thesis final
TRANSCRIPT
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INTRODUCTION
For many years, educational researchers have maintained an interest in the effective
prediction of students’ academic achievement in school. The prediction and explanation of
academic achievement and the examination of the factors relating to the academic
achievement are topics of greatest importance in different educational levels. Studies have
shown that prior academic performance is an important predictor of performance in other
levels of education. Similarly, cognitive ability was found as the strongest predictor of
academic performance. However, some studies confirm that the correlation between
cognitive ability and academic performance tends to decline as students progress in the
educational system (Casis, 1995). Thus, many researchers have emphasized the need to
include non-cognitive factors such as personality, motivation (Aquinas, 1990), gender, race,
social class as well as aptitudes (Kerlinger, 1986) in investigations of individual differences
in academic achievement.
Researchers continue to investigate the sources of variance in academic achievement,
focusing on what students bring with them to school which either facilitate or hinder their
performance (Casis, 1995). Movements in contemporary education during the past few
decades, for instance, have considered the influence of other cognitive factors such as
learning styles (Barbe & Milone, 1981) and epistemological beliefs (Perry, 1970).
Epistemology refers to the justification, nature, sources and evaluation of knowledge.
It has been reported that epistemological and cognitive sophistication are positively related to
skills such as critical thinking, self regulation and ability to communicate ideas and learning
in collaboration. The investigation of students’ perceptions of learning, teaching and
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epistemological beliefs in the sciences has been widely researched because of their influences
on learning, goal orientation and use of cognitive strategies.
Similarly, educators have, for many years, noticed that some students prefer certain
methods of learning more than others (Diaz and Cartnal, 1999). These dispositions, referred
to as learning styles, form a student's unique learning preference and aid teachers in the
planning of small-group and individualized instruction.
Studies about the epistemological beliefs and learning styles correlated with the
academic achievement of high school students in the Philippines are very limited. In the
same manner, investigation about the moderating effects of different socio-demographic
characteristics of the students toward the relationship of learning style, epistemological
beliefs and academic performance has been very inadequate. Studies made would usually
tackle about the learning styles and epistemological beliefs of graduate and undergraduate
students. Additionally, comprehending how the Philippine secondary students think, process
information as well as recognizing their beliefs in acquiring and building their own cognitive
structures has caught little attention among Philippine researchers.
In the CLSU setting, not just the college students but also the high school students
share the same criticisms when they poorly perform in their academics specifically in science
subjects. This may be attributed to many factors such as language barrier (David, 1999),
mismatched learning and teaching styles (Velasquez, 2007), learning modalities (Leoveras,
2001), among others. Unfortunately, there were no specific studies yet that deeply examine
how these high school students manage their own understanding of their inner cognitive
constructs as well as their learning styles. It is important, thus, that researchers would make
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study pertaining to high school students’ learning styles and epistemological beliefs so that
not only the teachers would have an understanding of the students, but the students as well
would understand themselves as to how they will properly treat what they know and
understand their epistemic beliefs that they can utilize in dealing with various facets of
learning.
This study, therefore, was conducted to determine the dominant learning style of each
of the respondents and the classification of epistemological beliefs. It also looked into the
possibility of the effects of epistemological beliefs on the learning styles of the students.
Likewise, how individuals view knowledge and learning that would have an influence upon
their beliefs about their own ability to engage in academic tasks was analyzed. It further
investigated whether epistemological beliefs and learning styles would have an impact on
student's academic performance. Lastly, this study explored the possible influence of
moderating variables such as age, gender, school's location, ICT accessibility, monthly family
income, parents’ educational attainment, and parents’ occupation on the epistemological
beliefs, learning styles, and academic performance of the CLSU high school students.
Statement of the Problem
The growing concern about students’ epistemological beliefs and learning styles is
paving the way for more researches to understand how students may relate their
understanding, adoption of goal orientations and use of metacognitive and self-regulated
learning strategies, among other important aspects of learning in schools.
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There are efforts to study the influence of epistemological beliefs on various learning
strategies. These studies investigated the use of strategies for specific tasks and in the
contexts of traditional classroom learning. However, little work has been done to evaluate the
epistemological beliefs and learning styles of students in general and evaluate the effects of
the epistemological beliefs and learning styles on academic performance of students. It is
also interesting to note, that in the past, little attention has been given to assess the influence
of several moderating variables in the relationship between the students’ academic
performance, learning styles and epistemological beliefs.
In the context of this objective, this study addressed the following questions:
1. What is the most dominant learning style among high school students in
Biology?
2. What types of epistemological beliefs are possessed by the high school students
in Biology?
3. What is the profile of student’s academic performance in Biology during the
school year 2009-2010?
4. Is there a significant relationship between the high school students’
epistemological beliefs and learning styles in Biology?
5. Is there a significant relationship between the high school students’ learning
styles and academic performance in Biology?
6. Is there a significant relationship between the high school students’
epistemological beliefs and academic performance in Biology?
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7. Do dimensions of the students’ learning styles and epistemological beliefs
predict the academic performance of the students in Biology?
8. Is the relationship between learning styles and academic performance moderated
by age, gender, school's location, ICT accessibility, monthly family income,
parents’ educational background, parents’ occupation?
9. Is the relationship between epistemological beliefs and academic performance
moderated by age, gender, school's location, ICT accessibility, monthly family
income, parents’ educational background, parents’ occupation?
10. What are the socio-demographic characteristics of the CLSU sophomore high
school students in terms of age, gender, school's location, ICT accessibility,
monthly family income, parents’ educational background, parents’ occupation?
Objectives of the Study
The purpose of this study was to investigate the types of learning styles and
epistemological beliefs of the students and to determine the effects of students’ beliefs and
learning style on their academic performance as measured by their final grade in Biology in
the five high schools of Central Luzon State University during school year 2009-2010. This
study was conceptualized to investigate whether students’ epistemological beliefs and
learning styles would predict their academic performance. Furthermore, it was conducted to
test the moderating effect of several socio-demographic characteristics on the relationship of
students’ learning styles, epistemological beliefs, and their academic performance.
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Specifically, this study was conducted in order to:
1. find out the most dominant learning style among high school students in Biology;
2. ascertain the types of epistemological beliefs of the high school students in
Biology;
3. determine the profile of student’s academic performance in Biology during the
school year 2009-2010;
4. determine if there is a significant relationship between the high school students’
epistemological beliefs and learning styles in Biology;
5. determine if there is a significant relationship between the high school students’
learning styles and academic performance in Biology;
6. determine if there is a significant relationship between the high school students’
epistemological beliefs and academic performance in Biology;
7. find out whether the dimensions of the students’ learning styles and
epistemological beliefs predicted the academic performance of the students in
Biology.
8. find out whether the relationship between learning styles and academic
performance is moderated by age, gender, school's location, ICT accessibility,
monthly family income, parents’ educational background, parents’ occupation;
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9. establish whether the relationship between epistemological beliefs and academic
performance is moderated by age, gender, school's location, ICT accessibility,
monthly family income, parents’ educational background, parents’ occupation; and
10. determine the socio-demographic characteristics of CLSU high school students in
terms of age, gender, school's location, ICT accessibility, monthly family income,
parents’ educational background, parents’ occupation.
Hypotheses of the Study
The following hypotheses were tested at 0.05 level of confidence:
1. There is no significant relationship between the high school students’
epistemological beliefs and learning styles in Biology during the school year
2009-2010;
2. There is no significant relationship between the high school students’ learning
styles, epistemological beliefs and academic performance in Biology during
the school year 2009-2010;
3. Learning styles and epistemological beliefs do not predict the academic
performance of students in Biology.
4. The relationship between learning styles and academic performance is not
moderated by age, gender, school's location, ICT accessibility, monthly family
income, parents’ educational background, parents’ occupation; and
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5. The relationship between epistemological beliefs and academic performance
is not moderated by age, gender, school's location, ICT accessibility, monthly
family income, parents’ educational background, parents’ occupation;
Significance of the Study
This study is an important contribution to the Philippine research on learning styles
and epistemological beliefs. It used an improved design in investigating relationships among
learning styles, epistemological beliefs and academic performance by employing causal and
effect design through regression analysis. Moreover, the study considered other factors
namely: age, gender, school’s location, ICT accessibility, monthly family income, parents’
educational attainment and parents’ occupation . Second, it involved high school students
who are mainly from rural school – groups that the researcher has observed have been rarely
involved in previous studies. This study, therefore, provides not only a basis for a more
thorough understanding of Filipino high school learners but also an alternative perspective in
efforts to improve students' academic achievement levels.
It was anticipated that the results of this study would:
1. Provide theoretical development to support more in-depth studies of students’
learning styles and academic performance;
2. Emphasize the critical roles of epistemological beliefs and learning styles in
influencing academic performance of students; and
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3. Render a set of principles for creating a learning environment that would
enhance students’ development of sophisticated epistemological beliefs.
Scope and Limitation of the Study
This study focused on ascertaining the epistemological beliefs, learning styles and
academic performance of high school students of five high schools of the Central Luzon
State University. This study also correlated epistemological beliefs and learning styles to
academic performance and tried to look into the moderating influence of age, gender,
school's location, ICT accessibility, monthly family income, parents’ educational
background, parents’ occupation on the relationship between the abovementioned variables.
One hundred forty seven high school students from the University Laboratory High
School Bibiclat, Palusapis, and Pinili, all satellite high schools of CLSU that execute Revised
Basic Education Curriculum, Agricultural Science and Technology School which is primarily
an agricultural high school and the University Science High School that implements the
science curriculum, were the respondents of this research. All of them are using the same
reference materials.
The Learning Styles Inventory developed by Grasha and Reichmann (1996) and
Epistemological Beliefs Inventory developed by Schraw et al (2002) were used to assess
respondents’ learning styles and epistemological beliefs, respectively. The academic
performance refers to the final grade obtained by the students in Biology.
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Time and Place of the Study
This study was conducted during the 1st semester S.Y. 2010-2011 in the five high
schools of the Central Luzon State University namely: ULHS Palusapis in Science City of
Muñoz, ULHS Bibiclat in Aliaga, ULHS Pinili in San Jose City, the Agricultural Science and
Technology School and the University Science High School both situated within CLSU main
campus; ULHS-Palusapis, ULHS-Bibiclat, ULHS-Pinili are outreach high schools operated
by CLSU.
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REVIEW OF LITERATURE
Epistemological Beliefs
Development of Personal Epistemology Research
The seminal work of William Perry (1970) revealed that liberal arts students in
Harvard University and Radcliffe University increasingly developed more complex and
integrated epistemological beliefs as they progressed through their course and noticed that
students moved through four main epistemological positions, which he described as dualism,
multiplism, relativism and commitment. Individuals who held dualistic views about the
nature of knowledge believed that absolute truths (right/wrong) exist and could be
transmitted to an individual from an authority or expert. Next, when individuals began to
conceive knowledge in a multiplistic way, they conceded that, as well as absolute truths,
there were some things that could not be known with any certainty. Such individuals believed
that knowledge comprised both personal opinions and ultimate truths. They relied less on
authorities for absolute truths, and personal opinions and truths were still considered to be
'right' or 'wrong'. The next position, relativism, constituted a major shift in epistemological
thinking because individuals considered that knowledge is actively and personally
constructed, although initially this may have occurred in some contexts only. Absolute truths
no longer exist because truth is considered to be relative to individuals' personal
interpretations of experiences. In the final position, related to commitment, relativistic
thinking is still a feature, but particular beliefs are more valued than others and the
commitment to them was flexible. Although these positions are not intended to be gender-
specific, they were derived using male Harvard students. In subsequent research, Belenky et
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al. (1986) derived a similar set of epistemological positions using female samples.
Baxter Magolda (1993) continued this line of research, using a sample of more than
100 male and female college students in longitudinal research. The students were interviewed
yearly using open-ended questions and asked to complete short answer responses to the
Measure of Epistemological Reflections (MER). The sample included 50 males and 51
females at a Midwestern university with a final sample of 80 students in the fourth year of
the study (Baxter Magolda, 1994). This study was extended also up into the post-college
years with 70 students (Baxter Magolda, 1994).
Perry’s (1970) development model is not without critics. Moore (2002) reports that in
social constructivist literature, some researchers include Perry’s scheme in their critiques
those developmental perspectives “emphasize individual cognition and universal forms of
thought to the exclusion of sociocultural and contextual factors”. Hofer and Pintrich (1997)
stated that the epistemological movement in the Perry’s lower stages is clearer than
movement in the upper stages.
Schommer (1994) proposes that epistemological beliefs be conceived as a system of
relatively independent beliefs. She claims that there is more than one epistemological
dimension to consider and each dimension has a range of possible values. On the other hand,
Schommer (1994) does not totally discount the role of development in personal
epistemology. She also states that beliefs do not develop in synchrony and that the synchrony
or asynchrony of beliefs is dependent on an individual’s developmental level (Schommer-
Aikens, 2002). Schommer (1994) outlines five epistemological dimensions and their
corresponding values: (1) certainty of knowledge, ranging from knowledge is absolute, to
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knowledge is tentative; (2) structure of knowledge, ranging from knowledge is organized as
isolated bits and pieces, to knowledge is organized as highly interwoven concepts; (3) source
of knowledge, ranging from knowledge, is handed down by authority to knowledge is
derived through reason; (4) control of knowledge acquisition, ranging from the ability to
learn is fixed at birth, the ability to learn can be changed; and (5) the speed of the knowledge
acquisition, ranging from knowledge is acquired quickly or not-at-all to knowledge is
acquired gradually. According to Schommer (1994a), epistemological beliefs are relatively
independent, meaning that individuals are not necessarily sophisticated or naïve in all beliefs
concurrently. For instance, individuals may believe that the solution to poverty is highly
complex, yet once the solution is found, it will be absolute (Schommer, 1994a). Rather than
characterizing epistemological beliefs as a single point on a dimension, Schommer (1994a)
proposes that individuals’ epistemological beliefs are best represented as frequency
distributions with the distinction between the naïve learner and the sophisticated learner a
matter of the shape of the distribution. For example, the sophisticated learner may believe
that a small amount of knowledge is unchanging, some knowledge has yet to be discovered,
and a large amount of knowledge is evolving (Schommer, 1994b). On the contrary, the naïve
individual believes much knowledge is certain, some knowledge has yet to be discovered,
and a small portion of knowledge is changing (Schommer, 1994b). While based on Perry’s
(1970) groundbreaking work, the most noted distinction in Schommer’s theory (1990, 1994a)
is that one cannot simply assume that epistemological beliefs are in sync, especially when
individuals are changing their epistemological beliefs (Duell & Schommer-Aikens, 2001). In
other words, beliefs are independent and may not develop at the same rate or be inconsistent
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with each other (Schommer & Walker, 1997). For example, an individual may hold extreme
beliefs that knowledge is isolated, made up of pieces of information and certain or never
changing. As development occurs, the individual’s belief that knowledge is isolated may
change to the belief that knowledge is highly complex and involves an intricate network of
ideas. At the same time, this individual may still believe that knowledge is completely certain
(Schommer & Walker, 1997).
Hofer and Pintrich (1997) relay the important contribution of Schommer’s work and
that her research initiated other researchers to investigate how epistemological beliefs might
be linked to issues of academic classroom learning and performance. Schommer (1994a)
purports that epistemological beliefs have indirect and direct effects on aspects of cognition
and how students approach learning.
In her Reflective Judgment Model about Epistemological Beliefs in the Classroom,
King (2000) described the frustration and misunderstandings in both student and teacher
experience when there is a large discrepancy between student’s and professor’s expectations
about a course and what should occur in the classroom. King further explained that both
teachers and students hold expectations about the teaching and learning process and asserted
that these expectations are shaped by prior experiences and personal philosophies. Some of
these expectations reflect what both consider to be “important to learn, how it should be
learned, who has what responsibilities in the teacher-student relationship,” and how much
time and energy should be devoted to the course. The vital element underlying expectations
about teaching and learning is the assumptions a person holds about knowledge and how it is
gained. These expectations and beliefs about teaching and learning are epistemological as
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they focus on the nature and origin of knowledge. Baxter Magolda (1992a) suggests that
“students’ epistemologies affect students’ interpretations of community, involvement in
learning, and the pedagogies aimed at creating both”.
In line with Baxter Magolda’s assertions, Kember (2001) found that attitudes and the
ability to cope with studying at institutions of higher education were influenced by students’
sets of beliefs about knowledge and the process of teaching and learning. Kember suggests
that higher education assist new students with the transition to belief systems in line with
more experienced students.
Paulsen and Feldman (1999) explored the relationship between epistemological
beliefs of students and their motivation to learn. They found that sophisticated beliefs in the
areas of simple knowledge, quick learning, and fixed ability were significantly related to the
motivational constructs of intrinsic goal orientation, extrinsic goal orientation, task value,
control of learning, self-efficacy, and test anxiety. Paulsen and Feldman (1999) and Kember
(2001) discuss the need for higher education to provide a learning environment that promotes
the development of students’ epistemological beliefs. Further evidence of the importance of
and the need for additional research on students’ epistemological beliefs is found in studies
that assess students’ beliefs and academic performance. Several researchers (Schommer et
al., 1992; Schommer 1990, 1988; Ryan, 1984) found that more sophisticated epistemological
beliefs were related to better grades, enhanced test performance, and more sophisticated
study strategies.
Schrader (2004) suggests that classrooms that feel intellectually safe to students,
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resulting in more conducive learning environments, are derived from a moral atmosphere and
an epistemological “fit” between teacher and student. A moral climate in the classroom is one
where the instructor models respect, critical reflection, inclusiveness and support. It was
hypothesized that even if a moral climate is present; there may be tension between students’
and professors’ epistemological perspectives or fit. The instructor may challenge students to
think beyond their ways of knowing that they feel comfortable with, and the learning
experience may not fit the students’ epistemological perspectives. For instance, the teacher
may validate contradictory viewpoints or focus on construction of knowledge rather than on
disseminating knowledge (Schrader, 2004). On the other hand, students who feel supported
in their views and safe to speak their mind and question their assumptions will more likely
accept the challenge of a new way of thinking and be more apt to adopt new views. This
event is described as “epistemic stretch” (Schrader, 2004). Further, students must first be met
or valued at their initial level of epistemic thought before being able to accept new
epistemologies.
Many studies in epistemological literature illustrate the importance of students’
epistemological beliefs and their academic performance (Kember, 2001; Paulsen & Feldman,
1999; Hofer & Pintrich, 1997; Kardash & Scholes, 1996; Rukavina & Daneman, 1996; Qian
& Alvermann, 1995; Schraw et al 1995; Schommer, 1993a, 1993b, 1988, 1990; Ryan, 1984).
A study made by David (2008) found that BS Biology students and BSEd-major in
Biology students taking up Plant Physiology at Central Luzon State University showed
sophisticated epistemological beliefs on the dimensions of knowledge and the process of
knowing in acquiring knowledge when subjected to constructivist learning environment that
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brought them positive effect in improving the conceptual change. Majority of them held
mixed epistemological beliefs on the source of knowledge. Moreover, better conceptual
change was experienced by the students with sophisticated epistemological beliefs regardless
of their pre-instructional conception.
There is a scarcity of research, however, regarding students’ beliefs compared to those
of their instructors and how these beliefs affect students’ experience and integration into the
academic community. Previous research has found links between certain profiles of such
beliefs about epistemology and higher academic performance (Lodewyk, 2007; Schommer,
1993a) along with a host of achievement-enhancing factors like problem-solving (King &
Kitchener, 1994), comprehension (Qian & Alvermann, 1995), conceptual change (David,
2008; Mason & Boscolo, 2004) motivation (Qian & Alvermann, 1995), and use of study
strategies ( Leoveras, 2001; Schommer et al, 1992).
Epistemological Beliefs and Academic Performance
Epistemological beliefs were found to have an influence on performance of several
different learning tasks in literature such as physics conceptual understanding (Hammer,
1994), text comprehension (Schommer et al., 1992; Schommer, 1990; Ryan, 1984), science
learning (Qian & Alvermann, 1995; Songer & Linn, 1991), and general academic
achievement (Schommer, 1993). Ryan (1984) also found that students’ beliefs about
knowledge affect their understanding of complex topics or complex academic tasks like
conceptual change learning. Davis (1997) stated that students’ beliefs influence short term
performance in science class as well as their long term progress. Schommer (1993), in her
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study with high school students, showed that naïve beliefs about epistemology are associated
with low GPA’s.
Several researchers in the science education literature investigated the students’
beliefs about nature of science and the relationships between these beliefs and science
learning and achievement since 1980’s (Qian & Alvermann, 1995; Solomon et al., 1994;
Larochelle & Desautels, 1991; Songer & Linn, 1991). Epistemological beliefs are believed to
contribute to understanding of science concepts, science learning and performance in science
classrooms (Tsai, 1998b; 2000a; Hammer, 1994; Schommer, 1993; Songer & Linn, 1991).
Schommer (1997) stated that there is relationship between epistemological beliefs and
learning. In one of her studies with colloquies (Schommer et al., 1992), it was stated that
more students believe that the knowledge best characterized as isolated facts, the more
difficulty students have in understanding information in complex domains such as statistics
and medicine. Schommer (1993) also stated that academic achievement of students are not
only directly influenced by the epistemological beliefs, but also indirectly influenced by the
students’ learning approaches; epistemological beliefs may affect the students’ learning
approaches and these approaches in consequence influence their academic achievement.
In her study of 1,000 high school students, Schommer (1993) investigated the
development of secondary school students’ epistemological beliefs and the influence of these
beliefs on academic performance. The sample composed of 405 freshman, 312 sophomore,
274 junior and 191 senior high school students. Epistemological beliefs of the students were
assessed by Schommer’s (1990) questionnaire composed of 12 subsets of items to investigate
students’ preferences about knowledge and learning. In order to examine the influence of
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epistemological beliefs on overall academic performance, the researcher conducted
regression analysis in which students’ GPA scores were regressed on the four epistemological
factor scores. The results showed that all four epistemological factors predicted GPA.
