3 END Thesis

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Chapter 1

THE PROBLEM AND ITS SETTING

Introduction

Mathematics learning is a complex and dynamic process (Luitel, 2002).

Mathematics educators always hope that students can understand what is being

taught and not just memorize facts or merely apply procedures for solutions

(Kazemi, 1998). In this endeavor, the student not only learns to solve problemsbut thinks more deeply about why the method gives the solution.

However, determinants of students' performance have been the subject of

ongoing debate among educators, academics, and policy makers. There have

been many studies that sought to examine this issue and the findings of these

studies point out to hard work and discipline, previous schooling, parents

education, family income and self-motivation as factors that can explain

differences in students' grades.

Education stakeholders believe that students should have opportunities to

explore calculus concepts in various forms. Student should be able to experience

calculus concepts symbolically, numerically, and graphically (Ganter, 2001). In

addition, students should have the ability to communicate such concepts both

orally and in writing (ibid).


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Nevertheless, the fact remains that many students have difficulties with learning

calculus. Some of the difficulties stem from not thoroughly learning algebra, lack

of problem solving skills, or lack of study skills. In fact, Marcoff (1985) stated that

calculus cannot be learned passively that is, as the subject builds, the student

must continually master ideas and techniques in order to profitably continue. He

further asserts that calculus plays an important role in learning and degree

completion requirements for other courses. It is a higher, more complex

mathematics subject. It needs foundation on subjects like Algebra, Trigonometry,

and Analytic Geometry. In taking this subject, students are confronted with the

limit concept involving calculations that are no longer performed by simple

arithmetic and algebra.

According to Blackwell and Henkin,(1989), it is not possible to teach all

people all of the mathematics skills that could be taught. The same is true with

students taking up Differential Calculus, a subfield of mathematics. It provides

the foundation for understanding higher-level science, mathematics, and

engineering courses.

Further, Sorby and Hamlin (2001) have pointed out that Differential

Calculus is the starting point in mathematics instruction. Due to poor

performance of students in calculus in the last ten years, the undergraduate

calculus course has attracted an unprecedented level of national interest.

According to Thorndike, poor performance in Calculus may be attributed

to weak foundation in the topic and failure to master the basic concept.


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Studies on attitudes toward calculus are scarce. This research was

designed to provide quantitative data to help determine attitudes toward

calculus among students and the extent by which some factors influence their

performance in the said subject. Researchers, faculty and administrators may

gain a better understanding of their students as a result and put resources and

programs in place to better serve students to successfully assist them through

their calculus classes.

In our elementary grade we usually have positive attitudes towards

mathematics until we reach high school. However, as we progress our attitude

became less positive when difficulty in mathematics started. It is the time when

we enrolled the subject Differential Calculus. And it is not only true to us but to

all who enrolled in the said subject either you are education students,

engineering students or information technology students and many others.

Statement of the Problem

This study determined the relationship between the attitude and factors

affecting performance in differential calculus of students in the College of

Education and College of Engineering, Samar State University, Catbalogan City,

during the school year 2012-2013.

Specifically, this study seeks answers to the following questions:

1. What is the profile of the student-respondents in terms of the following:

1.1sex;


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1.2 course; and

1.3 academic performance in Differential Calculus?

2. What is the student- respondents performance in Differential Calculus

based on the result of the achievement test?

3. To what extent are the following factors influence the performance of

student-respondents in Differential Calculus:

3.1 attitude towards Differential Calculus;

3.2 instructional materials;

3.3 teaching strategies?

4. Is there a significant relationship between factors and profile of student-

respondents in terms of academic performance in Differential Calculus?

5. Is there a significant relationship between achievement test and factors

influencing academic performance in Differential Calculus?

6. Is there a significant difference between the attitude towards

Differential Calculus between Education and Engineering Students?

Hypotheses

On the bases of the specific problems, the following hypotheses were

tested:

1. There is no significant relationship between factors and profile of

student-respondents in terms of academic performance in Differential Calculus?


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2. There is no significant relationship between achievement test and

factors influencing academic performance in Differential Calculus?

3. There is no difference in attitude towards Differential Calculus between

Education Students and Engineering Students?

Theoretical Framework

The present study finds theoretical basis in the Theory of Behaviorism

espoused by Watson, as cited by Gregorio (1988). The said theory maintains that

learning is any change in behavior of an organism. Such change may range from

the acquisition of knowledge, simple skill, specific attitude and opinions. It may

also include innovation, elimination or modification of response.

The theorist emphasizes that the response most frequently associated with

stimulus will be elicited by that same stimulus. To him, the unit of stimulus and

response become the basic building blocks of behavior. As such, the teacher

chooses the pattern according to which he is going to mold the learners and then

goes to work. He sets up situation in which the learners can successfully

accomplish the task. A students success provides a particular situation which

offers constancy of stimulation sufficient to form bonds and habits and provides

adequate practice of them. Thus, the students success is mirrored in his

performance in certain learning areas such as Calculus.

The present study also finds basis on the Functional-Structural Theory by

Solomon (www.logic.Stanford.edu) . The said theory stresses out that the role of
http://www.logic.stanford.edu/http://www.logic.stanford.edu/


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education is to equip the individuals with the necessary skills and knowledge

that will make them functioning members of the society. In addition, this theory

emphasizes that it is the societys structure that makes it possible for members to

interact with one another and eventually gather as much knowledge and skills as

possible.

Based on the theory, the performance of a person in a particular field is

what he does in it. It is one of the determining factors of his being a person in

relation to the society as a whole. There are various factors that contribute to a

persons performance in any fi eld. Generally, motivation, learning and socio-

economic background are some of the factors that influence a persons

performance. The question then is that the performance of a person in a

particular field may be influenced by factors that he encounters in school.

This study finds theoretical basis in Festigers Cognitive Dissonance

Theory. According to Leon Festiger (1957), there is a tendency for individuals to

seek consistency among their cognitions (i.e., beliefs, opinions). When there is an

inconsistency between attitudes or behaviors (dissonance), something must

change to eliminate the dissonance. In the case of a discrepancy between

attitudes and behavior, it is most likely that the attitude will change to

accommodate the behavior. Dissonance occurs most often in situations where an

individual must choose between two incompatible beliefs or actions. The greatest

dissonance is created when the two alternatives are equally attractive.

Furthermore, attitude change is more likely in the direction of less incentive since


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subject in order for the students to have a good performance. He must also use

instructional materials and teaching strategies to deliver the subject in its easiest

way so that students will enjoy and find it interesting rather than a complicated

one. Thus, the students success is mirrored in his performance in certain

learning areas such as Calculus.

Conceptual Framework

Figure 1 presents the conceptual framework of the study. This illustrates

the process of how this research was conducted.

The base frame of the schema contains the respondents of this study from

the College of Education and College of Engineering of Samar State University,

Main Campus, Catbalogan City which is also the research environment as well as

the time frame during which this study was conducted during the school year

2013-2014. As it is shown, the respondents of this study are education and

engineering students of Samar State University, which serves as the research

environment. This study will be conducted during the school year 2012-2013.

The said base frame is connected to a bigger higher frame which contains

the research process. As it is seen in the schema, the research is descriptive co-

relational, as indicated by the double-edge arrow connecting the smaller frames.

