The Effect of Learning Styles on Students’ Metacognitive Skills
Stany Tiara Mulyawati, Yuniyarti Ahiri, Mia Aulia, Fury Indra Pratiwi and Ining Mukaromah
Universitas Pendidikan Indonesia, Jalan Setiabudhi 229 Bandung, Jawa Barat, Indonesia
Keywords: Learning Styles, Metacognitive Skill.
Abstract: The facts show that there is low metacognitive skill in grade VIII of junior secondary school 10 Kendari
(Southeast Sulawesi). This case was marked by learning process which is focused on concept mastery rather
than developing high-level thinking potential. The purpose of research is to review the effect of learning styles
on students’ metacognitive skill in economic. This research applied descriptive and verification method. The
data were analyzed using simple regression on SPSS 21.0. The data were gathered from 68 students of grade
VIII of Junior Secondary School 10 Kendari as the sample of the research with was taken randomly from 215
total number of population. The result of this research which is supposed to test the hypothesis reveals that
that there is any correlation between learning style with metacognitive skill; the regression equation is Ŷ =
54,320 + 0,595X and coefficient correlation is 0,713, and it gives strong correlation. According to the result
of this research that learning style can be increasing student’s metacognitive skill.
1 INTRODUCTION
Education is a very important need for the life of
society in general, so it cannot be denied that all the
progress that is obtained now is the result of the
educational process. The problem of education in
learning so far shows that there are many lessons that
use the memorization system and do not have the
meaning of learning so that the learning process is
perceived not to empower students through
metacognitive ability (Shen & Liu, 2011:2).
To Improving metacognitive skills to be an
important impact in the learning process because the
learning process can be said to be quality if students
are consciously able to control the cognitive process
that impact on learning outcomes (Wang, Haertel, and
Walberg, 1990 in journal (Bahri & Corebima, 2015:2;
Kristiani, Susilo, 2015:2; Shen & Liu, 2011:1)) and
student achievement (Coutinho & Neuman, 2008:2),
(Young dan Fry, 2008 in (Yunlu & Clapp-Smith,
2014:5)).
The approach used in addressing metacognitive
problems is John Hurley Flavell’s theory (Flavell,
Shipstead, & Croft, 1980). Flavell 1979 explains that
metacognitive is influenced by learners (self), tasks,
strategies. Kanfer & Ackerman's theory (Kanfer,
Ackerman, & Cudeck, 1989) explains that
metacognitive is influenced by intelligence,
motivation, age, and self-efficacy.
Theory of Albert Bandura (Bandura, 1991),
(Bandura, 1986, 1997 in (Pintrich, R. Paul, 2003: 43))
explains that metacognitive is influenced by self-
efficacy and motivation. Theories of Gregory Schraw
and David Moshman (Schraw & Moshman, 1995:
363) explain that metacognitive is influenced by
learning styles, learning motivation, learning culture,
individual construction, and peer interactions.
Caliskan & Sunbul (2011: 152) in their studies at
high school in Turkey found that learning styles affect
the metacognitive skills of learners. As a result
emotional intelligence and learning styles are
disrupted because students are less aware of
metacognitive skills that exist in themselves. The
purpose of research is to review the effect of learning
styles on students’ metacognitive skill in economic.
2 METHODS
Research design is a causal survey that applied
descriptive and verification with simple regression
techniques. The population of this research consist of
215 student (grade VIII of Junior Secondary School
10 Kendari) and the sample of this research, which
was randomly taken from the population consisted of
662
Mulyawati, S., Ahiri, Y., Aulia, M., Pratiwi, F. and Mukaromah, I.
The Effect of Learning Styles on Students’ Metacognitive Skills.
In Proceedings of the 2nd International Conference on Economic Education and Entrepreneurship (ICEEE 2017), pages 662-665
ISBN: 978-989-758-308-7
Copyright © 2017 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

68 students. The data were collected using
metacognitive scale and learning style scale. The data
were analyzed using simple regression on SPSS 21.0.
Hypothesis in this research is there direct influence of
learning styles to metacognitive skills in grade VIII
of Junior Secondary School 10 Kendari (Southeast
Sulawesi).
3 RESULTS AND DISCUSSION
3.1 Results
There is a direct influence of learning style to the
students' metacognitive skills of Grade VIII of Junior
Secondary School 10 Kendari. To test the hypothesis
of this research, a simple regression analysis was used
to see the relationship between the two variables,
learning style (X) with students' metacognitive skills
(Y) and to see the correlation of the two variables was
done by simple correlation analysis.
The test results were performed using SPSS 21 for
Windows program. To see the regression coefficients
can be presented in the following table:
Table 1: Coefficients simple regression analysis results.