In order to obtain a complete understanding of personal epistemology, and its’
relationship with academic performance, Schommer-Aikins and Easter (2006) conducted a
study with 107 college students. In this study, the researchers investigated two epistemic
paradigms; namely, ways of knowing (connected knowing and separate knowing) and
epistemological beliefs (beliefs about the speed of knowledge acquisition-speed, the structure
of knowledge-structure, knowledge construction and modification-construction,
characteristics of successful students-success, and attainability of truth-truth). Students’
academic performance was based on their scores on reading comprehension test and a
university course grade. Path analysis revealed that the effects of ways of knowing on
academic performance are mediated by belief in the speed of learning.
In a more specific area of research in terms of science education, Conley, et al. (2004)
conducted a correlational study in order to investigate the changes in 187 fifth grade students’
epistemological beliefs in a nine-week hands-on science unit. The researchers assessed
students’ epistemological beliefs in four dimensions, namely Source, Certainty, Development
and Justification by using Elder’ (1999) instrument. They also collected data related to
students’ gender, ethnicity, socio economic status and achievement from school records. They
used the combination of mathematics and reading test scores from the Stanford Achievement
Test as an indicator of students’ achievement. Students’ epistemological beliefs were
measured both at the beginning and at end of the unit. Results showed, that students’
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epistemological beliefs about source and certainty of knowledge became more sophisticated
at the end of the unit meaning that students moved away from the beliefs that knowledge was
certain and existed in external authorities. However, there were no significant changes in
development and justification in sub-dimensions. The researchers also investigated the effect
of gender, ethnicity, SES and achievement in the development of epistemological beliefs. The
result showed that there were no main or moderating effects of gender or ethnicity, but effects
of SES and achievement are observed. According to the results, students with low SES and
low achievement levels had less sophisticated beliefs compared to students with average SES
and high achievement level. Also, it was0 found out that high achievers had more
sophisticated beliefs. Correlation results showed that at the end of the intervention, it was
found that there were significant correlations between all four epistemological beliefs sub-
dimensions and achievement, namely; Source, Certainty, Development, and Justification.
Songer and Linn (1991) investigated the relationship between 153 eight grade
students’ epistemological views about science and their ability to integrate scientific
knowledge about thermodynamics. The participant students enrolled in a one semester
physical science class. A nine-item measure called The View of Science Evaluation was used
to collect data from students about their beliefs about science. As a result of the analysis,
students’ beliefs were categorized into three groups: a) dynamic beliefs, b) static beliefs, and
c) mixed beliefs. Students who have dynamic beliefs about science were likely to view
scientific knowledge as controversial and changing. On the other hand, students who have
static beliefs about science were unlikely to recognize the controversy in science knowledge.
These students believed that scientific knowledge is unchanging. The researchers also found
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that students having dynamic views related to epistemology of science were more likely to
demonstrate understanding of heat and temperature topic than students having more static
views of science. In other words, students believing, changing and developing nature of
scientific knowledge were more likely to integrate concepts in thermodynamics than students
believing that scientific knowledge is certain and stable. Songer and Linn (1991) explained
that if students believe that science consists of separate and isolated pieces of knowledge,
they may not able to integrate the knowledge presented in science classes. They added that, if
science is presented to students as relatively unrelated pieces of information, it will make
science learning even harder. Students can integrate science knowledge properly, if they are
presented with an appropriate nature of science view and with an instruction parallel to this
constructivist view.
Learning Styles
Research about learning styles began to develop several decades ago from several
different directions. These included early studies on cognitive growth, the areas of the brain
related to intelligence and behavior, and the influence of school environmental and social
factors on students. Learning styles can be defined, classified and identified in many different
ways. Gregorc (1978) based learning on perceptual preferences, concrete and abstract, and
ordering preferences, sequential and random. Kolb (1984) defined the way people learn
through “feelings” or through “thinking.” He defined learning as the process whereby
knowledge is created through the transformation of experience. In order to understand
learning, we must understand the nature and forms of human knowledge and the processes
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whereby this knowledge is created. In Kolb’s Experiential Learning Theory model (ELT),
Kolb defined three stages of a person’s development: acquisition, specialization and
integration.
Anthony Grasha and Sheryl Reichmann developed the Grasha-Reichmann Student
Learning Style Scales (GRSLAA) in 1974 (Reichmann & Grasha, 1974; Grasha, 1972) to
develop college student’s styles in classroom participation. Over a period of two years,
Grasha and Reichmann interviewed undergraduate students of the University of Cincinnati.
These students were asked to sort student behaviors in a typical classroom into response
styles. The student’s response styles were based on three classroom dimensions: student’s
attitudes toward learning, their views of the teacher and/or peers, and their reaction to
classroom procedures. From these three classroom dimensions three styles emerged:
avoidant-participant, competitive-collaborative, and dependent-independent.
Participant/Avoidant
Students with participant style are eager to learn course content, enjoy learning, and
take responsibility for their own learning. Students with avoidant style do not want to learn
the content, do not enjoy learning, and avoid taking part in course activities.
Students with participant style are more likely to do well in distance learning, which
requires more effort on their part than the typical classroom. To teach students with avoidant
style, demonstrate how learning the material will benefit them in their own lives.
Collaborative/Competitive
Students with collaborative style work well with others and enjoy cooperative
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learning and working in groups. Students with a competitive style see the classroom as a win-
lose situation in which they must win. These students will enjoy competitive activities.
Distance education that stresses cooperative learning and group projects will appeal
to students with a collaborative style. For students with competitive style, provide
opportunities for individual recognition. Instructional games or case study competitions will
also appeal to competitive learners.
Independent/Dependent
Students with independent style are curious and confident learners. They prefer to
work on their own in individual activities. Students with a dependent style see the teacher as
a source of information, want to be told what to do, and will learn only what is required.
For students with independent style, give them opportunities for independent study,
self-paced work, or special projects based on their interests. Students with dependent learning
style will need more guidance from the teacher. It is important to recognize these students in
a distance learning situation, as they may flounder without explicit instructor guidance.
According to Diaz and Cartnal (1999), the Grasha-Riechmann Student Learning
Style Scales (GRSLSS) was designed specifically to be used for senior high school and
college students. Diaz and Cartnal pointed out that this instrument not only measures the
learning styles of students but also how they deal with their fellow students and teachers. It
was also noted that the information gleaned from the GRSLSS can help instructors create
effective syllabi and allow them to be more attuned to the needs of their students. As with
Kolb’s Learning Style Inventory, learners have some aspects of all six attributes when
measured with the GRSLSS, but learners tend towards dominance in one or two categories
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(Diaz and Cartnal, 1999).
Learning Style and Academic Performance
Learning style is the way the students take in and process information. Learners have
different learning styles. Some prefer to work with concrete information while others are
more comfortable with abstraction. Understanding one’s learning style can improve the
student’s learning effectiveness in and outside of the classroom (Carbonel, 2008).
Drysdale et al. (2001) have shown that academic success and failure in higher
education is influenced by “the match between how material is presented and how students
process it”. They also found a correlation between learning style and increased levels of
GPA. Dunn et al. (1995) found that making students aware of their learning style and helping
them develop study skills compatible with their preferred learning style had a positive affect
on academic performance. In a similar vein, Griggs and Dunn (1996) claimed that students
who learn from an approach compatible with their preferred learning style experience greater
academic achievement and had more positive attitude towards learning.
Castro and Peck (2005) carried out a study on learning styles and learning difficulties
that foreign language students face at the college level and claim that student’s prefererence
for learning style can help or hinder success in a foreign language classroom. However, when
they analyzed the distribution of grades according to Kolb’s learning style types, they found
no significant correlation between learning style and grades.
Grasha and Reichmann (1996) believed that students’ learning styles can be identified
through the social and effective perspective like attitude toward teachers and peers, and
reaction to classroom procedures. Effective teaching requires a thorough understanding of the
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learning process, characteristics of students at different stages of development, individual
differences, factors that influence motivation, and procedures for maintaining orderly
classrooms. Teachers rely on this background when they make decisions about what they will
teach, which points they will emphasize, and how they will present content to their students
(Eggen & Kauchak, 1994).
Learning styles refer to the way people use the abilities they have. Learning styles
refer to what a person prefers to do, whereas skill, ability, and achievement refer to what a
person can do. The optimal conditions for learning include a good fit between learning styles
and learning environments. When a person’s learning styles are compatible with his learning
environments (i.e., affordances of the tasks, tools, instruction, etc.), the task seems easy and
the person is motivated, energized and productive. When a person is engaged in academic
work that does not matter with his learning styles, the work is arduous and draining
(Sternberg, 1997).
Dunn et al. (1995) conducted a meta-analysis of results across 42 experimental
studies designed to determine the value of teaching students through their own learning style
preferences. Using quantitative methods to compare across the different studies, it was
concluded that matching student learning style preferences with instructional method is
clearly advantageous to the academic achievement of the respondents. The combined
evidence from the analysis conducted by Dunn et al. (1995) showed that students whose
learning styles were accommodated in teaching methodologies were characterized by
learning achievements higher than students whose styles were not accommodated (75 percent
of a standard deviation). Similarly, working with nursing students, Laurillard (1994) showed
26
that a group of students provided with learning opportunities based on their identified
learning style preferences achieved statistically significantly higher grades than did a control
group of students provided with homogeneous instructional methodology.
In the same way, an extensive study by Hayes and Allinson (1997) led them to the
conclusion that the matching of learning styles to teaching methods in the workplace
positively influences learning outcome; and that learning style can be influenced by
educational experience. However, they also argue that some learning styles appear to be more
suited to workplace learning and the performance of certain duties than other styles.
Instructional strategies can be developed around an understanding of learning styles
and preferences in any given learning context, by providing more or less guidance and
structure to students, depending on their level of self-directedness or dependence; by
providing greater social interaction during learning where the group style would indicate that
is preferred; and more or less hands-on learning tasks, depending on their level of preference
for that or for more verbal forms of learning (Diaz and Cartnal, 1999).
Sarasin (1998) noted that instructors should be willing to change their teaching
strategies and techniques based on an appreciation of the variety of student learning styles.
“Teachers should try to ensure that their methods, materials and resources fit the ways in
which their students learn and maximize the learning potential of each student”.
In their review of cognitive style, Sternberg and Grigorenko (1997) have observed
that everyone possesses every style to some degree, and that people will use different styles
in different learning situations. The notion that individuals use different styles in different
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accommodating learning styles support document situations has also been proposed by
Laurillard (1993) and Kolb (1986).
In a study conducted among 120 high school students taking Biology, Santos (2008)
found that students who have high academic achievement tended to hold more positive
learning styles, that is, majority of them are independent and participative while those
students who have low academic achievement were mostly dependent and avoidant.
Furthermore, the more these students are given activities by themselves; they showed
significant positive effect on their academic achievement.
The same findings were observed among 100 senior high school students in the study
of Ayuste and Duran (2009). Students headed towards high academic achievement when
activities were designed for the students to work individually or in collaboration with others
with minimum supervision from their teacher. On the other hand, avoidance and dependence
were noticed among students who have low academic achievement.
Predictors of Academic Performance
Epistemological Beliefs
In the field of education, epistemological beliefs have been an important construct for
the past two decades and have frequently been used to predict achievement or achievement-
related behavior (Buehl & Alexander, 2001; Hofer & Pintrich, 1997). It has been assumed
that—similar to motivational constructs, sophisticated epistemological beliefs will positively
affect the learning process, and factors such as the choice of learning have been proposed as
mediating mechanisms. A significant relationship between achievement and epistemological
28
beliefs has indeed been found in several non-experimental and experimental studies (e.g.
Hofer, 2005; Ryan, 1984). However, the strength of this relationship varies across samples
and depends to some degree on the dimensions examined.
For instance, in the Schommer (1993) study with high school students, grade point
average (GPA) was significantly negatively predicted by the four dimensions covered in the
questionnaire (quick learning, stable knowledge/certainty, simple knowledge, fixed ability).
When controlling for verbal IQ, however, only the quick learning dimension remained
significant. The effect of the quick learning dimension on academic achievement was
confirmed in a longitudinal extension of the Schommer (1993) study by Schommer, et al.
(1997). However, neither stable knowledge/certainty nor two other dimensions significantly
contributed to the explanation of GPA in either study. Similarly, stable knowledge/certainty
beliefs were not significantly related to math test performance in a study of 139
undergraduate and graduate students (Schommer et al., 1992). The stable
knowledge/certainty dimension did, however, predict inappropriately absolute conclusions in
a study of 86 junior college students who completed several comprehension tasks after
reading text passages (Schommer, 1990). Similarly, Kardash and Scholes (1996) reported that
beliefs about the certainty of knowledge predicted the types of conclusions drawn by high
school students (ND96) after reading mixed evidence on a controversial topic (causes of
AIDS). The stronger the students’ beliefs in the certainty of knowledge, the more likely they
were to draw conclusions that failed to take into account the inconclusive nature of
information provided. The certainty dimension was also significantly related to achievement
in a study of 326 first year college students (Hofer, 2005). In this study, certainty scores on
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both domain-general and domain-specific measures were the strongest predictors of
academic achievement. The higher their certainty scores, the lower the students’ academic
standing.
In order to obtain a complete understanding of personal epistemology, and its
predictive power on academic performance, Schommer-Aikins and Easter (2006) conducted
a study of 107 college students. In this study, the researchers investigated two epistemic
paradigms; namely; ways of knowing (connected knowing and separate knowing) and
epistemological beliefs (beliefs about the speed of knowledge acquisition-speed, the structure
of knowledge-structure, knowledge construction and modification-construction,
characteristics of successful students-success, and attainability of truth-truth). Students’
academic performance was based on their scores on reading comprehension test and a
university course grade. Path analysis revealed that the effects of ways of knowing on
academic performance are mediated by belief in the speed of learning.
Kızılgüneş (2007) investigated the predictive influences of 1041 sixth grade students’
epistemological beliefs, achievement motivation, learning approaches on achievement in
classification concepts in science. She used the Turkish versions of Learning Approach
Questionnaire, Epistemological Beliefs Questionnaire, Achievement Motivation
Questionnaire and Classification Concept Test. Results of the study showed that most of the
students believed tentative nature of science, they utilized meaningful learning approach
during their science learning and they liked to learn something new. Students’ achievement
scores were found to be correlated with their epistemological beliefs, learning approaches
and goal orientations. Regression analysis revealed that learning approaches explained 12%
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of the variance and epistemological beliefs explained two percent of the variance in students’
achievement.
Similarly, in a survey study of 1269 grade 7 and 8 students to examine
epistemological beliefs, Schommer, et al. (2000) also investigated the predictive value of
epistemological beliefs in students GPA scores. The students in the study completed the
revised version of Schommer’s epistemological beliefs questionnaire. Only some part of the
students’ GPA scores could be obtained from school records. Therefore, to ensure that
students with GPA scores were not substantially different from the entire sample, the
researchers conducted chi-square analysis to compare students with and without GPA scores
information. No significant differences were found for gender or for grade level in school.
The researchers further tested the representativeness of beliefs of students with obtained GPA
information using one way multivariate analysis of variance incorporating the availability of
GPA predictor and epistemological belief scores as the criterion measures. There were no
significant differences obtained for the epistemological beliefs sub-dimension scores. Since
the researchers revealed that the students with available GPA scores were found comparable
with the entire sample, they continued with the regression analysis. In order to investigate the
predictive value of epistemological beliefs, students’ GPA scores were regressed on
epistemological beliefs scores in stepwise regression. At each step of the analysis, the
variable accounting for the largest variance entered the equation. Two of the predictor
variables were found significant; belief in fixed ability and belief in quick learning. It can be
concluded that there was a relationship between students’ epistemological beliefs and their
general achievement in school, more specifically, the less students believed in fixed ability to
31
learn and quick learning, the better GPA they had.
Trautwein and Ludtke (2007) examined the role of certainty beliefs as predictors of
school achievement using structural equation modeling. The certainty beliefs were specified
to be mediating the influence of cognitive abilities and family background on final school
grades. Family background, cultural capital, cognitive abilities, gender, age, were used as the
predictors of certainty beliefs and final school grade as an indicator of achievement. The fit
of this hypothetical model was found to be good. Similar to the findings of the other studies
in the literature, the certainty beliefs in the model had a negative significant effect on final
school grade (β = - .15, p < .001).
Learning Styles
Learning approaches can generally be defined as the learners’ ideas or conceptions of
learning, how they experience or define learning, and the strategies they use to learn (Cano,
2005). Similarly, Biggs (1991) described learning approaches as the ways students use
through their academic tasks that have an influence on the learning outcome.
Cavallo, Rozman, Blickenstaff and Walker (2003) conducted a study to explore
college students’ learning approaches, reasoning abilities, motivational goals, and beliefs
about the nature of science relative to science concept understanding and course
achievement. The study was conducted with 291 science major students enrolled in biology
or one of two different physics courses. Among the samples of the study, for the biology
major students, meaningful learning was significantly and positively correlated with learning
goals (r = .46). Rote learning was significantly and positively correlated with performance
32
goals (r = .37) and negatively correlated with learning goals (r = -.35). Also, they found that
performance goals were significantly and negatively correlated with epistemological beliefs
(r = -.23, p < .05), which means that high performance goals were related to beliefs that
science is fixed and authoritative. For biology students meaningful learning and tentative
view of science were positively related to learning goals. This means that these variables may
underlie the motivation to learn for just learning. Moreover, it was found that for biology
students, the reasoning ability, learning goals and scientific epistemological views were
positively correlated with course grade.
Boujaoude (1992) conducted a study to investigate the relationship between high
school students’ learning approaches, prior knowledge and attitudes towards chemistry, and
their performance on a misunderstanding test. Forty-nine high school students enrolled in the
study. The researcher observed the students for 16 weeks by attending eighty 50-minute
classes of a chemistry course. The typical week of the course included one laboratory period
and four lecture periods. To diagnose students’ misunderstandings about science, the
Misunderstanding Test was used. In order to assess their approaches to learning, The
Learning Approach Questionnaire developed by Donn was used. A stepwise multiple
regression analysis was applied to data in order to determine variables which were the best
predictors of performance on the Misunderstanding Post Test. The results showed that the
students’ performance on the misunderstanding pretest (36%) and their learning approaches
(14%) accounted a statistically significant proportion of the variance on their performance in
the misunderstanding posttest.
Diseth and Martinsen (2003) analyzed the relationship among approaches to learning
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(deep, strategic, surface), cognitive style, motives, and academic achievement. In their study,
192 undergraduate psychology students participated. A part of the Approaches and Study
Skills Inventory for Students was used to measure students’ learning approaches as deep,
strategic and surface approaches to learning. Results of the correlation analysis showed that
both the surface approach (r = -.19, p < .05) and the strategic approach (r = .06, p < .05)
correlated with the academic achievement significantly. The total set of variables was
analyzed using structural equation modeling to investigate their interrelationships and their
relationship to academic achievement simultaneously. The model showed that deep approach
to learning did not significantly predict academic achievement. As evidenced by the
correlation analysis, strategic and surface approaches predicted academic achievement
significantly in the model (r1 = .19, r2 = -.23, p < .05, for strategic and surface approaches
respectively). As a result of the study, it was found that approaches to learning predicted
academic achievement, however, motives and styles had only indirect effects on
achievement. Contrary to the expectations and the other studies in the literature, Diseth and
Martinsen (2003) found that deep approach to learning did not predict academic
achievement, while strategic and surface approaches significantly predicted achievement.
Bernardo (2003) investigated the influence of learning approaches to learning on
academic achievement of Filipino college students. The sample of the study consists of 156
male and 248 female students from a private university. The researcher used Biggs’ Learning
Approach Questionnaire to assess students’ approaches to learning. As a measure of
academic achievement, the students’ grade point averages (GPA) were used. The results
showed that deep and achieving sub-scale scores were positively related to academic
34
achievement even when the school ability and prior academic achievement were controlled,
whereas surface motive sub-scale scores and achievement were found to be negatively
correlated.
Sadler-Smith (1996) investigated if students’ study approaches predicted their
academic success and also the effects of gender, age, and program of study on approaches to
studying. The sample of the study had a total of 245 business studies students. The
respondents’ study approaches were assessed by a 38-item inventory in terms of three
primary orientations: deep approach, surface approach, and strategic approach. As the
indicators of academic success both the students’ end of semester scores on a core module
assessed by a variety of methods (course work, multiple choice test, and essay), and their
overall end of semester scores aggregated across 12 modules were used. Results revealed
moderately high positive correlations between deep and strategic orientations and between
surface and lack of direction orientations. The academic self confidence and surface
orientations were found to be correlated negatively, as did the strategic and lack of direction
orientations. For the entire sample of students, statistically significant correlation was
obtained for the overall academic performance and deep approach. However, for the sub-
groups, higher correlations were obtained. For the business computing sub-group of students,
lack of direction was found to be significantly correlated with the aggregate score as an
indicator of academic success, and for the accounting and finance sub-group, deep approach
significantly correlated with the aggregate score, and the strategic approach significantly
correlated with the test score.
In another study that examined learning approach and academic performance
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relationship, Cavallo (1996) investigated 189 tenth grade students’ meaningful learning
orientation and the relationship among those orientations, their reasoning ability,
understanding of genetic topics and problem solving ability in a one group pretest-posttest
design. Learning Approach Questionnaire was used to assess students’ learning approaches.
In order to assess students’ reasoning ability Classroom Test of Scientific Reasoning and to
assess their understanding of genetic topics three tests were used. Results of the correlation
analysis showed that there is no significant correlation between students’ meaningful learning
orientation and their reasoning ability. Stepwise multiple regression analysis revealed that
students’ meaningful learning orientation and reasoning ability predicted scores on the test of
understanding genetics topic. Reasoning ability predicted 9% of the variance and meaningful
learning orientation predicted 5% of the variance on the tests of understanding genetic topics.
