student performance and teacher skills was found to be stronger
than the correlation between student performance and adult skills at the country
level. These results suggest the importance of teacher skills in influencing student
outcomes and highlight the need to focus on enhancing teaching abilities to improve
overall student performance.
Lastly, the study investigated the impact of teachers' instructional materials on
the performance of grade 9 learners in Mathematics. The findings indicate that
certain instructional materials had higher mean scores, reflecting increased student
motivation. Specifically, the traditional method of using chalk and blackboard during
lesson explanations yielded the highest mean score, indicating a significant number
of motivated students. Additionally, a lower proportion of students found motivation
when the teacher utilized materials for project development and
workbooks/textbooks, used PowerPoint presentations as visual aids, and provided
articles to the lesson. Considering all the instructional materials used, it can be
concluded that instructional materials significantly influence student motivation. The
chalk and blackboard method were found to be the most effective in this study, as it
resulted in the majority of students exhibiting higher motivation levels.
The study conducted by Ayodele (2020) examined the significance of
instructional materials in the teaching-learning process and their impact on students'
academic performance. The findings underscored the important role instructional
materials play in engaging students' senses and facilitating information recall.
These findings align with the perspective presented by Yusuf (2005),
emphasizing the crucial role of instructional materials in the teaching-learning
process. The availability and appropriate selection of various materials, such as

textbooks, chalkboards, kits, guides, and audio-visual aids, were identified as vital
components. These materials contribute significantly to enhancing students'
understanding of concepts, leading to improved academic performance and
strengthening their cognitive abilities. Furthermore, the study emphasized the
importance of teachers' competences and professional knowledge in utilizing
instructional materials effectively. Teachers who possess the necessary expertise
can integrate instructional materials into their teaching methods, thereby maximizing
their impact on students' academic performance.
Overall, the research findings demonstrate the significance of these teacher-
related factors - Personality Traits, Teaching Skills, and Instructional Materials - in
influencing learners' mathematics performance. The grand mean of 4.22,
accompanied by a standard error of 0.101, indicates a very high level of
effectiveness in these factors. These results highlight the importance of recruiting
and supporting teachers who possess favorable personality traits, continually
developing their teaching skills, and providing access to quality instructional
materials. By prioritizing these factors, educators and policymakers can strive to
improve students' mathematics performance and foster a positive learning
experience in the subject.
Alshammari et. al (2017) found that teacher-related factors have the greatest
impact on academic performance. Richardson and colleagues (2001) further support
these findings and recommend that teachers embody positive qualities, provide
constructive feedback, create a respectful learning environment, promote unity in
diversity, and demonstrate effective leadership and teaching skills to foster overall
student achievement and school development. These insights emphasize the
importance of empowering teachers to enhance student performance and create a
conducive learning environment.

Significant Difference on Perceived Factors Affecting Mathematics
Performance When Grouped According to Demographic Profile
Table 8. Significant Difference on Student–Related Factors Affecting Mathematics

Performance in terms of Sex
Student– Mann-
Sex Mean P-Value Remarks
Related Whitney U
Female 3.77 Failed to
Interest 571.500 0.463
Male 3.68 Reject Ho
Female 3.85
Study Habits 453.500 0.038 Reject Ho
Male 3.58
Total 512.500 0.251
Male 3.63 Reject Ho
Legend: Reject Ho: P-Value ≤ 0.05; Accept Ho: P-Value > 0.05
This study conducted an analysis of significant differences in student-related
factors affecting mathematics performance, specifically in terms of sex. The results
showed that interest did not have a significant difference between male and female
students, as the p-value was greater than the assumed level of significance (p >
0.05). Therefore, the null hypothesis for interest was accepted, indicating no
significant difference based on sex. However, study habits exhibited a significant
difference between male and female students, as the p-value was less than the
assumed level of significance (p < 0.05). The null hypothesis for study habits was
rejected, indicating a significant difference based on sex. Consequently, when
considering all student-related factors and grouping the participants based on sex,
there was no significant difference. The p-value for the total student-related factors
was greater than the assumed level of significance, leading to the acceptance of the
null hypothesis. This suggests that, in terms of sex, there is no significant difference
in the impact of student-related factors on mathematics performance.
The study by Peteros et al. (2020) and the findings of Tella (2010) suggest
similar levels of self-concept between male and female students in Mathematics,
wherein there was no significant difference in self-concept based on