The box on the right represents the factors affecting performance in Differential

Calculus such as attitude, teaching strategies, and instructional materials. This is

connected to the two boxes at the left side represents profile of student-


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respondents such as sex, course, and academic performance in Differential

Calculus and Achievement Test.

This large frame is then connected upward to a smaller box representing

the findings and recommendations. The smaller box representing the findings

and recommendations is also connected downward to the bottom box which

represents the feedback mechanism of the study, then to the next upper box

representing the goal of study which is improved performance in Differential

Calculus.

This study will correlate the student- respondents profile in terms of their

and sex, course academic performance in Differential Calculus as shown in the

box at the left of the bigger frame, and their attitude towards Differential

Calculus, shown at the uppermost portion in the right of the bigger frame. In

addition, the same student- respondents profile will also be correlated with the

factors that affect their performance in Differential Calculus relative to

instructional materials and teaching methods, shown at the lowermost box at the

right of the bigger frame.

The results of this study will serve as recommendations for the

improvement of the student- respondents attitude towards Differential Calculus

and their academic performance in the subjects, as shown in the uppermost

frame.


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Significance of the Study

This study provides benefits to the students, teachers, education

stakeholders, and future researchers.

Students . The students would essentially acquire insights relative to their

attitude towards Differential Calculus and their academic performance in the

same subjects. They would likewise acquire knowledge relative to the factors

which affect their academic performance in Differential Calculus. With the

acquisition on these concerns, they would be able to develop more favorable

attitudes towards the same subjects, and develop ways by which some factors

affecting their performance will be offset.

Teachers . The teachers would indirectly benefit from the results of this

study in terms of having baseline information regarding their students attitude

towards Differential Calculus, their performance in same subjects and the factors

which influence their performance in Differential Calculus. With such baseline

information, they would be able to develop instructional materials appropriate to

their students level of academic performance and attitude towards Differential

Calculus. They would also be able to devise teaching methods which are

applicable to their students level of academic performance and attitude towards

Differential Calculus.

Education Stakeholders . The stakeholders would benefit from this study

in terms of gaining inspiration to lobby for policies to re-assess the syllabi on

Differential Calculus especially as regard their contents, instructional materials


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and teaching strategies used. After such re-assessment, they would be able to

lobby for support to revise the syllabi on said subjects.

Future Researchers . The future researchers would able to get ample

literature to validate the results of this study involving other respondents in

other colleges.

Scope and Delimitation

Using a descriptive research design with correlation analyses, this study

determined the factors affecting performance in differential calculus of students

in the College of Education and College of Engineering. Moreover, this study

determined the relationship between the student- respondents attitude in

Differential Calculus and their academic performance in the same subjects.

Likewise, this study determined the relationship between the factors that affect

the student- respondents performance in Differential Calculus and their

performance in the same subjects.

Meantime, a questionnaire and documents in terms of the student-

respondents final grades in Differential Calculus was used as data gathering

instruments. This study involved education students and engineering students of

Samar State University, Catbalogan City, who took up Differential Calculus

during the school year 2012-2013.Descriptive as well as inferential statistical tools

such as frequency count, percentage, mean, weighted mean, standard deviation,


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Pears on r and Fishers t -test were used to compute, analyze and interpret the

data.

Finally, this study was conducted during the school year 2013-2014.

Definition of Terms

To have a better understanding of this study, the terms herein used will be

defined conceptually and operationally.

Attitude . An organized predisposition to respond in a favorable or

unfavorable manner toward a specified class of objects (Breckler and Wiggins,

1992). In this study, the term will refer to the favorable or unfavorable

predisposition towards Differential and Integral Calculus measured by the

student- respondents responses in Part II of the questionnaire.

Differential Calculus . It is a subfield of calculus concerned with the study

of the rates at which quantities change; the object of this subject is the derivative

of a function, related notions such as the differential, and their applications

(en.wikipedia.org).It will be used in this study in the same manner as it is

defined in the foregoing statement.

Performance . It refers to how students deal with their studies and how

they cope with or accomplish different tasks given to them by their teachers

(http://wiki.answers.com) . In this study, this term will refer to the student-

respondents performance in Differential Calculus based on their final grades in

the said subjects.
http://wiki.answers.com/http://wiki.answers.com/


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Teaching Strategies . These comprise the principles and methods used for

instruction, including class participation, demonstration, recitation,

memorization, or combinations of these (Lieberman, 2004). In this study, the

term will be used operationally in the same context as it is defined conceptually,

except that it will refer specifically to the methods used for instruction in

Calculus which may have influence on their performance in the same subjects

based on the student-res pondents responses in Part III of the questionnaire.

Instructional Materials. It is used to help transfer information and skills

to others. These are used in teaching at places like schools, colleges and

universities. These can include textbooks, films, audio, and more.

Academic Performance. It refers to the status of the pupils with respect to

attained skills or knowledge as compared with other students or of school

adopted standard (Good, 1959). Final grade obtained by students in Differential

Calculus.


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Chapter 2

RELATED LITERATURE AND STUDIES

Related Literature

Schools are important agents for the education of individual members of

society. It is undeniable that a major role of schools is to prepare students for

their future careers. It is so insofar as the level of success students achieve in

college has far-rea ching implications for students personal and professional

lives. Student success has an immediate influence on academic self-esteem,

persistence in elected majors, and perseverance in tertiary education. More

importantly, success in college also ultimately impacts on career choice, personal

income and degree and nature of participation in community life.

Despite the importance of college education, it is the least enjoyed in a

students post -secondary academic career. Disaffection with and low

performance in college classes is a serious problem at colleges and universities

across countries around the world (Horn ,Peter, Rooney ,2002). Subsequently,

determinants of student performance have attracted the attention of academic

researchers from many areas. They have tried to determine which variables

impact student performance in positive and negative direction.

Hence, research studies have been conducted by various academicians in

various countries and areas (Cheung and Kan, 2002).The emphasis given to the


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identification and understanding of determinants of student success in school

stems from the fact that institutions and lecturers have to find out ways to

motivate students for better performance. In order to do this, firstthey need to

determine which factors play significant role in student performance.

Forexample, if attendance increases student performance, lecturers can do

somethingto increase students attendance rate such as integrating atten dance

rate into gradingpolicy. Secondly, graduating from different high schools may

also play a significantrole in performance(Alfan and Othman, 2005). For

example, graduates of private high schools that haveprior and stronger baseline

knowledge may outperform graduates of ordinary high schools.

One of the most commonly studied learning areas is mathematics because

the quality of teaching and learning said subject has been a major challenge and

concern of educators. Knowing the factors affecting math achievement is

particularly important for making the best instructional design decisions. This

overemphasis in mathematics stems from the inherent difficulty of mathematics.

Students have continuously struggled with mathematics courses which often

lead to an overall weak background in said subject and may contribute to

performance difficulties among students.

In a study presented at the 11 th National Convention on Statistics in 2010,

Ogena, Laa and Sasota (2010) disclosed the performance of Philippine Science

High Schools with Special Science Curriculum in the 2008 Trends in International

Mathematics and Science Study Advanced (TIMSS-Advanced). In said study,


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results of the TIMSS-Advanced showed that among the ten (10) countries that

participated in the study, Russian Federation, got the highest average scale score

at 561, while the Philippines ranked 10 thwith an average scale score of 355. This

study also presented average percent correct responses in the three content areas

of the advanced mathematics framework, namely, algebra, calculus, and

geometry, compared by SHS types in the Philippines and with other countries.