Both meaningful learning and reasoning ability were found to be related with course
performance.
Moderating Variables
Several studies in the past established the relationship of the students’ achievement
and their socio-demographic characteristics. The socio-economics conditions under which
the parents of the children live are important factors that determine the student’s social
background. According to Velasquez (2007) and Carbonel (2008) the social class of the
students is defined by environment that provides different factors such as monthly family
income, parents’ occupation and parents’ educational background. The social class origin of
students on the average may explain differences in the students’ performance in school. In
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this study, these socio-demographic characteristics will be treated as moderating variables
that are anticipated to influence students’ epistemological beliefs, learning styles and
academic performance.
Moderating Variables and Epistemological Beliefs
The potential moderating role of select socio-demographic characteristics such as age,
gender, school's location, ICT accessibility, family income, parents’ educational attainment,
and parents’ occupation was also considered. Although it is clear that epistemological beliefs
change over the long term from less sophisticated to more sophisticated, personal factors can
facilitate or constrain development of epistemological beliefs. In the research on
epistemological beliefs, there is a fair amount of research on the role of socio-demographic
characteristics on achievement level of the students, but very little to none on the role of
school location, ICT accessibility and family income may play in the development of such.
There is a clear need to examine these factors and to investigate how they might moderate or
change the nature of development (Pintrich, 2002).
Although epistemological beliefs, particularly, certainty beliefs, have been found to
predict academic achievement in several studies in the past, results have not been
unequivocal. However, the non-significant findings may in part be attributable to the design
of the studies in question. As pointed out by Wood and Kardash (2002), studies on
epistemological beliefs often lack the power to detect small to moderate effect sizes. In
addition, most studies rely on convenience samples, which may decrease the likelihood of
finding significant effects. Moreover, although there likely is a link between cognitive
37
abilities (intelligence) and epistemological beliefs. Many studies examining the relationship
between epistemological beliefs and academic achievement have not taken cognitive abilities
into account. Likewise, characteristics of the family environment that are conducive to
academic progress (e.g., socioeconomic standing, cultural capital) are often disregarded.
Hence, even in the studies that have found link between certainty beliefs and academic
achievement, third variable explanations may apply.
Gender
The growing concern regarding the regulating effect of gender on academic
achievement of students as well as other educational constructs such as motivation, self-
regulation and epistemological beliefs increase over time in order to accommodate the
changes brought about by different environmental evolutions. Researches that focused on
demonstrating importance of gender in epistemological thinking were already studied in the
past in connection with one’s academic achievement (Baxter Magolda, 1992; Belenky et al,
1986). However, there are many other studies that find almost no mediating effect of gender
in epistemological thinking or beliefs (King & Kitchener, 1994; Kuhn, 1991). Pintrich (2002)
has recently suggested that gender may not be as important determiner in the change of
academic achievement of students in association with the epistemological thinking when it is
defined in terms of separate dimensions of epistemological beliefs. That is, when individuals
are asked to focus on specific dimensions of epistemological beliefs, rather than more holistic
and general ways of thinking, gender does not intervene in any of the relationships existing
within these variables.
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In the study of Trautwein and Lüdtke (2006) about the large-scale longitudinal study
on the impact of certainty beliefs on the school achievement of college students, they found
certainty beliefs to negatively predict school achievement, even when other important
variables were controlled. Certainty beliefs partly mediated the impact of cognitive abilities,
gender, and cultural capital on school achievement. Given that access to highly valued Welds
of study is competitive in Germany, the negative effect of certainty beliefs on final school
grades was by no means negligible.
Rennie (1998) argued that “if the issue of gender is to be considered effectively in
science teaching, account must be taken of the way gender is constructed in terms of
ethnicity, class, religion, race and often other variables as well.” In Baker’s study (2003),
gender and equity in science education have been reviewed since 1971. This review revealed
that between the years 1971 and 1978 not much emphasis was given on gender or equity. In
1980s, gender was investigated with respect to socioeconomic status, but this research lacked
sociological perspective. In late the 1980s, gender equity became an important issue in
several studies. By 1990s, researchers became interested in creating a school environment in
which girl-friendly instructional strategies, topics, and curriculum would be implemented.
Pintrich (2002) has suggested that there may not be important gender intervention
between students’ epistemological thinking and academic performance when the former is
described in terms of separate dimensions of epistemological beliefs. He argued that the
gender did not intercede with the relationship of epistemological beliefs as well as the
science achievement of secondary students when gender was considered in his study.
Gender effects on personal epistemological beliefs and performance of students have
39
been studied by a few researchers. Belenky et al. (1986) argued that at the early
developmental stage of personal epistemology, females view knowledge as handed down by
authority while males view knowledge as mastering what is handed down by authority. In
this argument, it is clear that at the same stage of the epistemological development females’
epistemological development is less complex than those of males with respect to authority.
On the contrary, Schommer’s (1993b) study investigated gender influence on students’
epistemological beliefs and academic achievement where girls were less likely to believe in
quick learning and fixed ability than the boys but this was statistically arbitrating in the
relationship between the students’ belief in simple and certain knowledge as well as their
achievement in science.
Meanwhile, although there were studies made in the past pertaining to the intervening
influence of gender, inconclusive reports were made regarding a series of research that
focused on the students’ epistemological beliefs and performance in science. Studies such as
those of Cano (2005), Baxter Magolda (1992), and Belenky et al, (1986) have found
important intercession of gender divergence in epistemological beliefs and science
achievement of students. In some studies, females showed more advanced beliefs than males
and relatively showed a more improved performance in school (Lodewyk, 2007; Mason et
al., 2006; Schommer and Dunnell, 1994; Schommer, 1993). Those, on the other hands, other
studies found almost no gender influence in epistemological thinking or beliefs and academic
accomplishment of students (Phan, 2008a; Hofer, 2006; Buehl et al, 2002; Kuhn and
Weinstock, 2000; King and Kitchener, 1994; Kuhn, 1991).
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Age
Studies of Conley, et al. (2004) and Schommer- Aikins, et al. (2005) started to study
younger students’ epistemological beliefs to test the hypothesis that students develop
epistemological beliefs at early ages. It was argued that there should be a link between
children’s theory of mind and epistemological thinking (Chandler et al., 2002). Conley et al.
(2004) study demonstrated that elementary school students’ epistemological beliefs about
science changed over time, hence, their academic achievement in science.
After a nine-week science course about chemical properties of substances taught with
emphasis on science process skills instruction, the students develop more sophisticated
beliefs about both the source and certainty of knowledge. At this age level, development of
the students’ epistemological beliefs can be fostered by hands-on or inquiry oriented
instruction. Related to students’ academic achievement, it was found that maturing students
tend to be high achiever in science when they developed more sophisticated epistemological
beliefs.
In another study, Schommer-Aikins et al. (2005) observed that multidimensional
model is applicable for middle grade students. They found that as students get older, quick
learning and innate ability were observed as distinct factors in improving their science
performance. In younger students, these two factors emerged as a single factor. It was stated
that young children have a global theory of mind whereas older students’ mind possessed
knowledge as processes and components. Again at this age level studying aimlessly was
found as another factor in which younger students believed that learning occurs as chance not
as a strategic activity. Related to the achievement variable, authors found that both beliefs in
41
quick learning and innate ability are predictors of students’ mathematical problem solving
ability. Earlier studies in high school (Schommer, 1993) and college levels (Schommer,
1990), demonstrated that the development of more sophisticated epistemological beliefs
mediated by their age resulted in better use of mathematical problem solving skills and
comprehension of complex text. Schommer-Aikins et al. (2005) also found that general
epistemological beliefs and mathematical beliefs affect students’ mathematical performance
and overall academic achievement.
Parents’ Educational Attainment
In the path analysis regarding family environment, epistemological beliefs, learning
strategies, and academic performance of students, Cano and Cardelle-Ellawar (2008)
specified that parents’ educational level and family’s intellectual climate are two possible
roots of epistemological beliefs about the speed and effort involved in learning, which in
their turn influence students’ learning strategies and academic performance and mediate the
effects of family variables. The results of path analysis suggested that some family
characteristics can predict children’s epistemological beliefs. The lower the educational level
of the parents, the more likely their children will develop naïve beliefs about quick, effortless
learning, a result which is in agreement with those of Schommer (1990, 1993a). They
observed that these beliefs depend not only on parents’ educational attainments, but also on
how these attainments are converted into an interest in social, cultural, political, and
intellectual activities (family intellectual–cultural climate). The better the family’s
intellectual climate, the more sophisticated the child’s beliefs about learning and the higher
42
their performance academically. Although this finding is broadly consistent with those of
Schommer (1990, 1993b) as regards family upbringing, it goes somewhat too far.
Further, family characteristics were also directly related to the cognitive and
metacognitive learning strategies that students engage in their school learning, and to the
academic achievement they attain. However, they suggested differentiating between family’s
intellectual climate, which is linked to all the learning strategies but not to academic
performance, and parents’ educational level, which is associated only with surface strategy
but predicts academic performance. The present pattern of results is in line with those of the
literature (Adams et al., 2000; Cool & Keith, 1991; Ryan & Adams, 1995; Cano, 2007).
In their study, Kardash and Howell (2000) proposed that more important aspect of
mediating variables’ influence is the indirect effects more than its direct effect. The latter
showed clearly that a family related variables such as parents’ educational attainment and
occupation mediate the influence of quick and effortless learning on children’s learning
strategies and academic performance. Parents’ educational level and family’s intellectual
climate show roughly similar indirect effects, except for those on metacognitive learning
strategies, which are greater. The belief referred to is also indirectly related to surface
strategy and academic performance, but most strongly to metacognitive learning strategies:
Students whose families encourage discussion and an interest in culture and that are
intellectually inclined appear to predispose their children to have mature beliefs about
learning and indirectly predispose them to deploy strategies aimed at regulating and
controlling their learning (which in turn is the variable with the highest positive impact on
academic performance). Previous research shows the mediator role of epistemological beliefs
43
on comprehension test performance (Schommer et al., 1992).
Monthly Family Income
Studies were started to investigate the relationship among socioeconomic status,
students’ beliefs in learning and academic performance. Earlier understanding of socio-
cultural variables including the status of the family indicated a very important issue for
researchers. In this understanding, it is clear that family condition had been investigated in
relations with other variables such as cognitive abilities, attitudinal variables, sociocultural
variables, and home-family factors (Kahle & Meece, 1994).
Cano and Cardelle-Ellawar (2008) found that the students’ belief in quick, effortless
learning mediated the influence of family variables on surface strategy, metacognitive
learning strategies and academic performance. The better the family’s intellectual climate, the
higher the students’ mature beliefs about learning, and consequently, their deep and
metacognitive strategies and academic performance.
Research on home-family variables such as ethnicity, socioeconomic status, and
parental education revealed that these variables mediates on the students’ belief in authority
and quick learning and students’ science achievement. Family background exerted its
regulative influence in science achievement in an indirect way through the availability of
economic capacity, the quality of home environment, parents’ educational and occupational
aspirations, and the quality of the schools attended.
In a longitudinal study, Trautwein and Ludtke (2007) examined the relationship between
epistemological beliefs, specifically the certainty of knowledge and school achievement and
44
the subject choice of college majors of German students. Results of the study showed that
certainty beliefs were found to be correlated significantly and negatively with family socio-
economic status (r = -.09, p < .05), cultural capital (r = -.17, p < .05), cognitive abilities (r =
-.18, p < .05), and final school grades (r = -.23, p < .05). There was no significant correlation
between certainty beliefs and age or gender. The researchers further examined the role of
certainty beliefs as predictors of school achievement using structural equation modeling. The
family socio-economic status was specified to be mediating the influence of cognitive
abilities and certainty beliefs on final school grades. Family background, cultural capital,
cognitive abilities, gender, age, were used as the predictors of certainty beliefs and final
school grade as an indicator of achievement.
School Location
Students’ environment including the geographical location of the school, its cultural
facet and as well as the authoritative influence has been always been illustrated in the past
studies to be one of the learners’ determining factors associated with their performance.
School environment was described as the social atmosphere in which learning takes place
(Johnson & McClure, 2004). There is an increasing recognition about the importance of the
classroom environments in education research over the past 30 years in terms of
conceptualization, assessment, and investigation of students’ perceptions of the learning
environments at elementary, secondary and also higher education levels (Alridge, Fraser, &
Huang, 1999).
Lederman and Druger (1985) investigated the Biology classroom characteristics
45
affecting the students’ epistemological views and academic achievement in science. They
specifically focused on students’ views related to the developing nature of science. They
found that the significant relationship between students’ epistemological views and
performance in Biology were affected by classroom characteristics such as a supportive
environment, openness to students’ thoughts and questions, students-teacher interaction, an
environment relating school science subjects to everyday life, using a variety of instructional
media and use of inquiry-oriented questions during instruction, characteristics which were
equally found in both rural and urban settings. The researchers concluded that instructional
climate and teachers’ approach affect students’ beliefs about the nature of knowledge.
In the Philippines, a clear example why majority of students located in rural areas
perform poorly is that the schools where they are studying are most of the time inadequately
providing them with enough resources that would enhance their performance in school. The
lack of reading centers or establishments such as public libraries and lack of access to
internet often hold the students from being open to the acquisition of more knowledge thus
having poor performance. The wide range of differences between urban regions and rural
regions, between developed regions and developing regions have been discussed in view of
teacher opinion (Pei, 2004), sub-cultures (Teng, 2003) and economy development (Zhu,
2003).
In his study, Cheng, R. C. (1994) hypothesized a model in which epistemological
beliefs and learning environment in both urban and rural locations were assumed to influence
academic achievement directly, and furthermore epistemological beliefs influence academic
46
achievement indirectly through the effect of learning environment such as those induced by
teachers and the cultural characteristics of the school. Results of the study showed that both
epistemological beliefs and learning environment influenced students’ achievement directly.
Epistemological beliefs also influenced achievement indirectly by the moderating effect of
the learning environment of students. It was found that those students in the urban setting had
more positive academic achievement relative to their beliefs in quick and simple learning and
certainty of knowledge. This strong relationship was found to have been induced by the
indirect or mediating effect of school’s related factors to the beliefs of the students.
The teachers' belief about learning may also be one of the determinants of how
students have mental construct or their own epistemological beliefs. The geographical area
where teachers teach has been reported to be an important factor influencing students’
beliefs. The institutional context where teachers work has an effect on the educational beliefs
of teachers as well (Lim & Torr, 2007). Martin and Yin (1999) examined the mediating
influence of classroom management beliefs and found that rural teachers adapted to a
significantly higher extent of teacher induced interventionist instructional approach, while
urban teachers adopted significantly more student based interventionist approach. A hidden
variable in the former study is whether schools are positioned in a developed or developing
province. In their study, Nisbet and Grimbeek (2004) argued that school location and the
related school size is expected to have a mediating effect on primary teachers’ beliefs and
practices and therefore may influence how their students believe in the acquisition of
knowledge.
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Information and Communication Technology
Research has suggested that the epistemological beliefs of learners may influence the
learning processes that students choose to engage in (Hofer, 2001), which have been referred
to as acts of self-regulated learning. In the online learning environment, the development of
self-regulated learning skills is particularly important as the online learning environment has
been indicated as requiring students to employ more self-regulated learning skills (Fisher &
Baird, 2005). Tsai and Chuang (2005) explored the association between epistemological
beliefs and the meta-cognitive learning preferences among learners in the online
environment. In finding a significant association, they suggest that educators must be aware
of the epistemological beliefs of learners in order to successfully implement self-regulated
learning activities in the online learning environment. The study presented an examination of
the relationship between epistemological beliefs and self-regulated learning skills associated
with academic achievement as mediated by their knowledge of manipulating online lessons.
In another study, Pieschl et al. (2007) investigated the relationship between the
epistemological beliefs, self-regulated learning behaviors and performance among biology
students learning the topic of genetics with hypertext. They found that more sophisticated or
more constructivist-oriented epistemological beliefs were significantly associated with
students being able to process more information as well as being associated with more
positive learning outcomes. The results of this study indicate that epistemological beliefs and
self-regulated learning skills among online learners may be associated with each other and
each in turn associated with academic achievement. The positive relationship among these
variables was significantly moderated by their knowledge in manipulating online lessons.
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Moderating Variables and Learning Styles
Gender
Gender has been found to exert its moderating effect on the students’ learning styles.
Males tend to be more kinesthetic and tactual, and if they have third modality strength, it is
often visual. Males also need more mobility in a more informal environment than females
(Dunn & Griggs, 1995). They are more non-conforming and peer motivated than females.
Females tend to be relatively conforming and either self-, parent-, or teacher-motivated
(Dunn & Griggs, 1995). Females, more than males, tend to be auditory, authority-oriented,
and better able to sit passively in conventional classroom desks and chairs. Females also tend
to need significantly more quietness while learning (Pizzo et al, 1990), are more self-
motivated and conform more than males.
Witkin et al. (1977) study on cognitive learning styles found a potential role of
gender as a moderating aspect of learning style – field dependence and field independence
while Logan & Thomas (2002) found gender in learning styles among distance education
students undertaking computing has been a potential demonstrator in the variation of learning
styles among male and female students.
The study by Philbin et al. (1995) includes findings of a significant mediation in the
learning styles of men and women surveyed. In the study, women were found to
predominantly correspond to the Diverger/Converger group while men preferred the
Assimilator style.
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Age
Learning styles may change as individuals grow older (Dunn & Griggs, 1995). Some
individuals change uniquely and then some do not change at all as they get older.
Individuals’ sociological, emotional and physiological preferences change as a person gets
older. Sociological preferences could be an individual’s choice whether to learn alone or with
a group. Emotional preferences can include motivation which fluctuates from day to day,
class to class, and teacher to teacher. If a student is interested in a topic and the presenter’s
teaching style matches the student’s learning style, then the student’s motivation will be
greater. Sound preferences, temperature preferences, and seating preferences also change as
individuals get older (Dunn & Griggs, 1995). Clearly the intervening effect of age is clearly
seen as the students get more mature in school.
While learning style has been defined as a consistent pattern of behavior, it appears
that it changes with age and experience. Researches of Daughenbaugh (1985) and McCarthy
(1985), showed that students’ preference for learning and teaching styles were found
moderated by both age group and gender. Further, Dorsey and Pierson (1984) found that age
influenced the relationship between the students’ learning styles and their academic
performance.
In the study exploring the learning styles of Business students (Australian and
NESBs) to determine if the relationship between their performance in school and their
preferred learning orientations is affected by cross-cultural and other demographic
differences such as gender and age, Teo (2002) pointed out that the learning styles of the
Australian Business students were related to their academic performance. Moreover, students
50
who were less than 20 years scored lowest in their Pragmatist learning orientation. Matured
students (41-50 years age group) scored highest in their learning interest when compared
with the younger age groups.
School Location
There are some studies in the past particularly focused on the relationship between
learning environment and students’ learning approaches. Campbell et al. (1996) found that there
is a relationship between students’ learning approaches, teacher’s instructional processes and
form of assessment. Similarly, Dart and his colleagues (2000) conducted a study investigating the
relationship between learning environments and students’ learning approaches and academic
performance. Results of their study found that relationship between students’ academic
achievement and learning approaches was significantly moderated by the effect exerted by the
third variable, school location.
Another line of research in the classroom environment literature particularly focused the
relationship between learning environment, learning approaches and academic performance of
the students. It was stated that students’ perceptions of the learning approach that influenced their
performance, was necessarily mediated by the learning environment (Enwistle, 1991). Results of
study showed that when students perceived their course unit to be generally supportive and
encouraging of their learning, sensitive to students’ mental processing in learning, concerned
with their capacity to learn independently, and supportive of study practices expected of higher
education, they tended to use deeper approaches to study which in turn pushes their academic
performance positively. The perception of students related to the learning environment directly
determines approach of learning and academic performance; whether they tackle it in a
51
superficial way or strive for meaning (Eley, 1992; Enwistle & Tait, 1990; Ramsden, 1979; 1990;
Trigwell & Prosser,1991).
52
METHODOLOGY
Theoretical and Conceptual Framework
This study is anchored on Schommer-Aikins (2004) embedded theory of
epistemological beliefs where five factors of personal epistemology would be analyzed in
conjunction with other cognitive and affective learner characteristics. In Schommer-Aikins’
early work (Schommer, 1990), she suggested that personal epistemology is comprised of five
distinct factors that exist on continua. Stated from their naïve pole, these factors were: simple
knowledge, certain knowledge, innate ability, quick learning, and omniscient authority.
Briefly, the simple knowledge continuum stemmed from the belief that all knowledge is
rudimentary to the belief that knowledge was complex. Beliefs in certain knowledge range
from those who hold that all knowledge is concrete and certain to those who acknowledge
the dynamic and changing nature of knowledge. Beliefs about learning ability range from the
view that such ability is innate and unchanging to one that acknowledged the benefits of hard
work and self-improvement. Those who scored towards the naïve pole of quick knowledge
thionk that learning happens quickly or not at all, while learners with more sophisticated
beliefs acknowledge that some topics take time and effort. Finally, the omniscient authority
factor, distinct from the previous beliefs regarding knowledge and learning, deals with an
individual’s faith in authority figures, ranging from complete trust to educated skepticism.
Schommer-Aikins (Schommer, 1990) hypothesized that individuals’ positions on
these factors are relatively independent, and that more naïve beliefs predict poorer academic
performance, particularly on those tasks involving complex or nuanced topics (e.g. writing
essays, examining issues from multiple perspectives). She also believed that these
53
epistemological beliefs are domain-general.
In recent publication, Schommer-Aikins (2004) advocated an embedded theory of
epistemological beliefs where she called for more integrative investigations into the relations
between epistemological beliefs and other constructs of interest to educational psychologists.