gender. Therefore, it can be inferred that both male and female students possess
similar perceptions of their mathematical abilities.
The study by Egorova (2016) presents contrasting results, wherein he
analyzed sex differences in self-concept and academic performance in Math among
Russian high school students. The study revealed a sex difference in mathematics
achievement, with girls achieving higher grades compared to boys. Moreover, girls
had higher self-concept scores in Math tests, while boys performed better on the
actual tests compared to their female counterparts. These discrepancies highlight the
complexity of gender differences in self-concept and academic performance in
Mathematics, which may vary across different contexts and populations.

Performance in terms of Mathematics Performance
Kruskal-
Student– Mathematics Mean P-Value Remarks
Wallis
Related Performance
Statistics
Fairly
3.50
Satisfactory
Satisfactory 3.57 Failed to
Interest 5.744 0.125
Very Reject Ho
3.70
Satisfactory
Outstanding 4.05
Fairly
3.05
Satisfactory
Satisfactory 3.43
Study Habits 10.424 0.015 Reject Ho
Very
3.75
Satisfactory
Outstanding 4.11
Fairly
3.28
Satisfactory
Total 8.084 0.070
Very Reject Ho
3.73
Satisfactory
Outstanding 4.08
Table 9 shows the results of significant difference on student-related factors
affecting mathematics performance according to respondents’ mathematics
performance. The sub-factor interest had Kruskal-Wallis = 5.744 and p-value of
0.125. Meanwhile, the sub-factor study habits had Kruskal-Wallis = 10.424 and p-
value of 0.015. The total of Kruskal-Wallis = 8.084 and p-value = 0.070 in student-
related factor.
The p-value of interest was greater than the significance value = 0.05,
therefore the null hypothesis was accepted. This implies that when the respondents
were grouped according to their mathematics performance in their interest, it has no
significant difference. However, the p-value of study habits was less than 0.05,
therefore the null hypothesis was rejected. It implies that when the respondents were
grouped according to mathematics performance in their study habits, it has
significant difference. All in all, the p-value was greater than 0.05, hence the null
hypothesis was accepted. This implies that when the respondents were grouped
according to mathematics performance in student-related factor, it has no significant
difference.
Khan (2016) described poor study habits as the most important reason for
students’ academic failure. Abid (2006) stated that better study habits leads to better
achievement. Riaz et al (2002) in their research work on the relationship between
study habits and achievement concluded that there exists a significant and positive
relationship between achievements of students and study habits. They also observed
that good study habits lead to good achievement. Sarwa (2002) concluded that high
achievers have better study habits than that of low achievers. Some students claim to
thrive in any environment even with music in the background but studies have proved
that it is only a peaceful environment that can yield optimum results in a studying
situation. It is essential to remember that a good environment makes it much easier
for students to concentrate. If students' study habits are bad, eventually such
students cannot achieve well in mathematics (Odiri, 2015). As the result shows in
table 9, researchers were able to reject the null hypothesis. Therefore, the study
habits of the students are affecting students’ mathematics performance.
The students’ attitude is seen to affect their performance in mathematics in
different studies (Ayebale, 2020). In comparative studies have found that there was a
direct link between students’ attitudes towards Mathematics and student outcomes.
This is said to prevent them from experiencing the richness of Mathematics and the
many approaches that could be used to develop competence in the subject
(Odogwu, 2015). Hence, the said studies do not support this study. As a result,
researchers cannot fail to reject the null hypothesis. In terms of the difference on
student factor and student mathematics performance, this research failed to find a
strong connection between the two even though it supported earlier findings about
how students' attitudes affect their performance in mathematics. This might be as a
result of the fact that a number of factors, rather than just the students’ attitude, affect
how well students perform. Consequently, even though the attitude of the student
does affect the performance of the students, it is not the only factor.