Meanwhile, Filipino students performed relatively better in geometry than

they did overall and relatively less well in calculus. This achievement pattern is

true and consistent across all types of secondary high schools (SHS). In the

cognitive domains, Philippines, in general, demonstrated relative strength in

knowing and relative weakness in applying. Weak performance in Applying is

consistent to all types of SHS. Strong performance, however, could be noted

among students both in Philippine Science High School (PSHS) and Regional

Science High School which did relatively better in Reasoning than they did

overall, whereas students from S&T Oriented HS and University Rural and

Laboratory HS did relatively better in Knowing than they did overall. Students

from Other Public SHS and Other Private HS did better not only in the Knowing

domain but also in the Reasoning domain.

Compared to other countries, performance of students from the

Philippines in general is relatively less well, be it in general or in specific content

area or domain. However, looking at the types of Philippine HS vis-a-vis other

participating countries, PSHS seems to be competitive internationally,


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demonstrating higher achievement rating in terms of average percent correct

responses than other countries, namely, Armenia, Iran, Italy, Norway, Slovenia,

and Sweden in overall advanced mathematics rating. PSHS had consistent

performance across content areas. In the cognitive domains, PSHS also seemingly

outperformed other countries particularly in the Applying and Reasoning

domains, in which its performance rating surpasses almost all countries except

Russian Federation and the Netherlands.

In general, very few students in the Philippines reached the international

benchmarks compared to other participating countries like Russian Federation

and Islamic Republic of Iran. Only 1 percent or 15 out of 4091 students reached

the advanced benchmark; 4 percent made it to high benchmark; and only 13%

got it at least to intermediate benchmark.

Among the types of HS, PSHS got the highest percent (6%) reaching the

advanced international benchmarks. More than half of the students (68%) from

PSHS made it at least at the intermediate benchmark. Interestingly, PSHS can

compete internationally having higher percentage (28%) of students reaching

high international benchmarks than 5 participating countries, namely, Armenia,

Italy, Norway, Slovenia, and Sweden. On the other hand, students from

University Rural HS & Laboratory Schools demonstrated weak performance

with only 2 percent reaching at least the intermediate benchmark. For Calculus

released items, the question with the lowest correct responses from the

Philippines is on Limits and Continuity with specific topic about


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Function/Where Not Differentiable, while the highest percent correct response

item is in Applying Derivatives to Graphs of Functions. Only 2.5% of Filipino

students got the correct answer in Limits and Continuity, with the performance

of students from S&T Oriented HS lower (1.5%) than this. The PSHS students got

a bit higher percent correct (9%) in same question. Nevertheless, PSHS

performance is still quite distant from that of Islamic Republic of Iran (36.7%) as

well as of Russian Federation (15.9%). In Applying Derivatives, the question was

correctly answered by a significant number (38.8%) of Filipino students in

general. Remarkably, PSHS had the highest percent correct (76.3%) surpassing

not only other SHS type but also all the other participating countries.

Filipino students are capable of performing better in mathematics if only

content in said subject is intensified and improved as shown in the

aforementioned results of the 2008 TIMSS-Advanced. It could also be that most

students today still believe that mathematics is all about computation. However,

computation, for mathematicians, is merely a tool for comprehending structures,

relationships and patterns of mathematical concepts, and therefore producing

solutions for complex real life problems (Libienski and Gutierrez, 2008). It has

become necessity for students to reach, analyze, and apply the mathematical

knowledge effectively and efficiently to be successful academically in school.

Hence, the quality of teaching and learning in mathematics is a major

challenge for educators. The current debate among scholars is what students

should learn to be successful in mathematics. The discussion emphasizes new


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instructional design techniques to produce individuals who can understand and

apply fundamental mathematics concepts. A central and persisting issue is how

to provide instructional environments, conditions, methods, and solutions that

achieve learning goals for students with different skill and ability levels (Dursun

and Dede, 2004). It is thus important for educators to adopt instructional design

techniques to attain higher achievement rates in mathematics (Rasmussen and

Marrongelle, 2006). Considering students needs and comprehension of

mathematical knowledge, instructional design provides a systematic process and

a framework for analytically planning, developing, and adapting mathematics

instruction (Saritas, 2004).

In an effort to understand the factors associated with mathematics

achievement, researchers have focused on many factors (Beaton and Dwyer,

2002). The impact of various demographic, social, economic and educational

factors on students mat h achievement continues to be of great interest to the

educators and researchers. For instance, Israel, et al. (2001) concluded that

parents socioeconomic status is correlated with a childs educational

achievement. Another study by Jensen and Seltzer (2000) showed that factors

such as individual study, parents role, and social environment had a significant

influence on further education decisions and achievements of young students.

A growing body of research provides additional factors which could have

an impact on students achievement . Of these factors, the students attitudes

toward the subject have been studied (Campbell, et al. 2000). Attitudes can be


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seen as more or less positive. A positive attitude towards mathematics reflects a

positive emotional disposition in relation to the subject and, in a similar way, a

negative attitude towards mathematics relates to a negative emotional

disposition (Zan and Martino, 2008). These emotional dispositions have an

impact on an individuals behavio r, as one is likely to achieve better in a subject

that one enjoys, has confidence in or finds useful (Eshun, 2004). For this reason,

positive attitudes towards mathematics are desirable since they may influence

ones willingness to learn and also the bene fits one can derive from mathematics

instruction.

Nicolaidou and Philippou(2006) showed that negative attitudes are the

result of frequent and repeated failures or problems when dealing with

mathematical tasks and these negative attitudes may become relatively

permanent. According to these authors, when children first go to school they

usually have positive attitudes towards mathematics. However, as they progress

their attitudes become less positive and frequently become negative at high

school. Likewise, K ce ,et. al. (2009) found significant differences between

younger and older students attitudes towards mathematics with 8th graders

having lower attitudes than 6th graders.There are a number of factors which can

explain why attitudes towards mathematics become more negative with the

school grade, such as the pressure to perform well, over demanding tasks,

uninteresting lessons and less than positive attitudes on the part of teachers.


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Moreover, students' opinions and beliefs regarding mathematics, how

much they like and value it, and what they forecast for their own future

education can all be understood as different facets of students' attitudes toward

mathematics(Aiken, 2002). The study of attitudes toward mathematics is justified

from at least three standpoints. First, the development of positive attitudes is a

goal for many educational systems; they are seen as a requisite for students'

academic engagement and to boost learning. Second, attitudes are learned

predispositions that reflect the school ethos and the wider social context in which

mathematics instruction occurs. As such, attitudes can be influenced by policy

interventions. Third, the literature has suggested that there is a positive

relationship between attitudes toward mathematics and academic competence.

The study of attitudes in the school setting has several complications.

Because of the different facets of the attitude construct, what is meant by

attitudes toward mathematics varies from one study to the other. Moreover, it is

common to find studies that do not use the term attitudes, but whose focus lay in

one or more of its facets such as academic self-perception and locus of control.

Relationships that may hold true at the student level may not be of the same

nature and strength at the school or classroom level.