She emphasized the need for an embedded systemic model of epistemological beliefs, that is,
a model that includes many other aspects of cognition and affect, comes from the assumption
that epistemological beliefs do not function in a vacuum (Greene et al., 2003). As such, it is
important to test personal epistemology's influence in the presence of other constructs that
are important to learning such as self-efficacy, strategy use and motivation (Hofer, 2005).
An extensive body of research addresses beliefs about knowledge and learning or
epistemological beliefs (Elby, 2001; Roth and Roychoudury, 1997; Hewson 1985). These
studies found that students' epistemological beliefs about scientific knowledge and learning
have important influence on their approach to learning.
The recommendations and research of others (Hoffer, 2005; 1999; Paulsen &
Feldman, 2005; Schommer-Aikins, 2004) allow for the prediction of the interrelationship
between beliefs about knowledge and learning (epistemological beliefs) may have on
learning approaches/styles and classroom performance. How individuals view knowledge
and learning will logically seem to have an influence on their beliefs on how to engage on
academic tasks. Theories of personal epistemology suggest that students with simplistic or
naïve beliefs about knowledge may struggle with more nuanced academic subjects, thus,
affecting their academic performance (Muis, 2004).
As the students define their learning in accordance with their own beliefs, they
54
develop their own manner or style in acquiring knowledge. These students develop their
distinctive behavior which serves as an indicator or person’s mediation utilities and capacities
(Gregor, as cited by Leoveras, 2001). Together, the student’s personal epistemological beliefs
and learning styles shape the learner’s capacity to perceive and handle information and
interpret it in line with their own mental construct. In the light of this study, it is important
that a student understands himself in order to explore his inner self, his own perspectives and
his own assumptions about his experiences in and out of the classroom as his source of
knowledge.
Personal epistemological beliefs play an important role in one’s learning process. This
study tried to find out if the learner's beliefs mirror his own style of learning. For example, if
more sophisticated learners who construct their own meaning would have the tendency to
become independent in the learning process. On the other hand, those who held naïve beliefs
have high regard of authority and believe that the ability to learn is fixed at birth may have
the tendency to practice avoidant and dependent learning styles.
The modification in the relationship between the students’ learning styles and
epistemological beliefs and academic performance are perceived to be the effect of link
among biological, sociocultural and environmental elements (De Guzman, 2005; Ickens and
Layden, 1978). Age and gender are biological and social factors. School's location, ICT
accessibility, family income, parents’ educational background, parents’ occupation are
environmental factors. They were chosen as moderator variables between learning styles and
academic performance and between epistemological beliefs and academic performance.
This study was anchored on the assumptions that students' ways of conceiving and
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espousing knowledge (epistemological belief) and recognizing and meting out concepts and
experiences to learn (learning styles) correlate with their academic performance.
Consequently, this study was also conceptualized to find out whether learning styles and
epistemological beliefs would predict the academic performance of the students in Biology. It
also assumed that this learning style- academic performance and epistemological beliefs-
academic performance links are affected by moderation of the students’ age, gender, school's
location, ICT accessibility, monthly family income, parents’ educational attainment, and
parents’ occupation.
Learning styles and epistemological beliefs were the independent variables whereas
academic performance was the dependent variable. Students’ age, gender, school's location,
ICT accessibility, monthly family income, parents’ educational background, parents’
occupation were the moderator variables.
Figure 1 shows the hypothesized relationships between the independent variables (i.e.
learning styles and epistemological beliefs) and the dependent variable (i.e. academic
performance). It also presents age, gender, school's location, ICT accessibility, monthly
family income, parents’ educational background, parents’ occupation as moderator variables.
Independent Variables
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Dependent Variable
Figure 1. Diagram of the hypothesized relationships among independent, dependent and moderator variables
Operational Definition of Terms
Moderating Variables
LEARNING STYLES
DependentIndependentCollaborative
ParticipantAvoidant
Competitive
Academic Performance in Biology
Moderating variables
GenderAge
School’s LocationICT Accessibility
Monthly Family IncomeParents’ Educational
BackgroundParents’ Occupation
EPISTEMOLOGICAL BELIEFS
TypesNaïve
EmergentSophisticated
DimensionsCertainty of Knowledge
Simple KnowledgeInnate Ability
Omniscient AuthorityQuick Learning
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To better understand the research concepts, several terms in this study were
operationally defined.
Academic Performance refers to the final grade obtained by the students in Biology. The
following categorization was used:
Qualitative Description Range
High Academic Performance 88 and above
Average Academic Performance 80 - 87
Low Academic Performance below 80
Epistemological beliefs refer to how individuals come to know, the theories and beliefs they
have about knowing, and the manner in which such epistemological premises are part of and
an influence on cognitive processes of thinking and reasoning (Hofer & Pintrich, 1997).
Sophisticated Beliefs refer to the beliefs that knowledge is tentative, complex,
derived by reason, acquired gradually, and that the ability to learn can be changed.
Emergent Beliefs refer to the beliefs consisting of combined characteristics
found in sophisticated and naïve beliefs.
Naïve Beliefs refer to the beliefs that knowledge is absolute, simple, handed
down by authority, acquired quickly or not at all and that the ability to learn is fixed
at birth.
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Epistemological belief dimensions refer to the aspect of personal
epistemological belief that simultaneously occur in a more or less independent
fashion in a person’s belief of the nature, acquisition and processing of knowledge.
Schommer (1990) identified five of them namely:
Certainty of Knowledge ranges from knowledge is absolute to knowledge is
tentative.
Simple Knowledge ranges from knowledge is organized as isolated bits and
pieces to knowledge is organized as highly interwoven concepts.
Omniscient Authority ranges from knowledge is handed down by authority
to knowledge is derived through reason.
Innate Ability ranges from the ability to learn is fixed at birth to the ability to
learning can be changed.
Quick Learning ranges from knowledge is acquired quickly or not-at-all to
knowledge is acquired gradually.
Epistemological Belief Inventory (EBI) is a research instrument used to
determine respondents’ epistemological beliefs in Biology. The EBI is scored on a 5-
point Likert scale from 1 (strongly disagree) to 5 (strongly agree). Higher scores
indicate a person is more naïve.
Based upon the scoring range from 32-160 points, students are categorized to
be sophisticated when he gains 32-64 points, emergent with 65-112 points and naïve
with 113-160 points. Statements towards sophisticated beliefs are scored reversely.
59
For statements leaning towards naive epistemological beliefs, the following
scoring were used:
Strongly Agree – 5
Moderately Agree – 4
Undecided – 3
Moderately Disagree – 2
Strongly Disagree – 1
On the other hand, reverse scoring was applied to statements gearing towards
sophisticated epistemological beliefs:
Strongly Agree – 1
Moderately Agree – 2
Undecided – 3
Moderately Disagree – 4
Strongly Disagree – 5
Learning Styles refer to how the students learn best. In this study, the Grasha-Reichmann
learning style was used. It categorized student’s learning styles into six categories, namely:
independent, avoidant, collaborative, dependent, participative and competitive. As an
instrument, it uses 60 questions with 10 equally distributed questions per style. These are
60
measured through a 5-point disagree-agree scale, agreement being high. Each dimension of
learning styles has 10 questions where the students can obtain scores ranging from 10 – 50
points. This, in turn, identifies each student with one predominantly style depending on the
dimension where he scored high. The following are the descriptions of each learning style
(Velasquez, 2007):
Independent refers to the student’s learning style that prefers to work alone
and require a little direction from the teacher. Independent students are curious and
confident learners. They prefer to work on their own in individual activities.
Dependent refers to the student’s learning style whereby students who have
this style see the teacher as a source of information, want to be told what to do, and
learn only what is required.
Collaborative refers to the learning styles where students work well with
others and enjoy cooperative learning and working in groups. They cooperate with
teachers and like to work with others.
Avoidant refers to the learning style of the students who tend to be at the
lower end of the grade distribution; they tend to have high absenteeism and take a
little responsibility on their learning.
Competitive refers to the learning style of the students where students see the
classroom as a win-lose situation in which they must win. Students who have this
learning style enjoy competitive activities.
Participative refers to the learning style of students who show eagerness to
learn course content, enjoy learning, and take responsibility on their own learning.
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Range and Description of the Mean refers to the scale that indicates the level of agreement
for both the students’ learning styles and epistemological beliefs. It consists of numerical
values and qualitative descriptions.
In addition to this, because some statements under the students’ epistemological
beliefs were oriented towards sophisticated pole, reverse range and description of the mean
was utilized. The scale below shows the reverse range and description of the mean:
Moderator Variables refer to the third variable that modifies the original relationship
between the independent and the dependent variables. These include the respondents’ socio-
demographic characteristics such as age, gender, school's location, ICT accessibility, family
income, parents’ educational attainment, and parents’ occupation.
Age refers to the specific age of the respondents at the time they took Biology
(SY 2009-2010).
Gender refers to whether the respondent is male or female.
Information and Communication Technology (ICT) Accessibility refers to
students’ access to information and communication technology such as internet,
educational electronic gadgets, reading centers and libraries.
Monthly Family Income refers to the monthly total gross income from all
1.00 - 1.79 Strongly Disagree1.80 - 2.59 Moderately Disagree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Agree4.20 - 5.00 Strongly Agree
1.00 - 1.79 Strongly Agree1.80 - 2.59 Moderately Agree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Disagree4.20 - 5.00 Strongly Disagree
62
sources of the family. It was categorized as “low family income” if it falls below and
within the mean and “high family income” if above the mean.
Parents’ Educational Attainment refers to the highest academic achievement
attained by the parents of the respondents.
Parents’ Occupation refers to the job, work or occupation of the respondents’
parents. Parents’ occupation may be categorized as blue collar or white collar jobs.
White collar job refers to those where activities are performed using
managerial, mental or professional skills like teaching, nursing, engineering,
architecture.
Blue collar job refers to those people’s occupations involving manual,
muscular application of unskilled, semi-skilled or highly skilled labor like
farmer, barber, baker, driver, utility worker and laborer.
Non-earners refer to occupation which has no wage or salary like
retired employee and homemaking.
School's Location refers to school's area classification as to rural or urban. In the
context of this study, urban schools are those nearer to the town proper where there
are several places that serve as sources of additional information for the respondents
such as internet cafe, municipal library and reading center. On the other hand, rural
schools are those located at least 8 kilometers away from the town proper and those
which are deemed the opposite of the other classification.
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Research Design
This study used an explanatory research design employing multiple regression
analysis to explore the potential influence of learning styles and epistemological beliefs as
predictors of Biology performance of students in the secondary schools of CLSU. It also used
descriptive-correlational analysis to describe the interrelationship of learning styles,
epistemological beliefs and academic performance of the students. Profiles of the
respondents' academic performance, learning styles and epistemological beliefs were
determined. The researcher specifically investigated the correlation between academic
performance and (a) learning styles and (b) epistemological belief of the respondents.
Moreover, the researcher determined whether or not the predictability of academic
achievement from learning styles and epistemological belief was improved when age, sex,
school’s location, ICT accessibility, monthly family income, parents’ educational
background and parents’ occupation were considered.
The Sample
The respondents were students from the three laboratory high schools of CLSU
(ULHS-Bibiclat, ULHS-Palusapis and ULHS-Pinili), the Agricultural Science and
Technology School and the University Science High School. The respondents took their
Biology subject during the S.Y. 2009-2010.
A total of 147 students who were randomly chosen from the Biology classes of the
five high schools for SY 2009-2010 were requested to participate in the survey. Random
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sampling was used to identify the respondents and to gather the needed data. Using the
formula of population sampling as cited by De Guzman (2005), n = N / 1 + Ne2, where n is
the total sample, N is the total population and e represents margin of error (5%), the
researcher figured out the appropriate percentage from the total number of population in each
school. Based on the formula, from the total population of 240 Biology students from the
five high schools of CLSU, a total of 147 students or 61% was identified. The distribution of
the respondents by school location is found in Table 1.
Table 1. Distribution of respondents by school location
School / LocationTotal population
per schoolSample size
Rural
ULHS - Bibiclat 49 30
ULHS - Palusapis 50 31
ULHS - Pinili 44 27
Urban
ASTS 25 15
USHS 72 44
Total 240 147
Instrumentation
This study used a questionnaire divided into three parts. Part I comprises the socio-
demographic characteristics of the respondents inquiring the age, gender, school's location,
ICT accessibility, monthly family income, parents’ educational background, parents’
65
occupation and the respondent’s final grade in Biology. Part II constituted statements
pertaining to the personal epistemological beliefs in Biology of the respondents. Part III, on
the other hand, includes the list of statements that identifies the learning styles of the
respondents in Biology.
Sources of data for this study came from: (a) Student's Permanent Record, (b)
Student’s responses to Grasha-Reichmann Learning Style Inventory and (c) Students’
responses to Epistemological Beliefs Inventory (adapted from Schraw et al, 2002).
Student's Permanent Record
To authenticate the grades indicated by the respondents in the survey questionnaire,
the researcher requested the transcript of records from the registrar of each school. The
students’ permanent record is an official document which contains information regarding the
student's academic performance during the school year. This was used to validate the
respondents’ final grade in Biology. The final grade in Biology was used as a measure of the
respondent's academic performance.
Socio-Demographic Characteristics
The first part of the research instrument sought information regarding the
respondents’ socio-demographic characteristics. Data on age, gender, school’s location, ICT
capability, parents’ educational background, monthly family income and parents’ occupation
were included. These data were treated as moderating variables.
66
Grasha-Reichmann Learning Style Inventory (adapted from Grasha-Reichmann et al, 1996)
The Learning Styles Inventory of Grasha and Reichmann (Appendix A) was divided
into six categories namely, avoidant, competitive, and dependent which were thought to be
negative; and participative, collaborative and independent which were thought to be positive.
The Grasha-Reichmann Learning Style Inventory is composed of 60 items which reflect the
respondents' learning styles as to negative or positive learning styles. The 60 statements were
scattered throughout so that the respondents would not have any clue or pattern that would
easily identify them on a certain learning style.
To describe the level of agreement of the respondents in this inventory, the range and
description of mean for each description was used. It is described as follows:
Epistemological Belief Inventory (adapted from Schraw et al, 2002)
To measure the epistemological beliefs of the respondents, the Epistemic Belief
Inventory (Appendix A) developed by Schraw, et al (2002) was utilized. This inventory, the
32-item Epistemic Beliefs Inventory, was used to measure five different factors regarding the
nature of knowledge and the origins of individuals' abilities. The five factors were originally
developed by Bendixen, et al. (1998) and based on earlier work of Schommer (1990). The
factors include certain knowledge (i.e., absolute knowledge exists and will eventually be
known), simple knowledge (i.e., knowledge consists of discrete facts), omniscient authority
1.00 - 1.79 Strongly Disagree1.80 - 2.59 Moderately Disagree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Agree4.20 - 5.00 Strongly Agree
67
(i.e., authorities have access to otherwise inaccessible knowledge), quick learning (i.e.,
learning occurs in a quick or not-at-all fashion), and innate ability (i.e., the ability to acquire
knowledge is innate).
In order to fit in this study, the researcher reworded and/or added words or phrases
such as “in biology class”, “of the biology teacher”, “of concepts in biology” to specifically
cater to epistemological beliefs of the respondents in Biology subject. Statements leaning
towards naïve epistemological beliefs were scored as Strongly Agree – 5, Moderately Agree
– 4, Undecided – 3, Moderately disagree – 2, Strongly disagree – 1. On the other hand, the
following reverse scoring were applied to statements gearing towards sophisticated
epistemological beliefs: Strongly Agree – 1, Moderately Agree – 2, Undecided – 3,
Moderately disagree – 4, Strongly disagree – 5. Higher scores on this instrument indicated
naïve epistemological beliefs while lower scores indicated sophisticated epistemological
beliefs. The reported internal consistency of the instrument was α = .83 (Schraw et al, 2002).
The students’ intensity of agreement and disagreement regarding each dimension of
epistemological beliefs was described using the following range and description of means:
Due to orientation towards sophisticated pole, some statements under the students’
epistemological beliefs used reverse range and description of the mean. The scale below
shows the reverse range and description of the mean:
1.00 - 1.79 Strongly Disagree1.80 - 2.59 Moderately Disagree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Agree4.20 - 5.00 Strongly Agree
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Data Gathering Procedure
Before the researcher began collecting data from the respondents, approval was first
sought from the school principals of the five high schools of CLSU to ask for their assistance
regarding this study.
The respondents’ final grade in Biology was retrieved from the registrars of the five
high schools of CLSU. To identify the students’ epistemological beliefs, learning styles and
some socio-demographic profiles, a questionnaire was prepared which included the Grasha-
Reichmann Learning Style Inventory, and Epistemological Belief Inventory developed by
Schraw et al. (2002).
Before administering the questionnaires, the researcher oriented the students on the
purpose of the study. The non-academic, non-evaluative nature of the test was emphasized to
encourage the students to accomplish the questionnaires, objectively. They were also assured
that the data they provided will be used solely for research purposes. Moreover, the students
were reminded to feel free to approach the researcher should they need help in any part of the
tests. The respondents were given sufficient time to answer the test instrument. If they tried
to submit the survey questionnaire with unanswered items, they were prompted to go back
and complete missed items.
1.00 - 1.79 Strongly Agree1.80 - 2.59 Moderately Agree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Disagree4.20 - 5.00 Strongly Disagree
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Statistical Analyses
Answers to the problems for this descriptive correlational study were provided
through different statistical techniques. Level of confidence was set at 0.05.
1. A profile of the students' epistemological beliefs, learning styles and socio-
demographic characteristics in terms of age, gender, school's location, ICT
accessibility, monthly family income, parents’ educational background, parents’
occupation was determined using frequencies and percentages.
2. A profile of the respondents' academic performance in Biology was obtained with the
use of frequencies, percentages, mean and standard deviation.
3. Pearson Product-Moment Coefficient of Correlation (Pearson r) was used to
determine the relationship between: (a) epistemological beliefs and academic
performance; (b) learning styles and academic performance; and (c) epistemological
beliefs and learning styles.
4. Multiple regression analysis was used in order to find out if learning styles and
epistemological beliefs would predict the academic performance of the students in
Biology.
5. Hierarchical regression analysis was used to find out whether or not age, gender,
school's location, ICT accessibility, monthly family income, parents’ educational
background, parents’ occupation significantly moderate the relationship between (a)
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epistemological beliefs and academic performance and (b) learning styles and
academic performance.
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RESULTS AND DISCUSSION
This chapter presents the findings regarding the relationship of the respondents'
epistemological beliefs and learning styles as the independent variables and their consequent
relationship on the academic performance of the students in Biology. This chapter also
presents the possible predictors of academic performance as a result of regression analysis. In
addition, this chapter also shows the impact of socio-demographic characteristics of the
respondents such as age, gender, school location, ICT accessibility, parents' educational
background and parents' occupation referred to as moderating variables on the relationship of
epistemological beliefs and learning styles to the academic performance of students. The
results are discussed in sequential order as they appear in the objectives of this study.
Learning Styles of the Respondents
Learning style describes the process learners used to sort and process information.
Learning style is an important factor in several areas including students’ academic
achievement, how students learn and teachers teach, and student-teacher interaction (Witkin,
et al. 1977).
Results revealed that respondents were more collaborative than competitive, more de-
pendent than independent and more participant than avoidant. This result is further supported
by the percentage of respondents that scored high, moderate and low in the learning style in-
72
ventory (Appendix D). Figure 2 shows the distribution of learning styles among the respon-
dents.
Collaborative Learning Style
Table 2a shows the level of agreement of the respondents pertaining to collaborative
statements as the respondents’ most dominant learning style. The collaborative learning style
had an overall of 3.89 which means moderately agree. The students strongly agreed that
activities of different sorts in Biology class and learning through cooperative effort with their
teachers and classmates were the most effective way to learn Biology. However, they just
moderately agreed that they enjoy discussing their ideas about course contents with others.
Most of them enjoy hearing what others think about the issues raised in class. Students
believe that learning the material was a cooperative effort between students and teachers.
These students agreed that working with others in class activities was something they
Figure 2. Distribution of respondents’ learning style
73
enjoyed doing; that they should be encouraged to share more of their ideas with each other.
Moreover, the students believe that an important part of studying Biology is learning to get
along with other people.
Table 2a. Responses of the students toward collaborative learning styles
Collaborative Statement Description
Working with other students on class activities is something I enjoy doing in my Biology class.
4.24Strongly
Agree
I enjoy discussing my ideas about Biology with other students.
3.54 Moderately Agree
I enjoy hearing what other students think about issues raised in Biology class.
3.62 Moderately Agree
Students should be encouraged to share more of their ideas with each other in Biology class.
3.99 Moderately Agree
I like to study for tests in Biology with other students. 3.62 Moderately Agree
Biology classes make me feel like part of a team where people help each other learn.
4.09 Moderately Agree
An important part of studying Biology is learning to get along with other people.
3.87 Moderately Agree
Learning the lessons in Biology is a cooperative effort between students and teachers.
4.20 Strongly Agree
I am willing to help other students out when they do not understand something in Biology.
3.82 Moderately Agree
I enjoy participating in small group activities during Biology class.
3.90 Moderately Agree
Overall 3.89
Moderately Agree
Legend:
1.00 - 1.79 Strongly Disagree1.80 - 2.59 Moderately Disagree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Agree4.20 - 5.00 Strongly Agree
74
This result implies that most of the students enjoy working in cooperation with their
peers. They usually function in the classroom by sharing their ideas, views and talents with
others. These students prefer group discussions or group activities where they can freely
interact with others while learning. Students who have collaborative learning styles are
willing to help other students when they do not understand something in Biology.