The simple regression equation obtained from
the coefficients table of the simple regression model
between the learning style variables (X) and the
students 'metacognitive skills (Y) is: = 54.32 + 0.6X,
it means that any increase for 1 in learning style score
will increase the score of the students' metacognitive
skills equal to 0,6 at constant 54,32.
Furthermore, to test the significance of the above
regression can be seen in ANOVA table result of
output of SPSS 21 for Windows follows.
Table 2: ANOVA simple linear regression analysis results.
From the ANOVA table above, with the F test,
obtained significant value <α = 0.05, which means the
regression coefficient = 54.32 + 0.6X significant.
This suggests that the regression of metacognitive
skills over learning styles is significant and their
relationships are linear. Thus, the learning style is one
of the predictors of students' metacognitive skills.
The simple correlation analysis between learning
style variables (X) and students' metacognitive skills
(Y) was performed using the SPSS 21 for Windows
program. The results of the correlation analysis of the
two variables above are shown in the following table:
Table 3: Simple correlation test result.
From the results of simple correlation analysis
obtained correlation coefficient value of
metacognitive skills with student learning style of
0.713. The value of sig 0,000 <0.05 H
0
is rejected.
This means that any learning style score can be
used to predict the students' metacognitive skills
score. This result implies that learning styles is
affected by student metacognitive skills by 50,8%
while the remaining 49,2% influenced by other
factors not examined by the authors in this study.
Standardied
Coefficiens
B Std. Error Beta
Constant 54,32 9,40 5,78 0,000
X 0,60 0,07 0,713 8,25 0,000
a. Dependent Variable: Y
Coefficients
a
Model
Unstandardized
Coefficients
T
Sig.
1
Sum of
Squares
f
Mean
Square
F Sig.
Regression 3715,52 1 3715,52 68,1
0,000
a
Residual 3599,34 66 54,54
Total 7314,87 67
a. Predictors: (Constant), X
b. Dependent Variable: Y
ANOVA
b
Model
1
X Y
X Pearson Correlation 1 0,713**
Sig. (2-tailed) 0,000
N 68 68
Y Pearson Correlation 0,713** 1
Sig. (2-tailed) 0,000
N 68 68
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
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663

3.2 Discussion
The causal relationship between learning styles and
metacognitive skills can be shown by significant
correlation coefficients and regression coefficients.
The result of significance test on correlation shows
that the relation between learning styles with
metacognitive skills of students is significant. The
result of regression coefficient test shows that
learning style has direct effect to students'
metacognitive skill. It means that learning style is one
of the predictors of students' metacognitive skills. In
other words, a qualified learning style will improve
students' metacognitive skills.
According to Hyland (2005: 43), learning styles
perceptual dimension is a person's tendency to learn
through the sense of sight (visual), or auditory
(auditory, or touch (kinesthetic). According to
Misbach (2010: 80-82), each of the learning styles
consists of three types, namely: (1) visual type: visual
text (more focus on letters, numbers, symbols, object
and visual images (2) auditory type: auditory
linguistics (likes grammar, vocabulary, and
interesting stories) and auditory music (happy to hear
the tone, rhythm, and melodies); (3) kinesthetic types:
kinesthetic type body (movement) that tend to
practice operational motion of dexterity and body
dexterity, and kinesthetic touch types that tend to
touch of an object (fine motor).
Linvingston (1997: 43) states that metacognitive
is a form of the ability to look at oneself so that what
he does can be controlled optimally. Students who
have metacognitive skills in being able to solve a
problem use metacognitive strategies in solving a
problem. Anderson and Krathwohl (2001: 43) state
that metacognitive is the knowledge of cognition, in
general the same as awareness and knowledge about
one's self cognition. Hence it can be said that
metacognitive is an awareness of what is known and
what is unknown.
This finding is in line with the results of a study
conducted by Gogus and Gunes (2007: 599) who
found out that students' understanding of their own
learning styles can affect awareness of their own
learning abilities (metacognitive skills) which can
further contribute to their responsibilities in learning.
This happens because students need a cognitive
strategy in learning, which is self-management. This
cognitive strategy works well if students know what
they can do in learning. Theories Gregory Schraw and
David Moshman (Schraw & Moshman, 1995: 363)
explain that metacognitive is influenced by learning
styles, learning motivation, learning culture,
individual construction, and peer interactions.
4 CONCLUSIONS
The result of learning styles has direct affect to
students’ metacognitive skill. It means that learning
style is one of the predictors of students’
metacognitive skill. In Other words a qualified
learning style will improve students’ metacognitive
skill in Junior Secondary School 10 Kendari
(Southeast Sulawesi).
REFERENCES
Anderson, O.W., & Krathwohl, D.R., 2001. Taxonomy for
Learning, Teaching, and Assessing. A Revision of
Bloom’s Taxonomy of Educational Objectives. New
York: Addison Wisley Longman, Inc.