For instance, from the 1995 Trends in International Mathematics and

Science Study (TIMSS) there is evidence that the majority of 8 th graders around

the world liked mathematics, thought it was important for them to do well in this

subject, thought it was not boring, and did not find it easy (Kifer, 2002). In school


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effectiveness studies, expectations for further education had been reported as a

strong predictor of school mean achievement across the countries (Martin,

Mullis, Gregory, Hoyle, and Shen, 2000).

The question then is whether students attitude will also have the same

impact in their academic performance in Calculus. The said subject provides the

foundation for understanding higher-level science, mathematics, and

engineering courses (Gainenand Willemsen, 2005). Further, ,Sorby and Hamlin

(2001) have pointed out that calculus is the starting point in mathematics

instruction for many academic programs. Success in calculus is therefore

imperative for students in that it provides the mathematical background and

foundation.

An abundance of research has been performed to identify predictors of

student performance in Calculus. Both cognitive and non-cognitive factors have

been considered, because numerous studies have shown both types of variables

to be useful predictors. Some studies have shown that non-cognitive variables

are more useful than cognitive variables in predicting the academic success of

non-traditional students (Sedlacek, 2002). The students attitu des are included in

the category of non-cognitive variables.

Hence, this study which aims to determine the relationship between the

students attitude towards calculus and their academic performance in the same

subject.


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Related Studies

The following are discussions of researches reviewed to provide insights

to this study.

In a study of Reinholz (2009) entitled An Analysis of Factors Affecting

Student Success in Math 160 (Calculus) for Physical Scientists I, Assessment and

Learning in Knowledge Spaces (ALEKS) Preparation for Calculus and Exam 1

scores were significant predictors of Final Exam scores. It also found out that

although the ALEKS initial assessment does have some predictive value, Exam1

scores are much more useful in predicting a stud ents outcome in the course.

The said study concluded that despite instructor impressions that the

inclusion of ALEKS reduced the number of mechanical pre-calculus questions

asked in class, the inclusion of ALEKS as required component of MATH 160

failed to elicit any improvement in student success. ACT Math scores were not a

significant predictor of success. A students ACT Math scores are largely

indicative of the students mechanical pre-calculus skills. The inclusion of ALEKS

did not improve success in MATH 160 and mechanical pre-calculus skills are not

as important to success in MATH160.

The similarity is on the subject under study that is, the previous study

dealt with Calculus in much the same way that the present study will also deal

with the same subject. They differ, however, in terms of other variates used and

methodologies employed.


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Depaolo (2005) conducted a study entitled The Relationship between

Attitudes and Performance in Business Calculus. This study examined

undergraduate business students' attitudes toward and performance in both

business statistics and calculus, and determines that after controlling for ability,

attitudes play a significant role in performance. Although self-reported attitudes

become more positive over the course of the semester, attitudes toward calculus

are less positive than those toward statistics, and negative attitudes are related to

lower exam scores. For students with no prior calculus background, this

relationship between negative attitudes and poor exam performance appears to

be particularly strong.

In the study of Bulan (2005) entitled Correlates of Study Habits of Grades

VI Pupils inputs to Enhancement Strategies, study habits of the pupils were

correlated to their parents attitude towards education: attitude towards

schooling, reading ability and teachers attitude towards teaching, performance

rating and their strategies to develop pupils study habits.

It is similar to the recent study conducted since both focused on the study

habits of the learners and included attitude towards schooling. It differs in a lot

of ways. In the previous study the main study are the Grade VI pupils while the

recent study focused on the college student. In the recent study, attitude and

study habits are variants to be considered and also to be correlated, unlike the

previous study that the study habits is only the major variates while the attitude


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is only the one of the correlates. In the scope and the delimitation of the previous

study three variables were considered pupils, parents and teachers, the present

study was centered on students mathematics attitudes, their study habits, which

might affect their success in the study of calculus.


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Chapter 3

METHODOLOGY

Research Design

This study utilized descriptive correlational research design with

correlation analysis in determining the factors affecting performance in

differential calculus of students in the College of Education, and College of

Engineering, Samar State University, Catbalogan City, during the school year

2012-2013

The descriptive research correlation design was used in describing the

personal profile of the student-respondents in terms of their sex, course, and

academic performance in Differential Calculus based on the result of the

achievement test, and factors affecting performance in Differential Calculus ofthe student-respondents as regard the following: attitudes, instructional

materials, and teaching methods.

Correlation analyses was conducted in order to determine the

relationship between: (1) the student- respondents perception of the factors

affecting performance in Differential Calculus and each of their profile varieties:

sex, course, and academic performance in Differential Calculus and factors

affecting performance in Differential Calculus of the student-respondents as

regard the following: attitudes, instructional materials, and teaching methods.


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Instrumentation

A questionnaire was used in order to gather the needed data of this study.

Questionnaire. The questionnaire served as the sole data gathering instrument.

This consisted of four major parts.

The first part supplied type wherein which the student-respondents was

required to fill in the needed information on the blank spaces provided and/or to

check the appropriate boxes of their responses. This part contains items on their

personal profile as to sex, course, and academic performance in differential

calculus.

The second part of the questionnaire is an attitude checklist reflecting the

student- respondents attitude toward Differential Calculus. Th is contains 10

statements with the following five-point scale to quantify the student-

respondents responses: (5) Strongly Agree; (4) Agree; (3) Undecided

(Neutral); (2) Disagree; and (1) Strongly disagree.

The third part of the questionnaire is a checklist reflecting the instructional

materials and teaching methods used in Differential Calculus. The responses of

the student-respondents were quantified using the following five-point scale: (5)

Extremely Influential; (4) Very Influential: (3) Moderately Influential; (2)

Slightly Influential; (1) Not Influential.


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Achievement Test.

The Achievement in Differential Calculus consisted of 15 multiple choice

items downloaded from the ACT multiple items in Differential Calculus. It has 5

options from which the respondents choose the best answer from the lettered

choices. The Achievement Test is a pre-validated items but it will undergo

another validation to determine its validity with the kinds of respondents.

Validation of Instrument

Since the questionnaire is researcher-made, this was validated through

expert validation for content validity. A draft of the questionnaire was submitted

for revision and/or modification to Math Teachers, and Research Adviser. After

their suggestions have been incorporated, the questionnaire was finalized and

prepared for pilot testing.

Sampling Procedure

The respondents of this study are the students who have finished

Differential Calculus from the two colleges of Samar State University-Main

Campus, namely, College of Education, College of Engineering. In determining

the respondents of this study, the researchers used random sampling techniqueusing the college affiliation as the stratum. We have drawn 20 respondents from

college of engineering and 30 respondents from college of education.


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Data Gathering Procedure

A letter requesting permission to conduct the study of Samar State

University-Main Campus was secured from the Dean of the College of

Education. Said letter, upon approval, will be attached to the letters requesting

permission from the deans of the different colleges in the same university. Upon

their approval, the survey was conducted using the questionnaire of this study.

After all the data shall have been collected, the tabulation, computation,

analyses and interpretation of data will proceed.

Statistical Treatment of Data

The data that will be gathered from the respondents was carefully tallied,

analyzed, and interpreted qualitative and quantitatively using both descriptive

as well as inferential statistical tools. The descriptive statistical tools which were

used include frequency count, percentage, mean, and weighted mean. The

inferential statistical tools like the Pearson Product Moment Coefficient of

Correlation (Pearson r), and Fishers t-test for independent sample will be used.