The dominance of collaborative learning style among the students may be attributed
to the kind of teaching strategy the teachers use in their classroom. The thrust of Philippine
education today has been geared towards student-centered goal where students are
encouraged to create their own learning experiences via different teaching strategies among
which is the cooperative learning approach. In cooperative learning approach, the teachers
incorporate the idea that the best learning occurs when students are actively engaged in the
learning process and working in collaboration with other students to accomplish a shared
goal. Kagan (1994) contends that when cooperative learning is incorporated into the
classroom, research suggests students learn with greater depth and complexity while enjoying
the experience even more. Students who are asked to work together also tend to be less
intimidated by the task and will work at the task with greater intensity for time. In addition,
75
Kain (2003) explained that in learner-centered approaches, the construction of knowledge is
shared, and learning is achieved through learners’ engagement with various activities.
In her study about the different learning styles of selected students of Munoz National
High School, Velasquez (2007) also found that the most dominant learning style in the three
student groupings (Mathematics, Science and English) was collaborative. Majority of the
respondents were found to have inclination for group discussions, group activities and group
dynamics.
Participant Learning Style
The next most dominant learning style is participant which has a of 3.82 which
means respondents moderately agreed on almost all the statements pertaining to this learning
preference. The respective means and descriptions of the students’ responses are presented in
Table 2b.
Participative students are characterized by the willingness to take responsibilities of
self-learning. The always look forward to partaking in every class activity and can be seen
with enthusiasm to do those which are required and optional requirements in class. They are
the most obedient students in class because they follow whatever the teacher tells to do. They
love to show what they got and always have the willingness to accomplish everything with
their peers, classmates and teachers as well.
Davis et al. (1990) maintain that the use of cooperative learning consequently
promotes participative approach among the students and in turn helps students clarify
76
concepts and ideas through discussion and debate. Because the level of discussion within
groups is significantly greater than in instructor led discussions, students receive immediate
feedback, thus advancing the level of discussion. It is through this process of interacting with
Table 2b. Responses of students toward participant learning styles
Participant Statement Description
I do whatever is asked of me to learn in my Biology class.
3.74 Moderately Agree
I find that Biology class is worth attending. 3.74 Moderately Agree
I get more out of going to Biology class than staying at home. 3.49 Moderately Agree
It is my responsibility to get as much as I can out of my Biology class. 3.82 Moderately Agree
Classroom activities in Biology class are interesting.4.18 Strongly Agree
I try to participate as much as I can in all activities in Biology.
4.24 Strongly Agree
I do all assignments in Biology well whether or not I think they are interesting.
4.03 Moderately Agree
I typically complete assignments in Biology before their deadlines.
3.84 Moderately Agree
I complete required assignments in Biology as well as those that are optional.
3.84 Moderately Agree
In my Biology class, I often sit toward the front of the room.
3.31 Undecided
Overall 3.82 Moderately Agree
Legend:
students of differing viewpoints that cognitive growth is stimulated. Emphasis is placed on
1.00 - 1.79 Strongly Disagree1.80 - 2.59 Moderately Disagree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Agree4.20 - 5.00 Strongly Agree
77
learning how to cooperate in order to find the best possible solution to a problem. According
to the constructivist approach, when students formulate their own solutions in this manner,
they are truly thinking critically (Davis et al., 1990).
The students strongly agree in the statements stating that activities in Biology class
are interesting and most of them try to participate as much as they can in all the activities in
Biology. They moderately agreed on statements that they would do whatever is asked of
them, that the Biology class is worth attending, that they get more information in the Biology
class, that they feel that it is their responsibility to get as much information in their Biology
class, that they do assignments in the Biology class whether they think they are interesting or
not, and that they complete assignments whether they are optional or required. They were
undecided, however, whether they would want to sit toward the front of the room.
As earlier stated, most respondents in this study have high regards with the authority
of the teacher in the classroom. In a setting where the teacher’s authority is prevalent,
students are expected to obey or abide by the teachers. This may have exerted influence on
the students to become more participative on almost every activity in the classroom.
Santos (2008) reported in his study among 120 high school students taking up
Biology that students tended to hold positive learning styles such as participative and
independent learning styles when exposed to activities that address these types of learning
styles. These learning styles had particular positive influence on the high academic
achievement of the respondents.
Dependent Learning Style
78
Statements under dependent learning styles were shown in Table 2c. The means and
their corresponding descriptions for each statement were also presented in the same table.
The overall of the statements under dependent learning style is 3.77 which is moderately
agree.
Table 2c. Responses of the students toward dependent learning styles
Dependent Statement Description
I want my Biology teacher to state exactly what he expects from the students.
3.72 Moderately Agree
I rely on my Biology teacher to tell me what is important for me to learn.
3.31 Undecided
I want clear and detailed instructions in Biology on how to complete assignments.
4.24 Strongly Agree
I complete assignments in Biology exactly the way my Biology teacher tells me to do them.
3.82 Moderately Agree
Trying to decide what to study or how to do assignments in Biology makes me uncomfortable.
2.94 Undecided
Students should be more closely supervised by Biology teachers in doing Biology projects.
3.96 Moderately Agree
My notes contain almost everything the teacher said in my Biology class.
3.77 Moderately Agree
I prefer Biology lessons that are highly organized. 3.88 Moderately Agree
Students should be told exactly what topics are to be covered on Biology exams.
3.96 Moderately Agree
I want Biology teachers to have outlines or notes on the board.
4.06 Moderately Agree
Overall 3.77 Moderately
79
Agree
Legend:
The students strongly agreed that Biology teachers should have clear and well-
explained instructions in doing their assignments or activities in the class. The students
moderately agreed on the statements stating that they want their teacher to exactly state what
to expect from the students, that they rely much on whatever their teachers say, that they
accomplish their requirements exactly the way their teacher wants them, that they wanted
close supervision from their teachers whenever there is a class activity, that their notes
contain exactly almost everything the teacher said, that they want highly organized lessons,
that they should be told of what topics are to be covered in Biology and they wanted notes or
outlines from their teachers. They were undecided, however, when asked if they rely heavily
on their Biology teacher regarding the most important concepts that students should learn in
class.
The cultural perspective on the belief of the authority of the teachers may be pointed
as one of the many attributing factors why students become dependent. The relative high
percentage of respondents in this study who have this kind of learning style suggests that
many students heavily rely on their teachers with regard to learning Biology.
In a study made by Witkin et al. (1977) about the pre-service teacher of agriculture
education, they found that individuals who prefer a field-dependent learning style tend to per-
1.00 - 1.79 Strongly Disagree1.80 - 2.59 Moderately Disagree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Agree4.20 - 5.00 Strongly Agree
80
ceive globally, have more difficult time solving problems, are more attuned to their social en-
vironment, learn better when concepts are humanized, and tend to favor a “spectator ap-
proach” to learning which means they rely on their teacher and classmates as to what’s going
to happen inside the class. Additionally, individuals preferring a field-dependent learning
style have been found to be more extrinsically motivated and learn better when organization
and structure are provided by the teacher.
Independent Learning Style
Independent learning style is characterized by autonomy trait from the students who
work alone and require a little direction from the teacher. In this study, the overall for
independent learning style is 3.48 which is described as moderately agreed. The overall and
descriptions of statement under independent learning style are presented in Table 2d.
Table 2d. Responses of students toward independent learning styles
Independent Statement Description
I prefer to work by myself on assignments in my Biology class.
3.64 Moderately Agree
My ideas about Biology lessons often are as good as those in the textbook.
3.20 Undecided
I study what is important to me and not always what my Biology teacher says is important.
3.29 Undecided
I learn a lot of Biology on my own. 2.69 Undecided
I feel very confident about my ability to learn on my own in Biology.
3.51 Moderately Agree
I like to develop my own ideas about Biology lesson. 3.81 Moderately Agree
81
I have my own ideas about how Biology classes should be run.
3.22 Undecided
If I like a topic in Biology, I try to find out more about it on my own.
4.02 Moderately Agree
I prefer to work on class projects and assignments in Biology by myself.
3.59 Moderately Agree
When I don't understand something in Biology, I first try to figure it out for myself.
3.79Moderately Agree
Overall 3.48 Moderately Agree
Legend
Respondents
moderately agreed to statements about their confidence and their ability in learning ideas in
Biology. They also expressed their agreement towards learning concepts, making their own
projects and assignments, and figuring unclear ideas in Biology on their own. On the other
hand, they were undecided whether their ideas are as good as those in Biology textbooks and
about having their own idea on how a Biology class should be run. They also cast doubt on
their ability to seek information from other sources rather than from their teacher.
Independent students are curious and confident learners. Often, students with this type
of learning style find themselves understanding things on their own whenever possible and
would just turn to teachers in time for confirmation. Understanding the theory of
constructivism which also serves as guiding principle of Philippine education today may give
light to the level of agreement of the respondents concerning independent learning style.
Piaget's theory of constructivist learning has wide range impact on learning
1.00 - 1.79 Strongly Disagree1.80 - 2.59 Moderately Disagree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Agree4.20 - 5.00 Strongly Agree
82
theories and teaching methods in education and is an underlying theme of many education
reform movements today (Panitz, 1996). This principle exercised in most schools in the
Philippines may have influenced the development of student autonomy in learning. This may
have provided the students a freedom for expressing their own ability and skills inside the
classroom.
Boekaerts (1998) wrote that over the last decade, concern about formal education fos-
tering independent learning and its outcomes has been prevalent in Europe, America and
other parts of the world. Independent learning has been one of the approaches explored by
national governments and educators as a means of improving educational outcomes.
Competitive Learning Style
In competitive learning style, students learn in order to perform better than their peers
and to receive recognition for their academic accomplishments. It provides the students a
healthy academic competition among peers. In this study, the students’ overall was 3.89
for competitive learning style denoting that the respondents moderately agreed on the
statements leaning towards this learning method. The mean and description of each statement
under this learning style are presented in Table 2e.
The respondents moderately agreed on majority of the statements under competitive
learning style. Most of the respondents emphasized the significance of competition or
opposition as an integral part of their learning system. They agreed that to be able to perform
83
well in the class, students must be aggressive, be ahead of everyone in terms of class
activities, monitor their and their classmates’ own performance for comparison and like to be
recognized often by the teacher in Biology class. In addition, they like to solve problems or
answer questions in Biology before anybody else, indicating that competition is an integral
part of learning. They were undecided, on the other hand on the idea of directly competing
with others to get good grades and attention of their Biology teacher or to step on others toes
just to be on top.
Table 2e. Responses of students toward competitive learning styles
Competitive Statement Description
To do well, it is necessary to compete with other students for my Biology teacher’s attention. 3.03 Undecided
It is necessary to compete with other students to get a good grade in Biology class.
3.36 Undecided
In Biology class, I must compete with other students to get my ideas across.
3.21 Undecided
Students have to be aggressive to do well in Biology class.
3.63 Moderately Agree
I like to solve problems or answer questions in Biology before anybody else can.
3.69 Moderately Agree
To get ahead in Biology class, it is necessary to step on the toes of other students.
3.00 Undecided
Being one of the best students in my Biology class is very important to me.
4.10 Moderately Agree
To stand out in my Biology class, I complete assignments better than other students.
3.56 Moderately Agree
I like to know how well other students are doing on exams and assignments in Biology.
3.93 Moderately Agree
84
I want my Biology teacher to give me more recognition for the good work I do.
3.69 Moderately Agree
Overall
3.52 Moderately Agree
Legend:
This level of agreement among the respondents may be attributed to the nature of
human to compete with others most especially when one is highly motivated; has a feeling of
need to satisfy himself; and the environment he dwells in may have pushed him to compete
against others.
Mary (2010) maintained that although competition does not always belong in certain
areas of the academe, there were cases when a majority of students are highly
motivated, competition can lead to the most creative and innovative outcomes. In addition,
competition, like in the real world, is necessary to inspire people to produce more meaningful
advances. She argued that people are rewarded for the highest quality work, and if teachers
reward mediocre, above average, and below average results at the same rate, “they are only
doing their students a disservice, because the bar is lowered for everyone.” The idea is to
encourage and praise all participants, but in the end there can only be a few “winners.”
Tanner et al. (2003) contend that traditionally, educational settings have always taken
a competitive approach to learning, and many of those who have succeeded in school and
pursued careers in science excel in these environments. They further assumed that
1.00 - 1.79 Strongly Disagree1.80 - 2.59 Moderately Disagree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Agree4.20 - 5.00 Strongly Agree
85
competitive learning environments are beneficial in that they prepare students for life
experiences such as applying for jobs or competing for grants. In addition, these situations
can develop self-reliance and self-confidence in students.
Teachers have the option of structuring lessons competitively, individualistically, or
cooperatively. The decisions teachers make in structuring lessons can influence students'
interactions with others, knowledge, and attitudes (Carson, 1990; Johnson & Johnson, 1987).
In a competitively structured classroom, students engage in a win-lose struggle in an effort to
determine who is best (Johnson & Johnson, 1991). In competitive classrooms students
perceive that they can obtain their goals only if the other students in the class fail to attain
their own goals (Johnson et al., 1986).
Avoidant Learning Style
Only 5.4 % of the respondents have avoidant learning styles. The students’ level of
agreement or disagreement is presented in Table 2f. Majority of the responses of the students
under this learning style is undecided.
Table 2f. Responses of students toward avoidant learning styles
Avoidant Statement Description
I often daydream during Biology class. 2.66 Undecided
Classroom activities in Biology are usually boring. 2.12Moderately
Diasgree
I very seldom am excited about material covered in Biology.
3.27 Undecided
I don't want to attend my Biology class. 1.84Moderately
Disagree
86
Paying attention during Biology class is difficult for me to do.
2.71 Undecided
I have given up trying to learn anything from going to Biology class.
3.27 Undecided
I study just hard enough to get by in Biology. 3.86 Moderately Agree
I typically cram for exams in Biology. 3.19 Undecided
I would prefer that my Biology teacher ignores me in class.
2.69 Undecided
During Biology class, I tend to socialize with people sitting next to me.
3.57 Moderately Agree
Overall
2.92 Undecided
Legend
Students moderately agreed that they study hard enough and they tend to socialize
with people sitting next to them. They were undecided when they talk about their enthusiasm,
cramming during exams, and the ignoring attitude of their Biology teacher. Students
moderately disagreed that the classroom activities are boring; that they do not want to attend
Biology class.
Leroy and Symes ( 2001) wrote that students with avoidant learning style are seen to
lack interest in learning content and attending class. They usually do not participate in the
class activities; worst, most of them are also likely to have high absenteeism. They organize
their work poorly and take little accountability for their learning. For them, going to school is
monotony that requires a little of their attention. Velasquez (2007) and Mariano (2005) wrote
in their respective studies that students with this kind of learning style often perform poorly,
1.00 - 1.79 Strongly Disagree1.80 - 2.59 Moderately Disagree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Agree4.20 - 5.00 Strongly Agree
87
hence, their academic performance suffer the most.
According to Grasha (1996), avoidant learners are typically overwhelmed and
disinterested in the learning environment, and tend to keep ideas to themselves. Research by
Weiten (1998) suggests that academic and social pressure associated with student’s life
increase the likelihood of the learners experiencing psychological symptoms and academic
stress. Avoidant learners who are easily overwhelmed by the learning environment may find
more pressure and stress which can manifest in the form of internalizing or externalizing
behaviors associated with psychological distress.
Summary of Students’ Learning Styles
The summary of the means and the description of students responses in all the six
dimension of learning styles are presented in Table 2g. This indicates the respondents’ degree
or level of agreement or disagreement about students’ approach in learning Biology.
Students’ responses varied according to the different dimensions of learning style under
different reflections.
Table 2g. Means and standard deviations obtained by the respondents in the dimensions of learning styles
Learning Style Overall SD Description
Collaborative 3.89 0.25 Moderately AgreeParticipant 3.82 0.28 Moderately AgreeDependent 3.77 0.38 Moderately AgreeIndependent 3.48 0.39 Moderately AgreeCompetitive 3.52 0.37 Moderately Agree
Avoidant 2.92 0.63 Undecided
88
Legend:
Table 2g reveals that the most dominant learning style among respondents was
collaborative. The rest of the respondents had independent, competitive and avoidant learning
style. Almost all the learning styles were moderately agreed by the students in different
degrees as supported by the overall and standard deviation of their responses. Students
were, however, undecided with avoidant learning style.
Epistemological Beliefs of the Respondents
Epistemological beliefs refer to how individuals come to know, the theories and
beliefs they have about knowing, and the manner in which such epistemological premises are
part of an influence on cognitive processes of thinking and reasoning. Figure 3 shows the
epistemological beliefs of the respondents. Generally, respondents exhibit relatively emergent
beliefs among the various dimensions of epistemological beliefs. In this study, the lower the
score, the more the students show sophistication in the different dimensions of
epistemological beliefs.
1.00 - 1.79 Strongly Disagree1.80 - 2.59 Moderately Disagree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Agree4.20 - 5.00 Strongly Agree
89
Figure
3. Epistemological beliefs held by the respondents in Biology
It could be noted that majority of the respondents, 128 or 87.1 % were emergent. Emergent
learners refer to students whose beliefs consist of combined characteristics found in
sophisticated and naïve believers. They have the tendency to think that knowledge is
tentative, complex, acquired gradually and the ability to learn can be changed, or at times,
they may believe that knowledge is absolute, simple and can be handed down by authority.
Seventeen (17) or 11.6%, on the other hand, were still naïve or believed that knowledge is
absolute, simple, handed down by authority, acquired quickly or not at all and that the ability
to learn is fixed at birth. Only two or 1.4% of the respondents were sophisticated in their
beliefs. Sophisticated learners believe that knowledge is tentative, complex, derived by
reason, acquired gradually, and that the ability to learn can be changed. These students were
found to have belonged to urban schools.
Results of the studies of Chan and Elliot (2002) and Ryan (1984) revealed that the
younger respondents usually hold naïve beliefs about the nature of knowledge that is certain
90
and instantly recognizable. As they grow older, they start to adopt a more sophisticated
viewpoint about knowledge and believe knowledge is changing and tentative. Majority of the
students in this study were probably in a transitional stage of development of epistemological
beliefs while others had already passed through the naïve stage. Perry (1970) also revealed in
his study that younger learners move from viewing truth in absolute terms of right and wrong
to recognizing multiple, conflicting versions of “truth” representing legitimate alternatives as
they mature.
In a longitudinal study, Schommer et al. (1997) continued Schommer’s (1993b) study
about the development of secondary students’ epistemological beliefs. This group was a ran-
dom sample of the students who started the questionnaire as freshmen in 1992. In this study,
high school seniors completed the SEQ in 1995. The researchers concluded that all four epis-
temological beliefs, quick learning, innate ability, simple knowledge, and certain knowledge,
became more sophisticated as students matured
The succeeding paragraphs present the students’ responses regarding the five dimen-
sions of epistemological beliefs. Mean, standard deviation and descriptions for each state-
ment under a specific facet of students’ epistemological beliefs are presented. Majority of the
statements of the Epistemological Beliefs Inventory are leaning toward naïve pole. This
means that when the overall mean of each dimension leads toward 5 (strongly agree), the stu-
dents become more naïve while when the students scored lower, they tend to become sophis-
ticated. However, in this study, there were also statements which were expressed in sophisti-
cated statements. To avoid confusion, the researcher used the reverse range of mean and de-
91
scription to show the level of students’ agreement and disagreement on the statements that in-
dicate sophisticated beliefs. Those indicated with asterisk are reversely scored.
Quick Learning
The students’ responses regarding Quick Learning dimension are described in Table
3a with the mean, standard deviation and description of each statement.
Table 3a. Responses of the students in quick learning dimension
Quick Learning Statement SD Description
Students who learn things quickly in Biology are the most successful. 3.25 1.34 Undecided
If a student tries too hard to understand a problem in Biology, he will most likely end up being confused. 3.21 1.19 Undecided
In Biology, if you don't learn something quickly, you won't ever learn it.
2.63 1.42 Undecided
If you haven't understood a lesson in Biology the first time through, going back over it won't help.
2.77 1.50 Undecided
Working on a problem in Biology with no quick solution is a waste of time.
2.78 1.31 Undecided
Overall 2.93 0.76 Undecided
Legend:
A relative sophistication in their beliefs is more evident in Quick Learning with a of
2.93 described as undecided. This indicates that majority of the students tend to believe that
1.00 - 1.79 Strongly Disagree1.80 - 2.59 Moderately Disagree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Agree4.20 - 5.00 Strongly Agree
92
there are cases where learning is acquired quickly or while sometimes knowledge is acquired
gradually.
Generally, students were undecided in all statements under Quick Learning. This
means that most of the respondents would tend to believe that there are cases where students
can learn things quickly, believe that those who learn things rapidly are the most successful
in Biology. For these students, learning either occurs at initial endeavors or is not likely to
occur at all. There are times, however, when these same students think that knowledge is cre-
ated through learning effort and process which means that they believe in the gradual
development of their knowledge in Biology. In addition, it would necessi-
tate that they spend longer time striving and struggling to perform fit-
tingly in Biology activities.
Innate Ability
Innate Ability refers to the factor as a continuum ranging from the belief that the abil-
ity to learn is fixed at birth to the belief that learning improves over time with experience.
The responses of the students are presented in Table 3b. In this dimension, the students had
an overall response of 3.10. Their belief manifested sophistication when they moderately
disagreed that no amount of hard work can make students smart and that smart students need
not work hard to be able to do well in Biology. Students showed less sophistication as they
believe that some students are born with special gifts and talents in Biology. It is interesting
to note that majority of the respondents tend to believe that in one way or another person may
93
have the innate capability that others do not have when it comes to Biology. On the other
hand, these same students cast their doubts as to whether aptitude in Biology is inborn and
whether the capacity to learn Biology is dependent on innate ability.
Table 3b. Responses of the students in innate ability dimension
Innate Ability Statement SD Description
Some students in Biology will never be smart no matter how hard they work.
2.31 1.18Moderately Dis-
agree
Really smart students don't have to work as hard to do well in Biology.