Performance in terms of Curriculum
Student– Type of Mann- P-
Mean Remarks
Related Curriculum Whitney U Value
General 3.87
Interest 452.500 0.026 Reject Ho
Special Science 3.59
General 3.71 Failed to
Study Habits 656.000 0.928
Special Science 3.76 Reject Ho
Total 554.250 0.477
The table 10 reveals the results of significant difference on student-related
factors affecting mathematics performance in terms of curriculum. The interest had a
Mann-Whitney U = 452.500 and p-value = 0.026. While, study habits had Mann-
Whitney U = 656.000 and p-value = 0.928. In total, the student-related factors had a
total of Mann-Whitney U = 554.250 and p-value = 0.477.
The p-value of interest was less than 0.05, the assumed level of significance,
hence the null hypothesis was rejected. This means that when the respondents were
grouped according to curriculum in interest, there were significant difference.
Whereas, the p-value of study habits was greater than the assumed level of
significance, thus the null hypothesis was accepted. This implies that when the
respondents were grouped according to curriculum in study habits, there were no
significant difference. Overall, the p-value was greater than the assumed significant
level, therefore the null hypothesis was accepted. This means that when the
participants were grouped according to curriculum in student-related factors, there
were no significant difference.
In this study, the student-related factors that affect the mathematics
performance of the learners were interest and study habits. The table above shows
that student-related factors that affects the academic performance of learners in the
special science curriculum were not notably different from students in the general
curriculum. According to study of Heize, Reiss and Francisca (2005), mathematics
achievement may be predicted by a student’s interest in learning mathematics. The
more a student is interested in mathematics the higher possibility to boost their
academic performance. However, the result shows the interest affecting mathematics
performance of students from the general curriculum was significantly different from
the students in the special science curriculum.

Table 11. Significant Difference on Teacher–Related Factors Affecting Mathematics
Performance in terms of Sex
Teacher– Mann-
Sex Mean P-Value Remarks
Related Whitney U
Personality Female 4.67
342.500 0.001 Reject Ho
Traits Male 4.27
Teaching Skills 592.000 0.608
Male 4.56 Reject Ho
Instructional Female 3.49 Failed to
736.500 0.248
Materials Male 3.67 Reject Ho
Total 557.000 0.286
Male 4.17 Reject Ho
The table 11 reveals the results of significant differences between teachers–
related factors affecting mathematics performance in terms of sex. The personality
traits had a Mann-Whitney U = 342.500 and p-value = 0.001. On the other hand,
teaching skills had Mann-Whitney U = 592.000 and p-value = 0.608. The instructional
materials had a Mann-Whitney U = 736.500 and p-value = 0.248. Overall, the
teacher-related factors had a total of Mann-Whitney U = 557.000 and p-value =
0.286.
The p-value of personality traits was less than 0.05, the assumed level of
significance. Thus, the null hypothesis was rejected. This implies that when the
respondents were grouped according to personality traits in female and male were
significantly different. While, the p-value of teaching skills was greater than the
assumed level of significance. Thus, the null hypothesis was accepted. This implies
that when the respondents were grouped according to teaching skills in female and
male was not significantly different. Lastly, the p-value of instructional materials was
greater than 0.05 the assumed level of significance. Hence, the null hypothesis was
accepted. This means that when the respondents were grouped according to
instructional materials in female and male, it was not significantly different. In total,
the p-value was greater than the assumed significant level, therefore the null
hypothesis was accepted. This means that when the participants were grouped
according to teacher-related factors female and male were not significantly different.
Onderi (2015), teachers’ beliefs about mathematics such as the usefulness of
mathematics, the way mathematics should be learned, the difficulty or ease of
Mathematics, as well as gender ability and beliefs also affect their attitude towards
the subject and impact on students’ performance. As the result shows that there is an
effect in students’ mathematics performance when grouped according to their sex by
teacher’s personality traits. Comparing female and male, females were the most
affected by the teacher’s personality traits. Learning resources and textbooks
availability in mixed schools, girls only school and boys only schools is still below the
expected standard. It seems to be the main cause of poor performance in
mathematics as seen from the results above. A majority of respondents disagreed
that there is enough learning material in schools. Textbooks at school libraries are
motivators for students to engage in personal study and hence improve outcomes in
subjects such as mathematics (UNESCO, 2009). Samuelsson (2016) found some
differences in how boys and girls perceive their classroom setting and some
differences in boys’ and girls’ relationship to mathematics. According to the classroom
setting, the study found that boys feel that they use group work more than the girls
do. Boys also feel that they have an influence over the content and are more involved
during the lesson than girls. It is statistically significant that students who feel that
they participate in decisions regarding working methods in the classroom and what
content should be taught perform better than students who do not participate in these
types of decisions. Such results are in contrast to earlier findings (Gherasim, 2013)
who found no significant correlation between the availability of teacher support and
better grades. Such a result could be understood as boys’ perceptions that they are
seen and heard in the classroom, as an aspect of being offered more communication
with teachers, affect the sense of participation that has a certain influence or at least
being involved in decision-making. Overall, the researchers found that there is still no
significant difference on teacher factors affecting mathematics performance when the
respondents were grouped according to their sex.