Frequency count. This statistical tool was resorted to determine the

number of respondents, who are of the same sex, course, academic performance,and attitude towards Differential Calculus.

Percentage. This descriptive statistical tool was used to present the data on

sex, course, and academic performance in Differential Calculus and factors


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affecting performance in Differential Calculus of the student-respondents as

regard the following: attitudes, instructional materials, and teaching methods.

Mean. This statistical measure was used to determine the quantitative

characteristics or profile of the respondents.

Weighted Mean (WM ). This was used to express the collective

perceptions of the respondents.

In interpreting the foregoing data, the following scale will be used.

4.51-5.00-Strongly Agree (SA)/Extremely Influential (EI)/Always Practiced (AP)

3.51-4.50- Agree (A)/ Very Influential (VI)/Often Practiced (OP)

2.51-3.50-Undecided (U)/ Moderately Influential (MI)/ Sometimes practiced (SP)

1.51-2.50 - Disagree (D)/Slightly Influential (SI)/ Rarely Practiced (RP)

1.00-1.50 Strongly Disagree (SD)/ Not Influential (NI)/ Never Practice (NP)

Pearson Product Moment Coefficient of Correlation . This statistical tool

was used to determine the relationships between dependent and independent

variables.

The degree of relationship will be determined by the size of the obtained r.

Interpretations of the obtained r will be as follows:

r from + .01 to + .19: negligible correlation


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r from + .20 to + .39: low correlation

r from + .40 to + .59: moderate correlation

r from +.60 to + .79: moderately higher correlation

r from + .80 to +.1.0: high correlation

Fishers t -test . To reject or accept the hypothesis that there is no significant

relationship of the computed coefficient of correlation of each of the variables,

the Fishers t -test was used. The hypothesis was accepted and/or rejected at 0.05level of significance, two-tailed.


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CHAPTER 4

PRESENTATION, ANALYSIS AND INTERPRETATION OF DATA

Profile of Student- Respondents

The profile variates of student- respondents such as sex, grade and course

are discussed here.

Sex. Table 1 provides the sex distribution of the student-respondents.

Table 1

Sex distributions of student- respondents

Sex Frequency PercentageMale 26 52

Female 24 48Total 50 100

There are 26 or 52 % male respondents and 24 or 48% female respondents.

Course . Table 2 shows the distributions of student-respondents according

to course.

Table 2Distribution of student-respondents according to course

Course Frequency PercentageCOED 30 60

COENG 20 40Total 50 100

There are 30 or 60% COED respondents and 20 or 40% COEng respondents.


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Academic Performance in Differential Calculus. Table 3 shows the

distributions f student-respondents according their grades in differential

calculus.

Table 3

Distribution of student-respondents according to academic performance inDifferential Calculus

GRADE INTERPRETATION FREQUENCY PERCENTAGE1.0 Excellent 0 0

1.1 1.5 Superior 0 01.6 -2.0 Very Good 7 142.1- 2.5 Good 26 522.6 3.0 Fair / Passing 17 34

5.0 Failure 0 0TOTAL 50 100MEAN 2.4

SD 0.05

As reflected in the table, 7 or 14% of the student-respondents have very

good performance in Differential Calculus with grades between 1.6 - 2.0. About

26 or 52% have good performance with grades between 2.1-2.5 and 17 or 34%

have fair performance with grades between 2.6 - 3.0.

The mean grade is 2.4 interpreted as good performance with a standard

deviation of 0.05.

Performance in Achievement Test. Table 4 shows the distribution of

students-respondents performance in the Achievement Test.


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Table 4

Distribution of student-respondents performance in the Achievement Test

Scores College of Education College of Engineering

13-15 6 12

10-12 19 87-9 5 04-6 0 01-3 0 0

Total 30 20Mean 11.1 12.8

SD 1.84 1.51Legend: 13-15Outstanding; 4-6 Fair;

10-12 Very Good; 1-3 Poor

7-9 Good;

As reflected in the table there 19 student-respondents have very good

performance from the College of Education and 12 student-respondents have

outstanding performance from the College of Engineering in Achievement Test.

The mean score is 11.1 and standard deviation of 1.84 for the College of

Education and for the College of Engineering the mean score is 12.8 and standard

deviation of 1.51.

Attitude towards Differential Calculus. Table 5 shows the distribution of

student-respondents according to their attitudes towards Differential Calculus.


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Table 5Distribution of student-respondents according to their attitudes towards

Differential Calculus

STATEMENTCOED COENG

WM INTERPRE-TATION WMINTERPRE-

TATION1. I find the Differential Calculus an interestingsubject. 3.93 HFA 3.95 HFA

2. I wish I could take more Differential Calculussubjects other than those offered in my course. 3.23 MFA 3.15 MFA

3. Differential Calculus makes me feel relaxed,happy and comfortable. 2.83 MFA 3.00 MFA

4. I like that my Differential Calculus teachergives me several examples before givingindividual exercises, seatwork and board work.

3.73 HFA 3.85 HFA

5. I give special attention to the accuracy of myanswer to Differential Calculus problem-solvingexercises.

3.93 HFA 3.85 HFA

6. When I have doubt about the correct answerto Differential Calculus exercises, I refer to myDifferential Calculus books for references.

3.67 HFA 3.80 HFA

7. I search internet for new ideas, concepts andinnovations related to Differential Calculus. 3.13 MFA 2.5 LFA

8.I like to recite and participate in class activitiesin my Differential Calculus class. 3.33 MFA 3.35 MFA

9. I believe that Differential Calculus is neededin daily life. 3.27 MFA 2.85 MFA

10. I love Differential Calculus as it gives mesuperiority. 3.37 MFA 3.25 MFA

GRAND MEAN 3.44 MFA 3.36 MFA

Legend: 4.51 5.00 VHFA (Very High Favorable Attitude)

3.51 4.50 HFA (High Favorable Attitude)

2.51 3.50 MFA (Moderately Favorable Attitude)1.51 - 2.50 LFA (Low Favorable Attitude)

1.00 - 1.50 UA (Unfavorable Attitude)

Four of the statements obtained weighted mean ratings between 3.51-4.50

interpreted as highly favorable attitude from and six statements obtained


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weighted mean ratings between 2.51- 3.50 interpreted as moderately favorable

attitude from the College of Education with grand mean of 3.44 interpreted as

moderately favorable attitude and four of the statements obtained weighted

mean ratings between 3.51-4.50 interpreted as highly favorable attitude from and

five statements obtained weighted mean ratings between 2.51- 3.50 interpreted as

moderately favorable attitude and one statement obtained weighted mean 2.5

interpreted as low favorable attitude, from the College of Engineering with

grand mean of 3.36 interpreted as moderately favorable attitude.

Instructional Materials. Table 6 shows the extent of influence of the

instructional materials used in the College of Education and College of

Engineering.