2.33 1.25Moderately Dis-
agree
Students can't do too much about how smart they are in Biology.
3.12 1.13 Undecided
How well you do in Biology depends on how smart you are.
3.18 1.18 Undecided
Some students in Biology class just have a knack for learning and others don't.
3.07 1.11 Undecided
Smart students in Biology are born that way. 2.61 1.19 Undecided
Some students are born with special gifts and talents in Biology
3.49 1.25Moderately
Agree
Overall 3.10 0.66 Undecided
Legend:
Simple Knowledge
1.00 - 1.79 Strongly Disagree1.80 - 2.59 Moderately Disagree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Agree4.20 - 5.00 Strongly Agree
94
Table 3c presents the responses of the students regarding Simple Knowledge. Stu-
dents had mixed agreements in their belief in Simple Knowledge with the overall of 3.13
and standard deviation of 0.53. In this particular dimension, one of the statements was ex-
pressed towards sophistication. To avoid confusion, it was marked with an asterisk to indicate
that it was reversely scored. Reverse scoring was utilized in some
Table 3c. Responses of the students in simple knowledge dimension
Simple Knowledge Statement SD Description
It bothers me when Biology teachers don't tell stu-dents the answers to complicated Biology problems.
3.56 1.19Moderately
Agree
Too many theories in biology just complicate things. 3.22 1.24 Undecided
The best ideas in biology are often the simplest ones. 3.64 1.22Moderately
Agree
Biology teachers should focus on facts instead of the-ories.
3.52 1.17Moderately
Agree
Some Biology concepts are simpler than most Biol-ogy teachers would have you believe.
3.27 0.99 Undecided
Biology is easy to understand because it contains so many facts.
3.37 1.21 Undecided
In Biology, the more you know about a topic, the more there is to know.*
1.86 0.99Moderately
Agree
Overall 3.13 0.53 Undecided
* reverse scored Legend:
Regular scoring *Reverse Scoring
Strongly Disagree 1.00 - 1.79 Strongly AgreeModerately Disagree 1.80 - 2.59 Moderately AgreeUndecided 2.60 - 3.39 UndecidedModerately Agree 3.40 - 4.19 Moderately DisagreeStrongly Agree 4.20 - 5.00 Strongly Disagree
95
statements of selected dimensions such as this to show the students’ agreement and disagree-
ment regarding the statement. In this study, as the statement is reversely scored, it demon-
strates sophistication in the viewpoint of the respondent.
They moderately agreed that, inconvenience arises when teachers do not teach what it
is ought to be taught, teachers should focus on facts and that the best ideas in Biology are of-
ten the simplest ones. This may be attributed the respondents’ strong belief in authority as
source of knowledge that is why many depend on them, thereby, influencing students’ con-
ception of one’s own ability.
They felt undecided as to whether many theories just complicate things and that Biol-
ogy is filled with simpler concepts and facts. This means that they sometimes tend to believe
that there are simple concepts or ideas in Biology that are easy to understand and sometimes
they regard this knowledge in Biology as rather complex than simple. Ryan (1984) disclosed
that majority of high school respondents in his study exhibit beliefs in simple knowl-
edge and quick learning. These students later on developed more ma-
tured or sophisticated idea about the structure and origin of knowledge
when they are exposed to classroom activities that promote more sensi-
ble perception regarding knowledge.
Certainty of Knowledge
Certainty of knowledge refers to the dimension of the students’ epistemological
beliefs which maintain that knowledge is absolute to knowledge is constantly changing.
Consequently, this dimension also holds the largest number of statements that are oriented
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toward sophisticated beliefs. As earlier stated, they were marked in such a way showing their
reverse scoring. Statements which were reversely scored illustrate sophistication in the
responses of the students.
The responses of the respondents regarding certainty of knowledge are presented in
Table 3d with an overall of 3.29 which is undecided. This means that majority of the
students show greater conviction that knowledge in Biology may be tentative or ever-
changing at one time or may be certain sometimes.
Table 3d. Responses of the students in certainty of knowledge dimension
Certainty of Knowledge Statement SD DescriptionTruth in Biology means different things to different people. *
2.53 1.14 Moderately Agree
Absolute moral truth does not exist in Biology.* 3.20 1.14 Undecided
I like biology teachers who present several competing theories and let their students decide which is best.*
2.36 1.29 Moderately Agree
If two students are arguing about something in a Biol-ogy class, at least one of them must be wrong.
3.48 1.17 Moderately Agree
The moral rules in Biology I live by apply to everyone in the class.
3.38 1.01 Undecided
What is true today in Biology will be true tomorrow. 3.37 1.17 Undecided
You can study Biology concepts for years and still not really understand them.*
3.41 1.2Moderately Dis-
agree
Sometimes there are no right answers to Biology's big problems. *
2.81 1.17 Undecided
Overall 3.29 0.57 Undecided
* reverse scored Legend:
Regular scoring *Reverse Scoring
Strongly Disagree 1.00 - 1.79 Strongly AgreeModerately Disagree 1.80 - 2.59 Moderately AgreeUndecided 2.60 - 3.39 UndecidedModerately Agree 3.40 - 4.19 Moderately DisagreeStrongly Agree 4.20 - 5.00 Strongly Disagree
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Most of the students moderately agreed on statements pertaining to truth in Biology
that is different from one person to another and that when two people have opposing ideas in
Biology, at least one of them is wrong denoting of the certainty of knowledge. They were,
however, undecided whether or not to believe in the existence and applicability of moral ab-
solute truth in Biology to others and right answers in Biology’s big problems. This implies
that the more students believed that knowledge in Biology is certain, the more likely they
were to treat inconclusive information as certain or unchangeable knowledge.
Solomon et al. (1994) found in their studies students aged seven to ten years old were
more likely to have less sophisticated beliefs in the stability of knowledge, that is, they be-
lieve that knowledge is certain and unwavering. In a subsequent large-scale study, Solomon
and her colleagues used the same questionnaire with a much larger age-range of students (13-
to 18-years-old), the researchers found that older students’ views showed a significant pro-
gression toward a sophisticated understanding of science particularly in their beliefs in cer-
tainty and simplicity of knowledge.
Omniscient Authority
One of the dimensions of the epistemological beliefs recognizes the students’ beliefs
in the source of knowledge. Omniscient authority as referred to by Schommer (1990) main-
tains that knowledge is handed down by experts in the field to knowledge is reasoned out
through objective and subjective means. In this particular dimension, one specific statement
leaned toward sophistication. It was interesting to note students showed maturity when they
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moderately agreed that at times teachers’ authority in Biology may be questioned and they
moderately disagreed when asked if those who questioned the teachers were trouble makers.
However, for most, students showed least sophisticated epistemology in Omniscient
Authority with a = 3.32 (Table 3e). This implies that a large portion of the students believe
in the authority of teacher as the main source of knowledge in Biology.
The manifestation of their least sophistication in this dimension was supported by the
statement of the students strongly agreeing that teachers should teach all there is to know in
Biology. However, they all moderately agreed about the influence of the teacher in the class-
room.
Table 3e. Responses of the students in omniscient authority dimension
Omniscient Authority Statement SD Description
Students should always obey the law inside Biology classroom.
3.91 1.22Moderately
AgreeTeachers should teach their students all there is to know about Biology.
4.20 1.10 Strongly Agree
In a Biology class, students should be allowed to question their teachers' authority.*
2.07 1.19 Moderately Agree
When a Biology teacher tells me what to do, I usually do it.
4.00 1.03 Moderately Agree
Students who question Biology teachers are trouble makers.
2.39 1.26 Moderately Agree
Overall Mean
3.32 0.56 Undecided
* reverse scored Legend
Regular scoring *Reverse Scoring
Strongly Disagree 1.00 - 1.79 Strongly AgreeModerately Disagree 1.80 - 2.59 Moderately AgreeUndecided 2.60 - 3.39 UndecidedModerately Agree 3.40 - 4.19 Moderately DisagreeStrongly Agree 4.20 - 5.00 Strongly Disagree
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This strong agreement of the students towards the authority of the teacher may be ad-
dressed borrowing the conceptual lenses from social psychology where culture, that of Asian,
in particular, plays an important role in the learning of students.
It can be fairly sustained that culture in Asian societies, where modernity seems to go
along with traditional values, principles such as those pinpointed by Moemeka (1996) may
still influence norms, values and behavior in people’s relationships, in general, and in com-
munication, in particular. If so, and since schools (classrooms) are, by excellence, settings of
communication (primarily between the teacher and the students), a culturally based explana-
tion could be found as to why Omniscient Authority is a prevalent element in students’ epis-
temological beliefs among the respondents.
Sitoe (2004) further argued that, in his study where education is highly treasured for
being a ‘social good’, the culture of respect towards a teacher is to be regarded as associated
to a perception of the utility of the teacher (the one conveying that ‘social good’) to the
community.
Summary of Students’ Epistemological Beliefs
To decide on the nature of epistemological beliefs that respondents hold, means and
standard deviations were calculated and tabulated as shown in Table 3f.
Table 3f. Means and standard deviations obtained by the respondents in the five dimen-sions of the Epistemological Beliefs
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Dimension Overall SD Description
Simple Knowledge 3.13 0.53 UndecidedCertainty of Knowledge 3.29 0.57 UndecidedInnate Ability 3.10 0.66 UndecidedOmniscient Authority 3.32 0.56 UndecidedQuick Learning 2.93 0.76 Undecided
Legend
Data in Table 3f indicate that respondents hold a variety of beliefs about the nature of
knowledge in Biology and the process of handling this knowledge. Students’ responses
varied according to the different dimensions of epistemology under consideration. Based on
the findings, students showed sophistication in Quick Learning, this means that they mostly
believed that knowledge is acquired gradually. However, they showed least sophistication in
the Omniscient Authority. This means that the respondents tended to believe that teachers are
the definitive source of information in Biology.
Profile of Students’ Academic Performance in Biology
The grade point average (GPA) of the respondents presented in Figure 4 refers to the
average grade in Biology of the respondents during the school year 2009-2010. The results
revealed that majority of the respondents had an average performance in Biology with the
mean rating of 83.76 and a standard deviation of 3.87 (Appendix E).
1.00 - 1.79 Strongly Disagree1.80 - 2.59 Moderately Disagree2.60 - 3.39 Undecided3.40 - 4.19 Moderately Agree4.20 - 5.00 Strongly Agree
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Majority of respondents about 108 or 73.4% had a grade of 80-87 which means they
have average performance. About 25 or 17% had a high academic performance. Their grades
were at least 88. Only 14 or 9.6% had a low academic performance or a grade just below 80.
Similar result was found by Velasquez (2007) in her study that majority of the high
school respondents in Muñoz National High School had average academic performance in
Mathematics, Science and English.
Relationship Between Learning Styleand Epistemological Beliefs of the Respondents
Figure 4. Distribution of respondents’ grade point average
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The relationship between the respondents’ epistemological beliefs and learning styles
was also investigated in this study. Table 4 below shows the correlation between the learning
styles of the respondents and their epistemological beliefs.
Table 4. Relationship between learning styles and epistemological beliefs
Learning
Styles
Epistemological Beliefs
Simple Knowledge
p-valueCertainty of Knowledge
p-valueInnate Ability
p-valueOmniscient Authority
p-valueQuick
Learningp-value
Independent 0.213** 0.009 -0.011 0.894 0.261** 0.001 0.117 0.160 0.212* 0.010
Avoidant -0.064 0.441 -0.203* 0.014 0.205* 0.013 -0.190 0.021 0.389** 0.000
Collaborative 0.101 0.225 0.366** 0.000 0.181* 0.028 0.099 0.235 0.075 0.364
Dependent 0.295** 0.000 0.262** 0.001 0.165* 0.046 0.278** 0.001 0.145 0.080
Competitive 0.163* 0.049 0.082 0.323 0.403** 0.000 0.141 0.090 0.362** 0.000
Participant 0.247** 0.003 0.315** 0.000 0 .095 0.254 0.294** 0.000 0.029 0.725
** Highly significant at 0.01 level (2-tailed) * Significant at the 0.05 level (2-tailed)
Results revealed that independent learners had a tendency to believe in the complexity
of knowledge; that learning can change anytime as well as in the gradual acquisition of
knowledge in Biology. For them, to grasp concepts or ideas in Biology, facts must be
presented in continuous manner to be able to absorb quickly. They also have the propensity
to believe in the knowledge as a result of personal experience and to those facts they acquired
gradually. This relationship may be attributed to the idea that independent learners are fond
of discovering their own knowledge so they always consider a continuous processing of
knowledge into a meaningful outcome when it comes to learning Biology.
Although most of avoidant learners are inattentive and uninterested in the class, those
students, on the other hand, are more likely to consider that knowledge is a lifelong process
and ability is not inborn. Respondents with this kind of learning style have the tendency to
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believe that knowledge is not inherent and that learning is gradually acquired when it comes
to learning Biology. While most of the time avoidant learners are associated with negative
connotations when it come to learning, they may exhibit positive characters at times
depending on activities and other classroom factors that may encourage them to be
constructive (Sarasin, 1998). The negative correlation existing between their learning style
and the certainty of knowledge connotes that these learners may have the predisposition of
believing that knowledge is definite. This may be attributed to their own behavior being
negligent and uninterested in the class.
The significant correlation between the collaborative learning style and certainty of
knowledge and innate ability may mean that learners who scored high on this kind of
learning style believe that knowledge is constantly evolving and that whatever knowledge
they have in Biology is a result of continuous experience. This belief may be explained by
the fundamental attitude exhibited by the collaborative learners. Since they always consider
associating themselves with others, they have the tendency to construct their own knowledge
through their experience from others, hence, whatever knowledge they have is still evolving.
Dependent learning style is highly correlated to the beliefs such as simple knowledge,
certainty of knowledge and omniscient authority. This may indicate that dependent learners
learn Biology if they perceive knowledge in its complex and indistinctive form. It is also
interesting to note that dependent learners set aside their regard for the authority or teacher as
the primary source of knowledge in Biology. Dependent learning style was also significantly
related with their belief in inner ability. This may mean that dependent learners learn better
Biology concepts as they realize that people learn through experience.
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Competitive learning style had highly significant correlation with the beliefs of innate
ability and quick learning. This may denote that as a student becomes competitive in the class
the more he becomes aware that knowledge may be constructed from one’s own experience
and it is acquired through gradual process. Competitive learners love to vie with others, thus,
this teaches them to explore outside and to create or interpret knowledge according to their
perspective. Competitive learning style was also significantly correlated with the simplicity
of knowledge. This denotes that competitive learners believe that knowledge is highly
integrated and interwoven. This view may arise from their belief in the gradual acquisition of
knowledge. For them to efficiently learn concepts or ideas in Biology, knowledge should be
encountered, progressively acquired and carefully integrated into a meaningful learning
experience.
Lastly, participant learning style has highly significant correlation with the simplicity
and certainty of knowledge. Participant learners may have the tendency to believe that
knowledge is organized into a highly incorporated and intertwined data resulting from an
evolving source of knowledge. It can be well remembered that participant learners are keen
to the idea of learning from their association with others. If so, participant learners may be
utilizing this system in organizing data they gather from their external environment apart
from what they learn from their teachers and from books. Participant learners are also closely
associated with the omniscient authority. It was stated previously that participant learners
take pride in connecting not just only with their classmates but with their teachers as well.
This sophistication in belief about the authority as the source of knowledge may have
influenced them to use such approach in functioning well in the Biology class.
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Many studies have investigated the influence of epistemological beliefs on learning
strategies (Hofer, 1999) in traditional contexts. Schommer and Hutter (2002) found links
between epistemological beliefs and students' comprehension, meta-comprehension, study
strategies, and interpretation of text. The more students believe in complex knowledge and
gradual learning, the more likely they are to successfully comprehend, monitor their
comprehension and strategize their learning. Kardash and Scholes, (1996) suggested that
students who have less sophisticated beliefs (in the case of avoidant students) tend to use
surface-level strategies to collect isolated facts and try to rehearse and memorize concepts
and key terms to prepare for examinations, while students with sophisticated epistemological
beliefs tend to apply deep-level strategies such as elaboration and organization (as in the case
of participative and collaborative learners).
Relationship Between Learning Styles and Academic Performance
Learning styles are seen to be the most distinguished way a student learns or
processes information. In many studies, the potentiality of learning styles as an indicator of
how a student learns and how he likes to learn have been frequently established in the past.
Table 5 shows the relationship between the learning styles and academic performance
in Biology of the respondents. A highly significant relationship (r=0.266, p<0.01) is
observed between participant learning style and academic performance. This means that as
the student becomes more participative and given the chance to involve himself actively with
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the rest of the students and with the activities in the classroom, the more likely that his grade
in Biology improves. This is also true with students who are collaborative.
Table 5. Relationship between learning styles and academic performance
Learning Styles Grade Point Average p-value
Independent 0.350 0.674Avoidant -0.288 ** 0.000Collaborative 0.217 ** 0.008Dependent 0.094 0.257Competitive 0.090 0.277Participant 0.266 ** 0.001
** Highly significant at 0.01 level (2-tailed)
A highly significant relationship (r = 0.217, p<0.01) is also noted between
collaborative learning style and academic performance of students. The more the teachers
give the learners the chance to collaborate with group activities, discussions and dynamics
within the classroom, the higher the tendency that students obtain higher grades.
This result may be attributed to the current educational reform in the Philippines
particularly the shifting of a teacher-centered to student-centered goal may be one of the
reasons why there is a high rate of students who favor collaborative and participant learning
styles. Collaborative and participative learning describe the many educational approaches
involving joint intellectual effort by students, or students and teachers together. Most learning
activities from collaborative and participative approach focus on the student's exploration and
application of the course material and not the teacher's presentation of it. Gerlach (1994)
stated that the student-oriented goal of education is anchored on two learning theories such as
cooperative and constructivist learning theories. Cooperative learning theory incorporates the
idea that the best learning occurs when students are actively engaged in the learning process
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and working in collaboration with other students to accomplish a shared goal. While
constructivism focuses on personal experience as the foundation for learning new material,
cooperative learning utilizes not only the student’s own experience to solidify knowledge, but
also uses the experiences of others (Panitz, 1996). When cooperative learning is incorporated
into the classroom, research suggests students learn with greater depth and complexity while
enjoying the experience even more. Students who are asked to work together also tend to be
less intimidated by the task and will work at the task with greater intensity for longer time.
Consequently, a highly significant but negative correlation (r= -0.288, p<0.01) is
observed between the avoidant learning style and academic performance. This may mean that
when a student becomes neglectful, uninterested or passive in the classroom especially
toward activities, he tends to obtain lower grade in Biology. The result implies that
meaningful and thought provoking activities as well as encouragement from teachers, peers
and parents as well may help improve avoidant students’ attitude towards learning.
Results of the study are congruent with the findings of Carbonel (2008) and Mariano
(2005). Mariano (2005) found out in her study among students of General Biology in CLSU
that their CLSU College Admission Test (CAT) scores in Science were significantly
correlated with collaborative and participant learning styles. She found out that the students
who exhibit these learning styles are found to have higher CAT scores. Similarly, those who
exhibit avoidant and competitive learning styles were the ones who have low scores in
science CAT. Likewise, Carbonel (2008) also found out in her study that there was a highly
significant correlation noted between collaborative learning style and the score in science of
CLSU CAT among CFY students. This means that these students who showed collaborative
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learning style significantly earned higher score in CAT. Results of her study further revealed
that respondents who exhibited avoidant learning styles tended to get lower grade in the
science part of the CLSU-CAT.
Relationship Between Epistemological Beliefsand Academic Performance
The relationship between the respondents’ epistemological beliefs and academic
performance in Biology was presented in Table 6. This shows a significant relationship
existing between the students’ academic performance and the certainty of knowledge.
Table 6. Relationship between epistemological beliefs and academic performance
Epistemological Beliefs Grade Point Average p-value
Simple Knowledge -0.008 0.921Certainty of Knowledge 0.308** 0.000Innate Ability 0.040 0.629Omniscient Authority 0.095 0.250Quick Learning -0.017 0.835
** Highly significant at 0.01 level (2-tailed)
This association of students’ performance in Biology and their belief in certainty of
knowledge denotes that students who scored perform better in Biology are those who believe
that knowledge is a product of a person’s effort to construct his own learning through direct
experience. This may also mean that when students see knowledge in Biology as tentative or
ever-changing, they tend to improve their performance in Biology.
In a longitudinal study, Trautwein and Ludtke (2007) examined the relationship
between epistemological beliefs, specifically the certainty of knowledge and school
109
achievement. Results of the study showed that certainty beliefs was found correlated
significantly and negatively with final school grades (r = -.23, p < .05) of the German
students. Furthermore, the certainty beliefs were specified mediating the influence of family
background on final school grades.
Sitoe (2004) in his study about the epistemological beliefs of Mozambican high
school students found that epistemological beliefs do not appear directly related with aca-
demic achievement. Their influence is rather indirect and it is exerted through perceptions of
education. Distinctively, believing that learning is simple and that knowledge is delivered by
authority seems to influence the likelihood of the perception that education is reduced to get-
ting schooled, for personal and material benefits. In turn, this perception of education, which
privileges the ultimate ends of education rather than the learning process, seems to have posi-
tive impact on academic achievement.
Learning Styles and Epistemological Belief as Predictors of Academic Performance
Multiple regression analysis was conducted to test the predictors of academic
performance of students in Biology. In this study, the students’ learning styles and
epistemological beliefs were tested for their predictive influence on the respondents’
academic performance in Biology. Results revealed that among the dimensions of
learning styles, it was only the avoidant learning style that predicted the
academic performance in Biology of students (F= 3.1243, p<.01 Adjusted
R²= .137). The negative value of the regression indicates that as students
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favor avoidant learning style, the more they obtain lower grades in
Biology. This implies that students who were underachievers in the class
are consequently those who portray passive and uninterested attitude in
the class. Such students if not always given attention to be encouraged
will remain indifferent and inactive in most classroom activities, thereby,
always continue to be the underachievers in the class. Avoidant learners
have always been the subject of interest among researches particularly
on how to improve their behavior towards learning. Table 7 shows the
result of the multiple regression analysis between the learning styles and
epistemological beliefs of the students.