Performance in terms of Mathematics Performance
Kruskal-
Teacher– Mathematics Mean P-Value Remarks
Wallis
Related Performance
Statistics
Fairly
4.60
Satisfactory
Personality Satisfactory 4.15
8.285 0.040 Reject Ho
Traits Very
4.52
Satisfactory
Outstanding 4.80
Fairly
4.10
Satisfactory
Teaching Satisfactory 4.48 Failed to
1.971 0.578
Skills Very Reject Ho
4.60
Satisfactory
Outstanding 4.82
Fairly
3.60
Satisfactory
Instructional Satisfactory 3.59 Failed to
0.443 0.931
Materials Very Reject Ho
3.59
Satisfactory
Outstanding 3.48
Fairly
4.10
Satisfactory
Total 3.566 0.516
Very Reject Ho
4.24
Satisfactory
Outstanding 4.36
Table 12 shows the results of significant difference on teacher-related factors
affecting mathematics performance according to respondents’ mathematics
performance. The sub-factor personality traits had Kruskal-Wallis = 8.285 and p-
value of 0.040. Meanwhile, the sub-factor teaching skills had Kruskal-Wallis = 1.971
and p-value of 0.578. Also, the sub-factor instructional materials had Kruskal-Wallis =
0.433 and p-value of 0.931. The total of Kruskal-Wallis = 3.566 and p-value = 0.516
in student-related factor.
The p-value of personality traits was less than the significance value = 0.05,
therefore the null hypothesis was rejected. This implies that when the respondents
were grouped according to their mathematics performance in the personality traits of
the teacher, it has significant difference. However, the p-value of teaching skills was
greater than 0.05, therefore the null hypothesis was accepted. It implies that when
the respondents were grouped according to mathematics performance in the
teaching skills of the teacher, it has no significant difference. Meanwhile, the p-value
of instructional materials was greater than 0.05, thus the null hypothesis was
accepted. All in all, the p-value was greater than 0.05, hence the null hypothesis was
accepted. This implies that when the respondents were grouped according to
mathematics performance in teacher-related factor, it has no significant difference.
In this study the teachers’ personality trait is strongly mentioned to influence
student achievement in mathematics. The learner draws from the teacher’s
disposition to form his own attitude which may affect her learning outcomes (Mazana,
2020). Positive teacher attitude towards Mathematics was significantly related to high
achievement in pupils (Okyere, 2013). Also studies that specifically focused on
teachers’ attitude and students’ achievement in mathematics found out that teachers’
attitude contributed to students’ academic performance and behavior (Ndifor, 2017).
The teaching methods, are key in enabling the learner understand underlying and
key concepts (Sule, 2018). Teaching Method can best be defined as the type of
principal & methods used for Instruction. There are many types of teaching methods,
depending on what information or skill the teacher is trying to convey. The methods
used in teaching may vary from one country to another, depending on the information
or skills being taught (Mohd, 2020). A variety of strategies & method are used to
ensure that all students have equal opportunities to learn. If the teaching method is
not favoring understanding the students will achieve less as compared to the other
(Ayebale, 2020). Thus, based on the results that the researchers gather, there is no
significant difference on students’ mathematics performance in teacher skills and
instructional materials. Given the overall results, that there is no significant difference
on mathematics performance in teacher-related factor, study said that if the teacher
is ineffective, students under the teacher’s tutelage will achieve inadequate progress
academically (Kimani, Kara, & Njagi, 2013) and this is regardless of how similar or
different the students are in terms of individual potential in academic achievement
(Obilor, 2019). As a result, researchers cannot fail to reject the null hypothesis. In
terms of the difference on teacher factor and student achievement, this research
failed to find a strong connection between the two even though it supported earlier
findings about how teachers' attitudes affect students' academic performance. This
might be as a result of the fact that a number of factors, rather than just the teacher's
attitude, affect how well students perform. Consequently, even though the attitude of
the teacher does affect the performance of the students, it is not the only factor.