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Table 6

Extent of Influence of the Instructional Materials on studentsperformance in Differential Calculus

InstructionalMaterials Used

COED COENGWeighted

Mean InterpretationWeighted

MeanInterpretation

1.Power PointPresentation 3.9 VI 2.9 MI

2. OHP and Acetate 2.7 MI 1.9 SI3. Xerox Copy(Handouts) 4.3 VI 4.2 VI

4. Cartolina and ManilaPaper 3.03 MI 2.15 SI

5. Whiteboard andMarker 4.3 VI 4.05 VI6.Blackboard and Chalk 3.8 VI 4.5 VI7.Books 4.6 EI 4.4 VI8.News Paper, Journals,Periodicals 2.8 MI 2.2 SI

9.Internet-Based 3.4 MI 3.8 VI

10.Web Site 3.3 MI 3.85 VI

Grand Mean 3.61 VI 3.395 MI

Legend: 4.51 5.00 Extremely Influential

3.51 4.50 Very Influential

2.51 3.50 Moderately Influential

1.51 - 2.50 Slightly Influential

1.00 - 1.50 Not Influential

From College of Education one of the instructional materials obtained

weighted mean 4.60 interpreted as extremely influential. This is IMs no. 7

(books) . Having a grand mean 3.61 interpreted as very influential. From the

College of Engineering six of the instructional materials obtained weighted mean

ratings between 3.51 4.50, interpreted as very influential. These are IMs

3(Xerox copy) at a value of 4.2, IMs 5(whiteboard & marker) at a value of 4.05,


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IMs 6 (Blackboard & chalk) at a value 4.5, IMs7(books) at a value 4.4, IMs

9(internet- based) at a value of 3.8 and IMs 10( web site) at value 3.85.

The grand mean is 3.395 interpreted as moderately influential.

Teaching Strategies. Table 7 shows the extent of influence of the teaching

strategies.

Table 7

Extent of Influence of Teaching Strategies on students performance inDifferential Calculus

Teaching StrategiesCOED COENG

WeightedMean Interpretation

WeightedMean Interpretation

1.Reporting 3.87 VI 2.15 SI2. Lecture AndDiscussion 4.37 VI 4.65 VI

3. Board Work andSeat Work 4.47 VI 4.30 VI

4. Problem Solving 4.37 VI 4.25 VI5. Recitation 4.17 VI 3.60 VI6.Problem Set 4.33 VI 4.05 VI7.Demonstration 4.23 VI 4.15 VI8.Inquiry Approach 3.77 VI 3.40 VI

9.Group Work 4.03 VI 3.20 MI

10. Project Method 3.03 MI 3.05 MI

Grand Mean 4.06 VI 3.68 VI

Legend: 4.51 5.00 Extremely Influential3.51 4.50 Very Influential2.51 3.50 Moderately Influential1.51 - 2.50 Slightly Influential1.00 - 1.50 Not Influential


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From the College of Education nine of the strategies obtained weighted

mean rating between 3.51-4.50 interpreted as very influential and one of the

strategies obtained weighted mean rating between 2.51-3.50 interpreted as

moderately influential this is method 10(project method) at a value 3.03. The

grand mean is 4.06 interpreted as very influential. From the College of

Engineering seven of the strategies obtained weighted mean rating between 3.51

4.50 interpreted as very influential and two of the strategies obtained weighted

mean rating between 2.51-3.50 interpreted as moderately influential. The grand

mean is 3.68 interpreted as very influential.

Relationship between student-respondentsacademic performance and the FactorsAffecting Students Performance

Table 8 shows the relationship between student-respondents academic

performance in Differential Calculus and the Factors Affecting Students

performance.

Table 8

Relationship between student-respondents academic performance and thefactors affecting s tudents performance

rxy Fishers t -test Evaluation Decision

Attitude 0.07226 0.5194 NS Accept H o

InstructionalMaterials 0.2279 1.62161 NS Accept H o

TeachingStrategies 0.0859 0.5951 NS Accept H o

Level of significance = 0.05; df = 48; CV= 2.0106 S-Significant; NS-Not Significant


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Attitude. As reflected in table 8, the computed r = -0.07226 and the

computed Fishers t -value was 0.5194 which t-value was lesser than the critical

value of 2.0106 with level of significance set at .05 (two tailed) and df=48. This

meant that the attitude is not significantly related to students academic

performance.

Instructional Materials. As to instructional materials, the same table

shows the computed r = 0.2279 and the computed Fishers t -value was 1.62161

which t-value was lesser than the critical value of 2.0106 with level of

significance set at .05 (two tailed). This meant that the instructional materials are

not significantly related to students academic performance.

Teaching Strategies. Relative to teaching strategies, the table shows that r

= 0.0859 was obtained with a computed t-value of 0.5951 which was lesser than

the critical t-value of 2.0106, with level of significance set at .05 (two tailed) and

df=48. This led to the acceptance of the null hypothesis which states there is no

significant relationship between student-respondents academic performance and

the Factors Affecting Students Performance.

Relationship between student-respondentsperformance in the achievement test

and the Factors Affecting Students Performance

Table 9 shows the Relationship between student-respondents performancein the achievement test and the Factors Affecting Students Performance .


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Table 9

Relationship between student-respondents performance in the achievementtest and the Factors Aff ecting Students Performance

rxy Fishers t -test Evaluation Decision

Attitude 0.134084 .93743 NS Accept H o

InstructionalMaterials 0.37580 0.2605 NS Accept H o

TeachingStrategies 0.24509 1.7515 NS Accept H o

Level of significance = 0.05; df = 48;CV= 2.0106 S-Significant; NS- Not Significant

Attitude. As reflected in table 9, the computed r = 0.134084 and the

computed Fishers t-value was .93743which t-value was lesser than the critical

value of 2.0106 with level of significance set at .05 (two tailed) and df=48. This

means that the attitude is not significantly related to students performance in the

achievement test.

Instructional Materials. As to instructional materials, the same table

shows the computed r = 0.37580 and the computed Fishers t -value was which t-

value 0.2605 was lesser than the critical value of 2.0106 with level of significance

set at .05 (two tailed). This meant that the instructional materials are not

significantly related to students performance in the achievement test.

Teaching Strategies Relative to strategies, the table shows that r = 0.24509

was obtained with a computed t-value of 1.7515 which was lesser than the critical

t-value of 2.0106, with level of significance set at .05 (two tailed) and df= 48. This

led to the acceptance of the n ull hypothesis which states there is no significant


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relationship between student-respondents performance in the achievement test

and the Factors Affecting Students Performance.

Relationship between student-respondentsattitude towards DifferentialCalculus and Course

Table 10 shows the Relationship between student-respondents attitudetowards Differential Calculus and Course

Table 10

Relationship between student-respondents attitude towards DifferentialCalculus and Course

rxy Fishers

t-test Evaluation Decision

CoEd & CoEng 0.868201 0.308927 NS Accept H o Level of significance = 0.05; df = 48; CV= 2.0106 S-Significant; NS- Not Significant

Student-respondents performance in the achievement test and

Courses obtained the Pearson r, rxy = 0.868201and t-value = 0.308927. So, the null

hypothesis ther e is no significant difference between student-respondents

attitude towards Differential Calculus and Courses is rejected.


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Chapter 5

SUMMARY OF FINDINGS, CONCLUSIONS AND RECOMMENDATIONS

Summary of Findings

The following are the salient findings of the study:

1. There are 26 or 52 % male respondents and 24 or 48% female respondents.

2. There are 30 or 60% COED respondents and 20 or 40% COEng

respondents.

3.