Table 7. Multiple regression analysis for predictors of academic per-formance
Variables β Std.Err. - of Beta t Sig.
Independent 0.008870 0.094154 0.0942 0.925084Avoidant 0.277572 0.093988 -2.9533** 0.003710Collaborative 0.110177 0.111742 0.9860 0.325901Dependent -0.172346 0.119614 -1.4409 0.151941Competitive 0.135127 0.104921 1.2879 0.199989Participant 0.167571 0.115550 1.4502 0.149321Simple Knowledge 0.013133 0.084482 0.1554 0.876700Certainty of Knowledge 0.203161 0.090162 2.2533* 0.025854Innate Ability -0.021917 0.095192 -0.2302 0.818257Omniscient Authority -0.025101 0.086049 -0.2917 0.770961Quick Learning 0.029646 0.094824 0.3126 0.755037** Highly significant at the 0.01 level (2-tailed) *Significant at the 0.05 level (2-tailed)
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Cano and Rodriguez (2008) asserted in their study that deep strategy for learning used
by the students in coping with their everyday academic works would predict the academic
performance of the students. In their study about the students’ approach to learning as
predictor of academic achievement among respondents, Diseth and Martinsen (2003) argue
that high achievement can be predicted by a deep approach, either alone or in combination
with a strategic approach to learning. In contrast, low academic achievement can be predicted
by a surface approach to learning. Indeed, the surface approach to learning has consistently
been found to negatively correlate with academic success. Approaches to learning are
conceived as the individual differences in intentions a student has when faced with a learning
task (Diseth and Martinsen, 2003). They reflect the strategies an individual uses to achieve a
particular goal.
When the epistemological beliefs were tested for their predictive ability, the students’
belief in the certainty of knowledge was found to predict the academic performance of the
students. This means that the more the students believed that knowledge is tentative or ever-
changing as a result of knowledge development though personal experience, the more they
improve their performance in Biology. Similarly when the students believe that knowledge is
definite, there is a tendency for students to obtain lower grade in Biology. Kardash and Sc-
holes (1996) wrote that the stronger the students’ beliefs in certainty, the more likely students
are to endorse opinions that do not reflect the inconclusive nature of the information pro-
vided. Because strong certainty beliefs prevent students from engaging in in-depth processing
of information, they will probably have significant long-term costs. Hence, helping students
to acquire a sophisticated beliefs system about human knowledge is an important educational
goal in itself and a means of enhancing academic achievement. It is more likely that this ob-
112
jective will be achieved if the materials used in the classroom represent the tentative nature
of human knowledge
Abdel-Majeed and Ismail (2005) found out in their study that three
dimensions of epistemological beliefs, specifically certainty of knowledge,
structure and integration of knowledge significantly predicted the aca-
demic performance of students in Saudi Arabia. They pointed out that stu-
dents who have sophisticated beliefs in the certainty, structure and inte-
gration of knowledge would have the tendency to obtain higher grades.
Moderating Effect of Socio-demographic Characteristicsto the Relationship of Learning Styles
and Academic Performance
In order to find the moderating effect of the socio-demographic characteristics such as
age, gender, school location, ICT accessibility, family income, parents’ educational
attainment and parents’ occupation on the relationship of academic performance and learning
styles, hierarchical regression was employed. Hierarchical regression is a method used in
order to determine which among the third variables would interact with the relationship of
independent and dependent variables. All the resulting mean of the dimensions of learning
styles were transformed into Z scores. The product of Z scores of independent variable and
moderating variables were obtained to create new variables (e.g. z avoidant X z family
income).
In this study, since only the avoidant learning style was the one to have been found to
113
predict the academic performance, the researcher focused on this particular learning strategy.
With regards to socio-demographic characteristics, only the family income was found to be a
moderating variable that interacts with the avoidant learning style as a result of regression. In
the hierarchical regression, the Z scores of the avoidant learning styles together with the
moderating variable were entered as independent variables in the first step. The product of Z
avoidant and family income, for example, was entered in the second step with the
performance in Biology as the dependent variable to find out whether moderating variables
moderate the relationship between learning style and academic performance. A similar
procedure was followed for the rest of the moderating variables. The beta coefficient and its
significant values were also identified. In investigating causal relationship such as this, direct
and indirect effects may emerge as result of the test. The direct effect is one in which the
cause affects the outcome unequivocally rather than other variables. In order for the
independent variable to cause a significant influence on the dependent variable, the effect of
the moderating variable in the independent variable is necessary. Indirect effect on the other
hand is described to which the cause affects the outcome implicitly or indirectly. In short,
with or without the moderating variable, the independent variable will still continue to
influence the dependent variable.
Results of the hierarchical regression analysis revealed that the family income did not
moderate the relationship between the avoidant learning style and the academic performance
of the students. This means that students who have the tendency to adopt avoidant learning
style will continue to have lower grades in Biology whether or not their family has low or
high income. This result may be attributed to the predictive ability of avoidant learning style
114
to academic performance of the respondents but not their family economic status specifically
their monthly income. With this in consideration, as economic status of students do not
interfere with their learning process, one may say that teachers should focus more on the
improvement of the students’ learning style in order to enhance their academic performance.
Since economic status is not an issue that matters on the academic performance of the
students, it is fair enough to quote an article by Haycock (2001) which addresses issues
related to the achievement gap through research conducted by The Education Trust in the late
1990’s. They questioned both children and adults on what they suspect are causes of this
achievement gap. One comment among those made by the children was, “ What hurts us
more is that you teach us less.’ “ Haycock (2001) concludes: “…we take the students who
have less to begin with and then systematically give them less in school.” What schools do
obviously matters. What also matters is effective teaching.
To further explain the lack of effect of family income on the learning style and
academic performance relationship, Figure 5 shows the interaction of the moderating variable
between the independent and the dependent variables.
115
Figure 5. Interaction plot of family income on the relationship of avoidant learning style and academic performance of the students
In this particular result, it can be seen that the figure depicts a null case. The null case
is a situation where the moderating variable has no effect on the relationship of the
independent (IV) and the dependent variables (DV). This figure assumes that even if the
students belong to families with low or high income, it could be expected that students would
still have low performance in Biology as a result of their adoption of avoidant learning style.
Only one line for both levels in the graphs is visible because one line falls right on top of the
other. Masking off the other line in an interaction plot like this is a clear indication of no
effect to IV-DV relationship.
Moderating Effect of Socio-demographic Characteristicsto the relationship of Epistemological Beliefs
and Academic Performance
Hierarchical regression analysis was also utilized to determine which among the
dimensions of epistemological beliefs would show significant interactions with the socio-
demographic characteristics acting as moderating variables.
After testing potential moderating variables such as age, gender, school location, ICT
accessibility, family income, parents’ educational attainment and parents’ occupation,
hierarchical regression analysis showed that three of moderating variables produced
significant interaction with the epistemological beliefs and academic performance. The
116
discussion of the moderating effects being referred to in this study was further divided into
direct effects and indirect effect. As discussed earlier, the direct effect is one in which the
cause affects the outcome unequivocally rather than the other variable. In order for the
independent variable to cause a significant influence on the dependent variable, the effect of
the moderating variable in the independent variable is necessary. Indirect effect on the other
hand is described to which the cause affects the outcome implicitly or indirectly. In short, the
independent variable will just influence the dependent variable if the mediator variable is
present.
Direct Effects
Earlier, it was established that the belief in the certainty of knowledge was identified
as a predictor of students’ academic performance in Biology. When hierarchical regression
analysis was done in order to test which among the socio-demographic characteristics would
significantly moderate the relationship of certainty of knowledge and academic performance
in Biology, the test revealed that school location significantly moderated their relationship
directly. This implies that students with improved or sophisticated belief in the certainty of
knowledge as a result of moderation brought about by the school location would have the
tendency to get high grade in Biology. This means that the effect of their belief in the
certainty of knowledge is induced by the type of school they attend. The moderating effect of
school location on the relationship of certainty of knowledge and academic performance is
117
shown in Table 8.
Table 8. Moderating effect of school location to the relationship of certainty of knowledge and academic performance
Change Statisticsβ t Sig R2 Change F Change Sig F. Change
Step 1School location -0.054 -0.682 0.496Certainty of knowledge 0.308 3.888** 0.000School Location, Certainty of Knowledge
0.097 7.778** 0.001
Step 2School location x Certainty of
Knowledge-0.295 -2.864** 0.005 0.049 8.201** 0.005
** Highly significant at the 0.01 level
The moderation of school location is most especially true for students who study in
rural areas where their school location is seen to interact directly with their belief in certainty
of knowledge. As these rural students believe that knowledge is not certain and that their
knowledge is built from their own experience, the higher the tendency for these students to
improve their academic standing. However, this interaction is not true for those who study in
urban areas. The school location does not seem to interact with students’ belief in certainty of
knowledge; therefore, their academic performance in Biology is not a result of the combina-
tory effect of school location and certainty of knowledge. With this in consideration, it
seemed reasonable to assume that rural schools teachers’ sensitiveness to improve their stu-
dent’s epistemological beliefs especially their beliefs in the certainty of knowledge is practi-
cally appropriate in order to enhance their students’ academic performance in Biology.
In order to further understand the interaction of the school location on the certainty of
belief-academic performance relationship, the interaction plot in Figure 6 explains the mod-
erating effect of the school location. Students from rural schools who generally have sophisti-
118
cated belief in the certainty of knowledge have the greater capacity to improve their perfor-
mance in Biology than those who have naïve beliefs. It can also be seen that in the case of ur-
ban students, their academic performance is only affected by their belief in the certainty of
knowledge.
Figure 6. Interaction plot of school location on the relationship of certainty of knowledge and academic performance of the students
Kardash and Scholes (1996) reported that beliefs about the certainty of knowledge
predicted the types of conclusions drawn by high school students after reading mixed evi-
dence on a controversial topic (causes of AIDS). The stronger the students’ beliefs in the cer -
tainty of knowledge, the more likely they were to draw conclusions that failed to take into ac-
count the inconclusive nature of information provided. The certainty dimension was also sig-
119
nificantly related to achievement in a study with 326 first year college students (Hofer,
2000). In this study, certainty scores on both a domain-general and a domain-specific mea-
sure were the strongest predictors of academic achievement. The higher their certainty
scores, the lower the students’ academic standing.
Sitoe (2004) found that school location was a significant predictor that affects the
relationship between the students’ epistemological beliefs and the location where the students
are studying. He found out that students in rural schools would have tendencies to improve
academic performance if their belief in certainty of knowledge becomes more sophisticated.
Indirect effect
Earlier it was emphasized that with regard to indirect effects, only in the presence of
the moderating variable that the independent variable will influence the dependent variable.
In further testing of several moderating variables, accessibility to ICT and fathers’
educational attainment of the students were revealed to interact indirectly with the two
dimensions of epistemological beliefs, the omniscient authority and innate ability,
respectively. The indirect of effects of ICT accessibility on the relationship of academic
performance and omniscient authority and father’s educational attainment on the relationship
of innate ability and academic performance were discussed separately.
ICT Accessibility
Hierarchical regression analysis shows that students who have sophisticated belief in
120
the omniscient authority would significantly affect their academic performance if they have
access to information and communication technology. This means that students would get
higher grade in Biology if their belief in omniscient authority is significantly moderated by
their access to information and communication technology. But since this is seen as an
indirect effect, it should be noted that without the access to information and communication
technology, their belief in omniscient authority will not influence their academic
performance. Table 9 shows the moderating effect of ICT on omniscient authority – academic
performance relationship.
Table 9. Moderating effect of ICT to the relationship of omniscient authority and academic performance
Change Statisticsβ t Sig R2 Change F Change Sig F. Change
Step 1ICT accessibility 0.024 0.288 0.774Omniscient authority 0.110 1.328 0.186ICT accessibility, Omniscient Authority
0.012 0.911 0.404
Step 2ICT accessibility x
Omniscient authority0.340 3.738** 0.000 0.088 13.974** 0.000
** Highly significant at the 0.01 level (2-tailed)
Figure 7 shows the interaction plot of the moderating variable on the independent and
the dependent variables. It can be seen that students who have sophisticated beliefs in
121
Figure 7. Interaction plot of ICT to the relationship of omniscient authority and academic performance
omniscient authority are more likely to have improved performance in Biology if they have
access to basic ICT such as internet, e-libraries, etc. On the other hand, those who believe
that teachers and books are the ultimate source of information are likely to have lower grade
only when ICT is considered. Hence, since majority of the students have access to internet, it
would also be better that classroom activities be geared towards sophistication in their
epistemology so that their performance in Biology would also be enhanced.
Barnard (2008) emphasized the need to improve the students’ epistemological beliefs
through online learning to be able to produce significant improvement in the students’ aca-
demic achievement. She suggested that classroom environment should emphasize more tech-
nologically driven teaching strategies. This result indicates that the students’ skill in manipu-
lating ICT may be viewed as positively mediating the relationship between epistemological
beliefs and their academic performance.
Father’s Educational Attainment
Hierarchical regression analysis showed that students who have improved beliefs in
the innate ability would significantly affect their academic performance if the fathers of the
students had higher educational attainment. This means that students who believe that
122
knowledge is not inborn would have the higher likelihood of getting high grades in Biology
especially if their fathers have high educational attainment. This suggests that the parental
education such as that of the father may help in sophistication of epistemological beliefs
which could in turn affect positively the academic performance of the students in Biology.
Innate ability loses its influence on the students’ performance in Biology when the fathers’
education is not considered. Table 10 shows the moderating effect of father’s educational
attainment on relationship of innate ability and academic performance of the students.
Table 10. Moderating effect of fathers’ educational attainment on the relationship of innate ability and academic performance
Change Statisticsβ t Sig R2 Change F Change Sig F. Change
Step 1Fathers’ educational attainment -0.148 -1.792 0.075Innate Ability -0.218 -1.915 0.057Fathers’ educational attainment, Innate Ability
0.023 1.687 0.189
Step 2Fathers’ educational attainment
x Innate Ability0.307 2.727** 0.007 0.048 7.437** 0.007
** highly significant at p < .01
Figure 8 shows the interaction of the moderating variable between the relationship of
the independent and the dependent variables. Students who have fathers who are college
graduates and whose beliefs in innate ability are sophisticated are likely to have improved
performance in Biology. On the other, those students who believe that knowledge
123
Figure 8. Interaction of father’s educational attainment to the relationship of innate ability and academic performance
is inborn and whose fathers are not college graduates are more likely to have lower
performance in Biology. This implies that in classroom where there are majority of students
who have fathers who are non-college graduates, structuring classroom activities to develop
mature belief in the innate ability may be done to facilitate enhancement of students’
performance in Biology.
On the basis of such outcome, it sounds fair to conclude that literacy and adult
education among parents in countries like the Philippines may collaterally contribute to
‘epistemological growth’ (or ‘epistemological sophistication’) of their respective children,
namely, by inculcating in them the perception that ability is not innate and that knowledge is
a result of the person’s own interaction to different sources of knowledge. This particular
result was congruent with Sitoe’s findings (2004) which also found on his study regarding
the intervention of family level of education on the beliefs of students on the authoritative
sources of knowledge, innate ability and on the simplicity of the learning process, that, it is
less likely to be found among those students whose parents have reached higher levels of
education.
124
Revised Diagram of Learning Style, Epistemological Beliefs and Academic Performance
The predictive influence of learning style and epistemological beliefs through
regression analysis have resulted to the revision of hypothesized diagram depicting the
hypothesized relationships among independent, dependent and moderator variables. Figure 9
shows the revised path diagram of students’ learning style and epistemological beliefs towards
students’ academic performance in Biology.
Figure 9. Revised path diagram of students’ learning style and epistemological beliefs toward their academic performance in Biology
Legend for Figure 9
The revision of hypothesized diagram to its new path diagram narrowed down the
predictors of academic performance of students in Biology into avoidant learning style and
Independent variables
Dependent variables
Academic Performance in Biology
EPISTEMOLOGICAL BELIEFS
Certainty of Knowledge
School Location
Omniscient Authority
Innate Ability
ICT Accessibility
Father’s Educational Attainment
LEARNING STYLES
Avoidant
predictorIndirect effectModerating effect
125
certainty of knowledge. On the other hand, hierarchical regression analysis revealed school
location directly influence the relationship of certainty of knowledge and students’ academic
performance in Biology, ICT accessibility and father’s educational attainment indirectly
influence the relationships between omniscient authority and students’ academic performance
in Biology and innate ability and students’ academic performance in Biology, respectively.
Socio-Demographic Characteristics of the Respondents
The socio-demographic characteristics of the respondents which include age, gender,
school, location, ICT accessibility, parents' educational background and parents' occupation
are presented with their respective data in graphical form.
Age
Figure 10 shows the age distribution of the respondents. The age of the respondents
ranged from 13 – 18 years old with the mean 14.12 and standard deviation of 0.63 (Appendix
E).
Figure 10. Age distribution of the respondents
126
The value of the standard deviation connotes that there is a small dispersion of age
among respondents. Majority of them are 14 years old (69.4%), the youngest respondents are
13 (10.2 %) and the oldest respondent is 18 years old or 0.7 %.
This result implies that most of the respondents started their schooling at the age of 6,
the age prescribed by the government to begin their education; hence, majority of the
respondents were 14 years old during their second year.
Gender
The distribution of gender of respondents is presented in Figure 11. The result
revealed that more than half (52.4%) or 77 are females and 70 or 47.6 % are males.
Enrolment for CLSU high schools showed that there were more females than males.
Figure 11. Gender distribution of respondents
127
This is in coherence with the studies earlier reported by Velasquez (2007), Mariano
(2005), and Inocencio (1997) whose respondents in CLSU and Muñoz National High School
were female dominated.
School Location
Figure 12 shows that majority of the respondents, 59.9 % or 88 are studying in rural
schools. The for reason being as such is that the three outreach schools, ULHS Bibiclat,
Palusapis and Pinili are located in the barrios in order to cater to the needs of those students
who live in the rural areas. Castro (1979) stated in his study that this way, these students need
not go to the town proper to continue their secondary education.
Figure 12.
Distribution of the respondents in rural and urban schools
A total of 40.1 % or 59 of the respondents disclosed that their schools are strategically
located in urban communities. These schools are those near the town proper and have access
128
to internet cafes, reading centers and established libraries.
ICT Accessibility
Figure 13 below shows the distribution of respondents on ICT accessibility. A total of
106 or 72.1 % of the respondents have access to basic information and communication
technologies such as internet, e-libraries, reading centers, and fully equipped libraries. These
students enjoy the benefit of ICT, mostly access information and communication technology
at home and not in school. Espino (2008) noted in her study about the ICT capability of
schools in Nueva Ecija that most of the student respondents obtain their experience of using
ICT from friends and classmates who bring them to nearby internet cafes.
A total of 41 or 27.9 %, however, revealed that they have limited or no access at all to
Figure 13. Distribution of the respondents who have access to ICT
129
these technologies. Espino’s (2008) study revealed that most high schools of Nueva Ecija,
had no appropriate master plan, time frame, budget plan and separate body for ICT, limited
access to ICT equipment, internet and landline connections. Students have limited access
and use of ICT equipment and rarely use ICT for school work.
Parents' Educational Attainment
For the educational attainment of the respondents' parents, Figure 14 shows that most of
the fathers, 38.8 % or 57 entered high school and finished their secondary education. A total of
55 or 37.4 %, on the other hand, had been in college and finished their degree. Twenty or 13.6 %
of the respondents' fathers attended graduate studies, 10 or 6.8% were elementary graduates and
only five or 3.4% of them obtained vocational courses.
Figure 14. Distribution of the parents’ educational attainment
Moreover, the result of the study further revealed that majority of the mothers of the
respondents, 64 or 43.5% enrolled and finished college. About 51 or 34.7% were high school
130
graduates. A total number of 22 or 15% attended graduate schooling and nine or 6.1% finished
their elementary education. Only one or 0.7% had vocational course.
Similar results for the father’s educational attainment is in coherence with the results
of respective studies of Mariano (2005), Leoveras (2001) and Inocencio (1997) who found
out that majority of the CLSU students’ fathers were high school graduates.
Parents' Occupation
The nature of work or job of the parents was classified into blue collar, white collar jobs
and non-earning. As shown in Figure 15, majority of the respondents' father occupation (106 or
72.1%) was blue collar job. Blue collar jobs are those occupations which entail manual and
physical application (Carbonel, 2008). These include barber, driver, plumber, vendor, worker,
cook and farmer among others. Only 39 or 26.5 % had fathers whose line of work is categorized
as white collar. White collar jobs include police, teacher, engineer, architect, researcher, food
scientist, nurse, government employee, veterinarian and other degree holders. Only two or 1.4%
were non-earning. These include pastor, jobless, or deceased. This result can be attributed to
their educational attainment wherein most of the fathers of the respondents finished secondary
education.
Figure 15. Distribution of the parents’ occupation
131
Most of the mothers, 65 or 44.2% were non-earning or plain housewives. A total of 42
or 28.6% had blue collar jobs whose line of work includes vendor, domestic helper, cook and
farmer. Forty of the mothers or 27.2% had white collar jobs. They were the professionals who
work as teacher, veterinarian, engineer, nurse, doctor, food scientists, etc. Although most of the
respondents’ mothers enrolled and finished college, majority still preferred to stay at home in
charge of household chores.
The result of this study is congruent with the studies of De Guzman (2005) and
Inocencio (1997) whose respondents’ (CLSU students) fathers had blue collar jobs or mostly
farmers and majority of mothers were plain housewives.