Performance in terms of Curriculum
Teacher– Type of Mann-
Mean P-Value Remarks
Related Curriculum Whitney U
Personality General 4.37
856.000 0.017 Reject Ho
Traits Special Science 4.63
General 4.50
Teaching Skills 827.500 0.036 Reject Ho
Special Science 4.71
Instructional General 3.57 Failed to
649.500 0.986
Materials Special Science 3.57 Reject Ho
Total 777.667 0.346
The results from table 13 exhibits significant difference on teacher-related
factors affecting mathematics performance in terms of curriculum. The personality

traits had a Mann-Whitney U = 856.000 and p-value = 0.017. The teaching skills had
a Mann-Whitney U = 827.500 and p-value = 0.036. And the instructional materials
had a Mann-Whitney U = 649.500 and p-value = 0.986. Generally, the teacher-
related factors had a total of Mann-Whitney U = 777.667 and p-value = 0.346.
The p- value of personality traits and teaching skills were less than 0.05, the
assumed level of significance, so the null hypothesis was rejected. These mean that
when the respondents were grouped according to curriculum in personality traits and
teaching skills, there were significant difference. But then, the p-value of instructional
materials was greater than the assumed level of significance, hence the null
hypothesis was accepted. This indicates that when the respondents were grouped
according to curriculum in instructional materials, there were no significant difference.
Overall, the p-value was greater than the assumed significant level, therefore the null
hypothesis was accepted. This means that when the participants were grouped
according to curriculum in teacher-related factors, there were no significant
difference.
In the current study, the teacher-related factors that affect the mathematics
performance of the learners were personality traits, teaching skills, and instructional
materials. Table 13 indicates that teacher-related factors that affect the academic
performance of learners in the special science curriculum were not notably different
from students in the general curriculum. In line with this, the academic achievement
of students is significantly influenced by the personalities of the teacher, as stated by
Noreen et. al. (2019). Building a good relationship with students, being a role model,
having a good sense of humor, and being open to suggestions are some of the many
personality traits that a teacher must possess. Also, as stated in the study of
Oluwadayo et.al. (2020), the academic achievements and failures depend heavily
and is an indicator of the teaching skills of a teacher. This implies that teaching skills
also greatly contribute to the academic performance of learners. On the other hand,
the results above exposed that the personality traits and teaching skills affecting
mathematics performance of students from the general curriculum was significantly
different from the students in the special science curriculum.
CONCLUSION
The study was carried out to provide a systematic review and synthesis of the
factors affecting students’ performance in Mathematics in Grade 9 students of Indang
National High School. Based on researchers’ findings, the researchers therefore
conclude that:
1. The demographic profile such as sex which the females are the dominant
respondents in this study, while in mathematics performance the average
grade of the respondents is 87 that fall under the Very Satisfactory, lastly for
the type of curriculum, 36 respondents from special science curriculum and
36 randomly selected from general curriculum.
2. Student factors affecting the mathematics performance of the students by
their interest in mathematics was high, while in study habits, it was also highly
affecting students’ mathematics performance. Overall, student-related factors
are highly affecting on students' mathematics performance.
3. Teacher factors affecting the mathematics performance of the students by
their teacher’s personality traits and teaching skills were very highly affecting,
while in teachers use of instructional materials was highly affecting. All in all,
teacher factors (1) personality traits, (2) teaching skills, and (3) instructional
materials, were very highly affecting on the mathematics performance of the
students.
4. Factors such as, student-related factors: (1) interest and (2) study habits, and
teacher-related factors: (1) personality traits, (2) teaching skills, and (3)
instructional materials, have not been widely found to affect students’
performance in mathematics. From this review, it is imperative that these
factors may not be addressed early in the students’ career and academic
performance in mathematics. Therefore, the researchers conclude that when
the respondents were grouped according to their demographic profile in
student and teacher factor, it does not affect their mathematics performance.
RECOMMENDATION
The researchers found out that the perceived factors, student and teacher-
related factors, do not affect the mathematics performance of the respondents. The
following were recommended to:
For students, it is recommended for them to actively participate and engage
themselves in the teaching and learning process, and utilize the time to review, read
and study during vacant time and when the teacher is not around. Student
involvement in the process of instruction and spending time to study can increase the
student’s academic performance, not only in Mathematics but also in other subjects.
For Mathematics teachers, having a good personality and showing
professionalism at work highly affects the mathematics performance of learners. It is
suggested to them to build a good connection with students to keep their interest in
touch with the subject resulting in high academic performance in mathematics.
For future researchers, it is recommended to broaden the participants and
select other schools to have accurate data to be gathered. Since, the researchers in
this study only focused on grade 9 learners at Indang National High School.
These specified individuals need to be consistent in their efforts in order for
the students to be enlightened to the perceived factors that influence their
mathematics performance.
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Factors Affecting Mathematics Performance of