Bahri, A., & Corebima, A. D., 2015. The contribution of
learning motivation and metacognitive skill on
cognitive learning outcome of students within different
learning strategies. Journal of Baltic Science
Education, 14(4), 487–500.
Caliskan, Muhittin and Ali Murat Sunbul. 2011. The
Effects of Learning Strategies Instruction on
Metacognitive Knowledge, Using Metacognitive Skills
and Academic Achievement (Primary Education Sixth
Grade Turkish Course Sample). Journal of Educational
Sciences: Theory & Practice. 11(1): 148-153.
Coutinho, S.A, Neuman, G., 2008. A model of
metacognition, achievement goal orientation, learning
style and self-efficacy. Learning Environ Res.
Duniosky, J., & Hertzog, C., 1998. Training programs to
improve learning in later adulthood: Helping older
adults educate themselves. In D. J. Hacker, J.
Duniosky, & A. C. Graesser (Eds.), Metacognition in
educational theory and practice (pp. 249- 276).
Mahwah, NJ: Edbaum.
Dunning, D., Johnson, K., Ehrlinger, J., & Kruger, J., 2003.
Why people fail to recognize their own incompetence.
Current Directions in Psychological Science, 12, 83–
87.
Fisher, A., 2003. Critical Thinking: An Introduction.
Cambridge: Cambridge University Press.
Flavell, J, H., 1979. Metacognition and Cognitive
Monitoring: A New Area of Cognitive–Developmental
Inquiry. American Psychologist, 34(10), 906–911.
Flavell, J. H., Shipstead, S. G., & Croft, K., 1980. What
young children think you see when their eyes are
closed. In Cognition (pp. 369–387).
Gogus, A. & Gunes, H., 2007. Learning Style and Effective
Learning Habits of University Students: A Case from
Turkey. Center for Individual and Academic
Development (CIAD). Sabanci University: Istanbul,
Turkey.
Hyland, K., 2005. Second Language Writing. Cambridge:
Cambridge University Press.
Jiménez, V., Puente, a, Alvarado, J. M., & Arrebillaga, L.,
2009. Measuring metacognitive strategies using the
ICEEE 2017 - 2nd International Conference on Economic Education and Entrepreneurship
664

reading awareness scale ESCOLA. Electronic Journal
of Research in Educational Psychology, 7(2), 779–804.
Kanfer, R., Ackerman, L. P., & Cudeck, R., 1989. Abilities
Motivation Methodology. Abilities Motivation
Methodology.
Kruger Justin and David Dunning. 1999. Unskilled and
unaware of it: How Difficulties in Recognizing One’s
Own Incompetence Lead to Inflated Self-Assessments.
Journal of Personality and Social Psychology, 77 (6):
1121-1134.
Listiana, L., Susilo, H., Suwono, H., & Suarsini, E., 2016.
Empowering Students’ Metacognitive Skills Through
New Teaching Strategy (Group Investigation Integrated
With Think Talk Write in Biology Classroom. Journal
of Baltic Science Education, 15(3), 391–400.
Livingston, J.A., 1997. Metacognition: An Overview.
http://www.gse.buffalo.edu/fas/shuel/cep564/metacog.
htm (Diakses 22 Maret 2015).
Misbach, Ifa H. 2010) Dahsyatnya Sidik Jari: Menguak
Bakat & Potensi untuk Merancang Masa Depan
Melalui Finger Print Analysis. Jakarta: Visimedia.
Ninik Kristiani and Herawati Susilo. 2015. The
contribution of students’ metacognitive skills and
scientific attitude towards their academic achievements
in biology learning implementing Thinking
Empowerment by Questioning (TEQ) learning
integrated with inquiry learning(TEQI).Journal of
Educational Policy Research and Review, 2 (9): 113-
120.
Pintrich. R. Paul, S. M. G. 2003. Intentional Conceptual
Change. Lawrence Erlbaum Associates, Inc.,
Publishers.
Raes, A., Schellens, T., De Wever, B., & Benoit, D. F.
2016. Promoting metacognitive regulation through
collaborative problem solving on the web: When
scripting does not work. Computers in Human
Behavior, 58, 325–342.
Schraw, G., & Moshman, D. 1995. Metacognitive theories.
Educational Psychology Review. 7, 351–371. New
York: JSTOR.
Shen Shujun and Fawang Liu. 2011. Numerical
approximations and solution techniques for the space-
time Riesz–Caputo fractional advection-diffusion
equation. Numer Algor (56): 383 – 403.
Yunlu Dilek Gulistan and Rachel Clapp-Smith. 2014.
Metacognition, cultural psychological capital and
motivational cultural intelligence. Cross Cultural
Management. 21 (4): 386-399.
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