Monthly Family Income
Figure 16 shows the distribution of the respondents’ monthly family income. Family
income refers to the amount earned by all members of the family. It is usually the indicator of
the parents’ ability to fulfill the basic necessities of the family including their children’s
education. The mean monthly family income of the respondents was Php 25,957.82 with the
standard deviation of Php 45,551.93 (Appendix E). The 2007 report of the Department of
Labor and Employment states that the poverty line is about Php 17, 652.00 per month.
Figure 16. Distribution of respondents’ monthly family income
132
Majority of the respondents’ families (103 or 70.1%) had low family incomes while
only 44 or 29.9% of the respondents had high family income. This can be attributed to the
fact that most of the parents had blue collar jobs so their income was considerably much
lower than those with white collar jobs.
The National Statistical Coordination Board (NSCB) estimated in 2006 that the
poverty incidence in the country is equal to 32.9%. In other words, almost 33 out of 100
Filipinos are considered poor. The increase in poverty incidence is reported as caused by
scarcity of job opportunities, social and economic exclusion, and poor economic policies
(Molano, 2010).
The findings of this study are in coherence with the results of the studies of
Velasquez (2007), De Guzman (2005) and Mariano (2005) that majority of the Filipino
families have incomes just below the poverty line.
133
SUMMARY, CONCLUSION AND RECOMMENDATION
Summary
This study was conducted to assess the epistemological beliefs and learning styles of
students for the SY 2009-2010 in Biology in the five high schools of Central Luzon State
University. This was also done to specifically determine the predictive ability and the
relationship of the respondents’ epistemological beliefs and learning styles to academic
performance. The influence of moderator variables such as respondents’ age, gender, school
location, ICT accessibility, parents’ educational attainment, parents’ occupation and family
income on the relationship between the respondents’ performance in Biology and their
epistemological beliefs and learning styles was also investigated in this study.
A total of 147 sophomore students of SY 2009-2010 from the five high schools of the
Central Luzon State University such as the University Laboratory High Schools Bibiclat,
Palusapis, Pinili, Agricultural Science and Technology School and the University Science
High School participated in this study. A survey questionnaire comprising of three parts such
as the Socio-Demographic Characteristics, Learning Styles Inventory developed by Grasha
and Reichmann and Epistemic Belief Inventory by Schraw et al. was used in this study. Data
were analyzed with descriptive statistics, correlational analysis and multiple regression
analysis using Statistica and SPSS.
The results of the study showed that that there were more collaborative (33.3%),
participants (25.2%) and dependent (21.1%) respondents with regard to their learning styles.
This prevailing behavior of being collaborative, participant and dependent were highly
134
attributed to the cultural context and much of educational reforms in the Philippine education
where there is a general shift of teacher-centered to student-centered setting.
As regards to their epistemological beliefs, most of the population (87.1% or 128) had
emergent belief in all of the dimensions of their epistemological beliefs. The most evident of
which is reflected in their beliefs in the “Quick Learning” and “Innate Ability” which showed
of 2.93 and 3.29, respectively. They were undecided as to whether knowledge is “in born”
or can be acquired through experience and knowledge is learnt quickly or not at all or can be
obtained gradually. On the other hand, majority of the respondents tended to show immature
or naïve responses with regard to the influence of the authority or the experts as most of them
still regard their teachers as the ultimate sources of information.
Majority of the respondents, about 73.4% or 108 were average performing students in
Biology. With regard to the relationship between the students’ learning styles and
epistemological beliefs, results revealed that independent learners had a tendency to have a
sophisticated belief in the simplicity of knowledge, in their innate ability and as well in the
speed of knowledge acquisition in Biology. Students who scored high on avoidant learning
styles are more likely to consider that ability is not innate and the learning is acquired
gradually. However, they tended to believe that knowledge is certain and evident when it
comes to Biology. The significant correlation between the collaborative learning style and
certainty of knowledge and innate ability may mean that learners who scored high on this
kind of learning style believe that knowledge is constantly evolving and that whatever
knowledge they have in Biology is a result of continuous experience. Dependent learning
style had a tendency to believe that knowledge is complex and uncertain as a result of their
135
own experience and tended to believe less in omniscient authority. Competitive learning style
had highly significant correlation with the beliefs of innate ability and quick learning and
participant learning style has highly significant correlation with the simplicity and certainty
of knowledge.
Meanwhile, a highly significant relationship was noted in the learning styles of the
respondents, such as participant (r=0.266, p<0.01), and collaborative (r=0.217, p<0.01) and
the students’ performance in Biology. Respondents’ whose learning styles such as participant
and collaborative had the tendency to earn high grades. A significant but negative correlation
was noted between the students’ avoidant learning style (r= -0.288, p<0.01) and their
performance in Biology. This suggested that students who practice avoidant learning style
had the tendency to earn lower grade in Biology.
Correlational analysis showed that there was significant relationship between
epistemological beliefs and academic performance of students. Findings revealed that
certainty of knowledge exerted influence on the students’ performance in Biology.
Regression analysis showed that avoidant learning style (β = -0.277, p<.01) and
certainty of knowledge (β = 0.203, p<.05) were identified as predictors of academic
performance in Biology. On the other hand, hierarchical regression analysis revealed that
none of the moderating variables moderated the relationship between the learning styles and
academic performance. However, the test revealed that school location had a direct effect on
the students’ belief in certainty of knowledge and academic performance (β = -0.295, p<.01).
ICT had an indirect effect on the omniscient authority belief and academic performance of
students (β = 0.340, p<.01) and father’s educational attainment indirectly affected the
136
relationship between the students’ belief in innate ability and academic performance
(β = 0.307, p<.01).
The results of the study revealed that the students of the five high schools of CLSU
are primarily female and majority of the respondents were 14 years old. A total of 59.9% or
88 participants were from rural schools and they had access to information and
communications technology. Fathers were mostly high school graduates while mothers were
college graduates. Most of these fathers, 72.1% or 106 had blue collar jobs, mostly farming
and many of them had low family incomes (70.1% or 103). The mothers (43.5% or 64), on
the other hand, despite, the occurrence of higher level of education, were mostly college
graduates but remained at home to attend to household chores.
Conclusion
On the basis of the results of this study, the following findings were noted:
1. Most respondents had preference on collaborating with their classmates than
competing with them; respondents were also found to be more participative learners
than avoidant; however, they tend to be more dependent on their teachers and
classmates than being independent when it comes to school activities;
2. With regard to the overall epistemological beliefs, majority of the respondents had
emergent or mixed beliefs about the nature of knowledge and the process of acquiring
knowledge. Only a small number of respondents had sophisticated beliefs. Most
respondents had a relative sophisticated belief about “Quick Learning” which means
that they assumed that learning is of gradual process that changes over a period of
137
time. They exhibited naïve belief, on the other hand, with Omniscient Authority in
which case they mostly believed that the teachers are utmost authority or sources of
knowledge in learning Biology. In general, students exhibited less sophisticated
beliefs, specifically in Simple Learning, Omniscient Authority, Certain Knowledge
and Innate Ability;
3. Most of the respondents were average performing students in Biology;
4. Independent learning style had highly significant positive relationship with the
students’ belief in simplicity of knowledge and innate ability and significant
relationship with quick learning. Avoidant learning style had high positive correlation
with quick learning and innate ability and significant but negatively correlated with
the students’ belief in the certainty of knowledge. Collaborative learning style had
high positive correlation with the certainty of knowledge and significantly related
with innate ability. Dependent learning style had highly significant and positive
relationship with the students’ beliefs in the simplicity and certainty of knowledge
and omniscient authority and was significantly correlated with innate ability.
Competitive learning styles, on the other hand, was highly correlated with the innate
ability and quick learning beliefs and significantly correlated with simple knowledge
beliefs of the students. Finally, participant learning style had highly significant
correlations with the students’ belief in simplicity and certainty of knowledge and the
omniscient authority.
138
5. Respondents who have collaborative and participant learning styles would tend to
perform better in Biology while those who exhibit avoidant learning styles were
found to have lower achievement in Biology.
6. The respondents’ epistemological beliefs on certainty of knowledge had significant
relationship with their performance in Biology.
7. Avoidant learning style and certainty of knowledge were identified as predictors of
academic performance in Biology.
8. None of the moderating variables moderated the relationship of learning style and
academic performance.
9. Hierarchical regression analyses revealed that school location had direct effect on the
relationship of students’ beliefs in certainty of knowledge and academic performance
while ICT had indirect effect on the omniscient authority beliefs and academic
performance of students and father’s educational attainment indirectly affect the
relationship between the students’ beliefs in innate ability and academic performance.
10. Most of the respondents are female, who were mostly 14 years old who studied in
rural school and had considerable access to information and communications
technology. Most of them had fathers who were high school graduates whose jobs
were mainly farming. Their mothers, though, mostly reached collegiate level, were
plain housewives.
Recommendations
Based on the results of this study, the following recommendations are made:
1. Teachers, principals, and policy makers should give enough importance to developing
139
students’ epistemological beliefs and learning styles throughout their formal
education. Trainings and workshops that would promote mature epistemological
beliefs (sophisticated) and more positive learning styles (independent, collaborative
and participant) should be arranged by the teachers to help develop the skills of their
students.
2. Students’ epistemological beliefs and learning style may be assessed to help the
teachers in designing effective classroom activities.
3. Future studies should consider the teacher’s epistemological beliefs and teaching style
and the relationship of these to students’ epistemological beliefs and learning styles.
4. To further investigate the students’ learning styles and epistemological beliefs, the
use of other instruments which entail qualitative data that can be gathered using inter-
views and observation to substantiate the discussion on students’ epistemological be-
liefs is suggested. In addition, it is suggested that more appropriate approaches in ana-
lyzing data like structure equation modeling should be used.
5. Longitudinal studies can be conducted to examine the change of students’ epistemo-
logical beliefs. This is to see whether change in epistemological beliefs can lead to
better performance in Biology.
140
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APPENDICES
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APPENDIX A – Sample Questionnaire
Republic of the PhilippinesCENTRAL LUZON STATE UNIVERSITY
Science City of Munoz
INSTITUTE OF GRADUATE STUDIES
Epistemological Beliefs, Learning Styles and Academic Performance of Biology Students in Five High Schools of Central Luzon State University
General Direction: Please supply the information needed by putting a mark on the box or write down your answers wherever feasible.
Name: ____________________(optional) Year and Section_______ Code No. ______
Part I. SOCIO-DEMOGRAPHIC CHARACTERISTICS
Direction: Please supply the needed information by putting a check mark in the space provided before each statement or write down your answer(s) on the blank after each statement.
Age _________ Final grade in biology ______ Gender ( ) male ( ) female School Location ( ) rural ( ) urbanICT Accessibility ( ) accessible Family Income: ___________________
( ) non-accessibleParents’ Educational BackgroundFather: ( ) elementary graduate ( ) high school graduate ( ) college graduate ( ) college graduate with MA/MS units ( ) MS/MA graduate ( ) with Ph.D./EdD. units ( ) Ph.D/Ed.D. graduate
Mother: ( ) elementary graduate ( ) high school graduate ( ) college graduate ( ) college graduate with MA/MS units ( ) MS/MA graduate
( ) Ph.D./EdD. units ( ) Ph.D/Ed.D. graduate
Mothers’ Occupation Fathers’ Occupation
( ) farmer ( ) driver ( ) construction worker ( ) Overseas Filipino Worker ( ) nurse ( ) teacher
( ) farmer ( ) driver ( ) construction worker ( ) Overseas Filipino Worker ( ) nurse ( ) teacher
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( ) others please specify ______________________
( ) others please specify ______________________
Part II. EPISTEMIC BELIEF INVENTORY
Please indicate your level of agreement or disagreement to the following statements. If you strongly agree, for example, write the number 5 in the blank provided on the left.
strongly disagree
moderately disagree
undecided moderately agree strongly agree
1 2 3 4 5
________1. It bothers me when biology teachers don't tell students the answers to complicated biology problems.
________2. Truth in Biology means different things to different people.
________3. Students who learn things quickly in biology are the most successful.
________4. Students should always obey the law inside biology classroom.
________5. Some students in biology will never be smart no matter how hard they work.
________6. Absolute moral truth does not exist in biology.
________7. Teachers should teach their students all there is to know about biology.
________8. Really smart students don't have to work as hard to do well in biology.
________9. If a student tries too hard to understand a problem in biology, he will most likely end up being confused.
________10. Too many theories in biology just complicate things.
________11. The best ideas in biology are often the simplest ones.
________12. Students can't do too much about how smart they are in biology.
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________13. Biology teachers should focus on facts instead of theories.
________14. I like biology teachers who present several competing theories and let their students decide which is best.
________15. How well you do in biology depends on how smart you are.
________16. In biology, if you don't learn something quickly, you won't ever learn it.
________17. Some students in biology class just have a knack for learning and others don't.
________18. Some biology concepts are simpler than most biology teachers would have you believe.
________19. If two students are arguing about something in a biology class, at least one of them must be wrong.
________20. In a biology class, students should be allowed to question their teachers' authority.
________21. If you haven't understood a lesson in biology the first time through, going back over it won't help.
________22. Biology is easy to understand because it contains so many facts.
________ 23. The moral rules in Biology I live by apply to everyone in the class.
________ 24. In biology, the more you know about a topic, the more there is to know.
________ 25. What is true today in biology will be true tomorrow.
________ 26. Smart students in biology are born that way.
________ 27. When a biology teacher tells me what to do, I usually do it.
________ 28. Students who question biology teachers are trouble makers.
________ 29. Working on a problem in biology with no quick solution is a waste of time.
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________ 30. You can study biology concepts for years and still not really understand them.
________ 31. Sometimes there are no right answers to biology's big problems.
________32. Some students are born with special gifts and talents in biology.
Part III. LEARNING STYLES
Direction: The following questionnaire has been designed to help you clarify your attitudes and feelings toward learning in high school. There is no right or wrong answer to each question. However, as you answer each question, form your answer with regard to your personal attitudes and feelings towards Science subject.
Please respond to the items listed below by putting a check mark under the following scale:
Use a rating scale 1, if you strongly disagree with the statement.Use a rating scale 2, if you moderately disagree with the statement.Use a rating scale 3, if you are undecided with the statement.Use a rating scale 4, if you moderately agree with the statement.Use a rating scale 5, if you strongly agree with the statement.
Statement 1 2 3 4 51. I prefer to work by myself on assignments in my Biology class. 2. I often daydream during Biology class. 3. Working with other students on class activities is something I enjoy doing in my Biology class. 4. I want my Biology teacher to state exactly what he expects from the students. 5. To do well, it is necessary to compete with other students for my Biology teacher’s attention. 6. I do whatever is asked of me to learn in my Biology class. 7. My ideas about Biology lessons often are as good as those in the textbook. 8. Classroom activities in Biology are usually boring. 9. I enjoy discussing my ideas about Biology with other students. 10. I rely on my Biology teacher to tell me what is important for me to learn. 11. It is necessary to compete with other students to get a good grade in Biology class. 12. I find that Biology class is worth attending. 13. I study what is important to me and not always what
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my Biology teacher says is important. 14. I very seldom am excited about material covered in Biology. 15. I enjoy hearing what other students think about issues raised in Biology class. 16. I want clear and detailed instructions in Biology on how to complete assignments. 17. In Biology class, I must compete with other students to get my ideas across. 18. I get more out of going to Biology class than staying at home. 19. I learn a lot of Biology on my own. 20. I don't want to attend my Biology class. 21. Students should be encouraged to share more of their ideas with each other in Biology class.22. I complete assignments in Biology exactly the way my Biology teacher tells me to do them. 23. Students have to be aggressive to do well in Biology class. 24. It is my responsibility to get as much as I can out of my Biology class. 25. I feel very confident about my ability to learn on my own in Biology. 26. Paying attention during Biology class is difficult for me to do. 27. I like to study for tests in Biology with other students. 28. Trying to decide what to study or how to do assignments in Biology makes me uncomfortable. 29. I like to solve problems or answer questions in Biology before anybody else can. 30. Classroom activities in Biology class are interesting. 31. I like to develop my own ideas about Biology lesson. 32. I have given up trying to learn anything from going to Biology class. 33. Biology classes make me feel like part of a team where people help each other learn. 34. Students should be more closely supervised by Biology teachers in doing Biology projects. 35. To get ahead in Biology class, it is necessary to step on the toes of other students. 36. I try to participate as much as I can in all activities in Biology. 37. I have my own ideas about how Biology classes
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should be run. 38. I study just hard enough to get by in Biology. 39. An important part of studying Biology is learning to get along with other people. 40. My notes contain almost everything the teacher said in my Biology class. 41. Being one of the best students in my Biology class is very important to me. 42. I do all assignments in Biology well whether or not I think they are interesting. 43. If I like a topic in Biology, I try to find out more about it on my own. 44. I typically cram for exams in Biology. 45. Learning the lessons in Biology is a cooperative effort between students and teachers. 46. I prefer Biology lessons that are highly organized. 47. To stand out in my Biology class, I complete assignments better than other students. 48. I typically complete assignments in Biology before their deadlines. 49. I prefer to work on class projects and assignments in Biology by myself. 50. I would prefer that my Biology teacher ignores me in class. 51. I am willing to help other students out when they do not understand something in Biology. 52. Students should be told exactly what topics are to be covered on Biology exams. 53. I like to know how well other students are doing on exams and assignments in Biology. 54. I complete required assignments in Biology as well as those that are optional. 55. When I don't understand something in Biology, I first try to figure it out for myself. 56. During Biology class, I tend to socialize with people sitting next to me. 57. I enjoy participating in small group activities during Biology class. 58. I want Biology teachers to have outlines or notes on the board. 59. I want my Biology teacher to give me more recognition for the good work I do. 60. In my Biology class, I often sit toward the front of the room.
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APPENDIX B – Letter to the Principal
Republic of the PhilippinesCENTRAL LUZON STATE UNIVERSITY
Science City of Muñoz Nueva Ecija
INSTITUTE OF GRADUATE STUDIES
14 June 2010
Prof. MA. ROSIE S. MANANGAN School Principal, ULHS-PalusapisScience City of Munoz, Nueva Ecija
Madam:
The undersigned is a Master of Science in Biology Education student at the Institute of Graduate Studies in Central Luzon State University. He is due to conduct his research this coming school year entitled, Epistemological Beliefs, Learning Styles and Academic Performance of Biology Students in Five High Schools of Central Luzon State University as partial fulfillment of the requirements for masteral degree.
Relative to this, he would like to humbly request your office to allow him to distribute the survey questionnaires to the sophomore students in your school for SY 2009-2010. Rest assured that the information gathered will be kept confidential
Thank you and more power!
Sincerely yours,
JOHN PAUL E. SANTOS Researcher
Noted:
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EDEN S. DAVID, Ph.D. Thesis Adviser
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APPENDIX C – Sample of student’s permanent record
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APPENDIX D – Epistemological Beliefs and Learning StylesProfiles of respondents
Appendix Table 1. Epistemological beliefs held by the sophomore high school students in Biology
Epistemological BeliefFrequency(N=147)
Percentage%
Emergent 128 87.1Naive 17 11.6Sophisticated 2 1.4
Appendix Table 2. Learning styles of sophomore high school students
Learning StylesFrequency(N = 147)
Percentage%
Independent 12 8.2Avoidant 8 5.4Collaborative 49 33.3Dependent 31 21.1Competitive 10 6.8Participant 37 25.2
Appendix Table 3. Learning Style in High, Moderate and Low
Learning Style
High Moderate LowMean
Descriptive classificationf % f % f %
Independent 38 25.9 94 63.9 15 10.2 3.47 Moderate
Avoidant 42 28.6 101 68.7 4 2.7 2.92 Moderate
Collaborative 122 83.0 18 12.2 7 4.8 3.89 High
Dependent 49 33.3 90 61.2 8 5.4 3.77 Moderate
Competitive 131 89.1 16 10.9 - - 3.52 High
Participant 48 32.7 89 60.5 10 6.8 3.82 Moderate
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Appendix Table 4. Learning Style with their Mean, SD, Description and Rank
APPENDIX E - Tabular data of Respondents’ Socio-demographic characteristics Appendix
Table 5. Respondents’ Socio-demographic characteristics
CharacteristicsFrequency(N = 147)
Percentage%
Age13 15 10.214 102 69.415 29 19.718 1 0.7
Mean 14.12Std. Deviation 0.63
Range 13 – 18Gender Female 77 52.4 Male 70 47.6School location Rural 88 59.9 Urban 59 40.1ICT Accessibility Accessible 106 72.1 Non-accessible 41 27.9Father’s educational attainment Elementary level 10 6.8 High school level 57 38.8 College level 55 37.4 Graduate level 20 13.6 Vocational 5 3.4Mother’s educational attainment Elementary level 9 6.1 High school level 51 34.7 College level 64 43.5 Graduate level 22 15.0 Vocational 1 0.7Father’s occupation Blue collar job 106 72.1 White collar job 39 26.5 Non-earning 2 1.4Mother’s occupation Blue collar job 42 28.6 White collar job 40 27.2 Non-earning 65 44.2
Learning Style Mean SDDescriptive
classification%
(High + Mod)Rank
Independent 3.47 0.55 Moderate 89.8 6Avoidant 2.92 0.60 Moderate 97.3 2Collaborative 3.89 0.57 High 95.2 3Dependent 3.77 0.53 Moderate 94.5 4Competitive 3.52 0.52 High 100 1Participant 3.82 0.58 Moderate 93.2 5
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Family income Low family income 103 70.1 High family income 44 29.9
Mean 25957.82Std. Deviation 45551.93
Range 4,000 – 500,000GPA High academic performance (at least 88) 25 17.0 Average academic performance (80 – 87) 108 73.4 Low academic performance (below 80) 14 9.6
Mean 83.76Std. Deviation 3.870
Range 75 - 93