There are 7 or 14% of the student-respondents have very goodperformance in Differential Calculus with grades between 1.6 - 2.0. About

26 or 52% have good performance with grades between 2.1-2.5 and 17 or

34% have fair performance with grades between 2.6-3.0.The mean grade is

2.4 interpreted as good performance with a standard deviation of 0.05.

4. There are 19 student-respondents having very good performance from the

College of Education and 12 student-respondents have outstanding

performance from the College of Engineering in Achievement Test. Themean score is 11.1 and standard deviation of 1.84 for the College of

Education and for the College of Engineering the mean score is 12.8 and

standard deviation of 1.51.

5. There are 15 male student-respondents having outstanding performance

and 12 student-respondents have very good performance in the

Achievement Test. The mean score is 12.73 and standard deviation of 1.51

for the male respondents and the mean score is 12.8 and standard

deviation of 2.17.

6. Four of the statements obtained weighted mean ratings between 3.51-4.50

interpreted as highly favorable attitude from and six statements obtained


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weighted mean ratings between 2.51- 3.50 interpreted as moderately

favorable attitude from the College of Education with grand mean of 3.44

interpreted as moderately favorable attitude and four of the statements

obtained weighted mean ratings between 3.51-4.50 interpreted as highly

favorable attitude from and five statements obtained weighted mean

ratings between 2.51- 3.50 interpreted as moderately favorable attitude

and one statement obtained weighted mean 2.5 interpreted as low

favorable attitude, from the College of Engineering with grand mean of

3.36 interpreted as moderately favorable attitude.

7. From College of Education one of the instructional materials obtained

weighted mean 4.60 interpreted as extremely influential. This is IMs no. 7

(books) . Having a grand mean 3.61 interpreted as very influential.

8. From the College of Engineering six of the instructional materials obtained

weighted mean ratings between 3.51 4.50,interpreted as very influential.

These are IMs 3(Xerox copy) at a value of 4.2, IMs 5(whiteboard &

marker) at a value of 4.05, IMs 6 (Blackboard & chalk) at a value 4.5, IMs 7

(books) at a value 4.4, IMs 9(internet -based) at a value of 3.8 and IMs

10(web site) at value 3.85. The grand mean is 3.395 interpreted as

moderately influential.

9. From the College of Education nine of the strategies obtained weighted

mean rating between 3.51-4.50 interpreted as very influential and one of

the strategies obtained weighted mean rating between 2.51-3.50


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interpreted as moderately influential this is method 10(project method) at

a value 3.03. The grand mean is 4.06 interpreted as very influential.

10. From the College of Engineering seven of the strategies obtained weighted

mean rating between 3.51 4.50 interpreted as very influential and two of

the strategies obtained weighted mean rating between 2.51-3.50

interpreted as moderately influential. The grand mean is 3.68 interpreted

as very influential.

11. As reflected in table 8, the computed r = -0.07226 and the computed

Fishers t-value was 0.5194 which t-value was lesser than the critical value

of 2.0106 with level of significance set at .05 (two tailed) and df=48. This

meant that the attitude is not signific antly related to students academic

performance.

12. As to instructional materials, the same table shows the computed r =

0.2279 and the computed Fishers t -value was 1.62161 which t-value was

lesser than the critical value of 2.0106 with level of significance set at .05

(two tailed). This meant that the instructional materials are not

significantly related to students academic performance.

13. Relative to teaching strategies, the table shows that r = 0.0859 was

obtained with a computed t-value of 0.5951 which was lesser than the

critical t-value of 2.0106, with level of significance set at .05 (two tailed)

and df=48. This led to the acceptance of the null hypothesis which states


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there is no significant relationship between student -respondents

academic performa nce and the Factors Affecting Students Performance.

14. As reflected in table 9, the computed r = 0.134084 and the computed

Fishers t-value was .93743which t-value was lesser than the critical value

of 2.0106 with level of significance set at .05 (two tailed) and df=48. This

means that the attitude is not significantly related to students

performance in the achievement test.

15. As to instructional materials, the same table shows the computed r =

0.37580 and the computed Fishers t -value was which t-value 0.2605 was

lesser than the critical value of 2.0106 with level of significance set at .05

(two tailed). This meant that the instructional materials are not

significantly related to students performance in the achievement test.

16. Relative to strategies, the table shows that r = 0.24509 was obtained with a

computed t-value of 1.7515 which was lesser than the critical t-value of

2.0106, with level of significance set at .05 (two tailed) and df= 48. This

led to the acceptance of the null hypothesis which states the re is no

significant relationship between student-respondents performance in the

achie vement test and the Factors Affecting Students Performance.

17. Student-respondents performance in the achievement test and Courses

obtained the Pearson r, rxy = 0.868201and t-value = 0.308927. So, the null

hypothesis there is no significant relationship between student -


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respondents attitude towards Differential Calculus and Courses is

rejected.

Conclusion

The following conclusions were drawn based on the findings of the study:

1. There is no significant relationship between student-respondents

academic performance and the factors affecting students performance .

2. There is no significant relationship between student-respondents

performance in the achievement test and factors affecting students

performance.

3. There is no significant relationship between student-respondents attitude

towards Differential Calculus and Courses.

4. Power Point Presentation, OHP and Acetate, News Paper, Journals,

Periodicals are not effective instructional materials in the College of

Engineering.

5. OHP and Acetate, News Paper, Journals, Periodicals are not influential; in

the College of Education.

6. Most of the teaching strategies are influential in the College of Education.

7. Students attitude towa rds Differential Calculus is classified as moderately

favorable as reflected in the grand mean.

8. There 19 student-respondents have very good performance from the

College of Education and 12 student-respondents have outstanding

performance from the College of Engineering in Achievement Test.


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9. There 7 or 14% of the student-respondents have very good performance in

Differential Calculus with grades between 1.6 - 2.0. About 26 or 52% have

good performance with grades between 2.1-2.5 and 17 or 34% have fair

performance with grades between 2.6 - 3.0.

Recommendations

As resulted from the study it is recommended to teachers and students to:

1. Develop highly favorable attitude towards Differential Calculus.

2. Implement the most effective teaching strategies that can help the students

to easily understand the subject.

3. Use instructional materials that are fitted to the subject matter and needs

of the students.


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Depaolo. The Relationship between Attitudes and Performance in Business

Calculus

Saritas, Tuncay and OmurAkdemir. Ident ifying Factors Affecting

theMathematics Achievements of Students for Better Instructional

Design Unpublished technical reort, Turkey, 2004.

Sorby, S.A., & Hamlin, A.J. 2001, August). The implementation of first-


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yearengineering program and its impact on calculus performance. Paper

presented at the meeting of International Conference on

Engineering Education, Oslo,Norway.

Marcroff, Gene, I. (1985). Class size is key to campus Success . New York Times.

February 26th, 17 18.

Luitel, B. C. (2002). Developing and probing understanding in mathematics . [On-line

serial] Available at http://au.geocities.com/bcluitel/vijaya


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APPENDICES


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Appendix A

Samar State University

COLLEGE OF EDUCATIONCatbalogan, Samar

COVER LETTER FOR THE QUESTIONNAIRE

Date: _____________

Dear Respondents,

We, the undersigned fourth year Bachelor of Secondary Education

students major in mathematics undertaking a research entitled FACTORSAFFECTING STUDENTSPERFORMANCE IN DIFFERENTIAL CALCULUS.