Indang National High School as Perceived

Undergraduate Research Project

CARIAGA, SHERY MAE L.

related factors has effect in mathematics performance of grade 9 students of Indang

National High School. Descriptive-evaluative under quantitative method was used to

sampling technique, to know the number of respondents in Grade 9, consisting of

respondents were grouped according to demographic profile: (1) sex, (2)

to reject in both student and teacher related factors. In conclusion, there is no

significant difference on student and teacher related factors in students’ mathematics

performance according to their demographic profile. The researchers therefore

Keywords: sex, mathematics performance, type of curriculum, student-related

factors, teacher-related factors.

Mathematics, in general, had a negative interpretation from the perspective of

related subject. When we say Mathematics, we automatically think of it as numeracy,

learner’s interests towards mathematics.

Student-related factors are being demonstrated to have significant effects on

mathematics performance. A variety of studies believe that a student's attitude is an

important factor in determining whether they perform well or poorly in mathematics

outlook prevents effective learning and subsequently has an impact on performance.

toward learning mathematics.

Teacher-related factors have been shown to have a major impact in

specifically focused on teachers’ attitude and students’ achievement in mathematics

conclude that this sub-factor affects the students' performance in mathematics.

strategy does not promote understanding.

Through this study, the researchers aimed to know if the mathematics

teacher-related factors, which are factors toward educational matters, is essential,

which results in intense learning and excellent educational achievement.

Statement of the Problem

1. What is the demographic profile of the participants in terms of:

1.2. Mathematics performance

1.3. Type of curriculum

performance in terms of:

2.2. Study habits

3. What are the teacher-related factors affecting learners' mathematics

performance in terms of:

3.1. Personality traits

3.2. Teaching skills

3.3. Instructional materials

4. Is there any significant difference on the following perceived factors

when grouped according to demographic profile?

Ho: There is no significant difference on the following perceived factors when

grouped according to demographic profile.

Theoretical framework is the structure that can hold or support a theory of a

In this framework the researchers produce a theoretical composite to support

The investigation is moored on the hypothesis of Affective-Cognitive

individuals’ affective component will produce changes in ones’ cognitive component

subject. However, a student with a positive attitude towards a subject will be

motivated to perform well because he or she thinks that he or she is capable of

achieving in that subject.

In general, students do not like mathematics. Difficulty in understanding the

students to understand, it is essential that their study habits should be developed.

improve their performance in the subject. Consequently, students’ performance in

math because it is difficult and so he does.

important factors in achieving good performance in school. It is expected that

the shortcomings of the students. Teachers have to encourage students to develop

on the child regarding these variables may be observed. Consequently, a better

performance, especially in mathematics, may be achieved.

specifically in the student related variables.