In this connection we have chosen you to be our respondents. Yourcooperation to answer the attached questionnaire is highly solicited.

This survey questionnaire is designed only for this study. Please do notleave any question unanswered. All the details and results will be treatedconfidentially.

Please feel free in answering the questionnaire. Thank you!

Truly yours,

ANITO B. FABILLORENGERLIE L. GOSOSOIAN FRANCIS G.OJEDA

JUNA T. TEJONESLEMUEL C. MONTALLANA


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Appendix B

SURVEY QUESTIONNAIRE

Direction: This questionnaire contains five major parts. Please read each

item of the questionnaire and answer as truthfully as possible. Do not

leave an item unanswered.

Part I. STUDENT RESPONDENTS PROFILE

Direction: This section contains items that relate to your personalbackground. Supply the needed information by filling in the appropriate

blank spaces and putting a check mark on the space provided before each

item.

Name

(Optional):____________________________________________________

Sex: ( ) Male ( ) Female Course: ___________ Grade in D.C:__________

Part II- STUDENTS ATTITUDE TOWARDS DIFFERENTIAL CALCULUS

Directions: Beside each statements presented below, please indicate whether

you strongly agree (SA) or very high favorable attitude (VHFA) agree (A) or

have highly favorable attitude (HFA), neutral (N) or have moderately favorable

attitude (MFA), disagree (D) or have less favorable attitude (LFA), or strongly

disagree (SD) or have unfavorable attitude (UA) towards Differential Calculus.


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Attitude Statements

Responses

SA/ A/ N/ D/ SD/

VHFA HFA MFA LFA UA

(5) (4) (3) (2) (1)1. I find the Differential Calculus aninteresting subject.

2. I wish I could take more DifferentialCalculus subjects other than thoseoffered in my course.

3. Differential Calculus makes me feelrelaxed, happy and comfortable.

4. I like that my Differential Calculusteacher gives me several examplesbefore giving individual exercises,seatwork and board work.

5. I give special attention to theaccuracy of my answer to DifferentialCalculus problem-solving exercises.

6. When I have doubt about the correctanswer to Differential Calculusexercises, I refer to my DifferentialCalculus books for references.

7. I search internet for new ideas,concepts and innovations related toDifferential Calculus.

8.I like to recite and participate in classactivities in my Differential Calculusclass.

9. I believe that Differential Calculus isneeded in daily life.10. I love Differential Calculus as itgives me superiority.


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Part III- TEACHING METHODS

Directions: Beside each of the statements presented below, please indicate

whether you are (5) Extreme Influential (EI); (4) Very Influential (VI); (3)

Moderately Influential (MI); (2) Slightly Influential (SI); and 1 Not Influential

(NI)

A. Instructional Materials Used in Differential Calculus

Instructional Materials Used

Responses

EI VI MI SI NI

5 4 3 2 1

1.Power Point Presentation

2. OHP and Acetate

3. Xerox Copy (Handouts)4. Cartolina and Manila Paper

5. Whiteboard and Marker

6.Blackboard and Chalk

7.Books

8.News Paper, Journals, and

Periodicals9.Internet-Based

10.Web Site


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B. Teaching Strategies Used in Teaching by the teachers

Teaching Strategies

Responses

EI VI MI SI NI

5 4 3 2 1

1.Reporting

2. Lecture And Discussion

3. Board Work and Seat Work

4. Problem Solving

5. Recitation

6.Problem Set

7.Demonstration

8.Inquiry Approach

9.Group Work

10.Project Method


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APPENDIX C

ACHIEVEMENT TEST IN CALCULUS

Directions: Solve each problem and encircle the letter of the correct answer.

1. If y = (x3 + 1)2 , then

a.( 3x2)2 b. 2 ( x3 + 1) c. ( 6x2) ( x3 + 1)

d. 2 ( 3x3 + 1) e. ( 3x3 ) ( x3 + 1)

2. If y = , then

a. ( ) b. . ( ) c. ( )

d. ( ) e.( )

3. Find the first derivative of y=

a. b. c.

d. e.

4. The graph of a function f is concave when f (x) is:

a. f (x) 0 b .f (x) c .f (x)

d. f (x) = 0 e. f (x)


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5. Evaluate the =

a. 0 b. 1 c. 8

d. 16 e. not existent

6. The critical number/s of the function y = 3x is / are:

a. 2, -2 b. 2, 0 c. -2, 0

d. 3, 2 e. 3, -2

7.

a. b. c.

d. e. 1

8. Find the second derivative of y = (2x -3) (3x - 2)

a. 11 b. 12 c. 13

d. 14 e. 15

9. Find two nonnegative numbers so that their sum is 100 and the sum of their

squares is maximum.

a. 30 & 70 b. 50 & 50 c. 60 & 40

d. 20 & e. 75 & 25


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10. A function is increasing on interval ( a , b ) if :

a. f ( x ) 0 for every x in ( a , b)

b. f ( x ) 0 for every x in ( a , b)

c. f ( x ) 0 for every x in ( a , b)

d. f ( x ) 0 for every x in ( a , b)

e. f ( x ) 0 for every x in ( a , b)

11. What is the derivative with respect to xof ( x + 1) 3 - x3?

a. 3x + 6 b. 3x 3 c. 6x 3

d. 6x + 3 e. -3x 6

12. Find the derivative of( )

a.( )

-( )

b.( )

-( )

c.( )

-( )

d.( )

-( )

e.( )

-( )

13. Find the slope of x 2y=8 at the point (2, 2).

a. 2 b. -1 c. -

d. -2 e. 1

14. The sum of two positive numbers is 50. What are the numbers if their product

is to be the largest possible.


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a. 24 & 26 b. 28 & 22 c. 25 & 25

d. 20 & 30 e. 29 & 21

15. A farmer has enough money to build only 100 meters of fence. What are the

dimensions of the field he can enclose the maximum area?

a. 25 m x 25 m b. 15 m x 35 m c. 20 m x 30 m

d. 22.5 m x27.5 m e. 15 m x 25 m


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CURRICULUM VITAE


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CURRICULUM VITAE

Personal Information

Name : Gerlie L. Gososo

Address : Brgy. Astorga, Daram Samar

Age : 20

Sex : Female

Civil Status : Single

Course : BSED MATH

Educational Background

Elementary : Brgy. Astorga Elementary School

Secondary : Daram National High School

Tertiary : Samar State University


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CURRICULUM VITAE


Name : Juna T. Tejones

Address : Poblacion 3, Daram Samar

Age : 21

Sex : Female


Course : BSED MATH


Elementary : Daram Elementary School

Secondary : Daram National High School



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CURRICULUM VITAE


Name : Ian Francis G. Ojeda

Address : Brgy. Parina, Jiabong Samar

Age : 20

Sex : Male


Course : BSED MATH


Elementary : Parina Elementary School

Secondary : Samar National School



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CURRICULUM VITAE


Name : Rhald Lemuel C. Montallana

Address : Oras, Eastern Samar

Age : 22

Sex : Male


Course : BSED MATH


Elementary : Cagpile Elementary School

Secondary : Oras National High School



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CURRICULUM VITAE


Name : Anito B. Fabilloren

Address : Brgy. Solupan, Paranas Samar

Age : 28

Sex : Male


Course : BSED MATH


Elementary : Pequit Elementary School

Secondary : Wright Vocational School


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