The Role of Cognitive Styles in Computer Programming Learning

Dyah Susilowati

, I Nyoman Sudana Degeng

, Punaji Setyosari

and Saida Ulfa

STMIK Bumigora Mataram, Mataram, Indonesia

Universitas Negeri Malang, Malang, Indonesia

Keywords: Cognitive Style, Computer Programming Learning, Data Structure.

Abstract: Cognitive style is one of the most important factors in determining the success of computer programming

learning. There are two characteristics of cognitive styles: field dependent and field independent. Cognitive

style in programming learning has been widely studied; however, there are no studies that discuss the relation

of cognitive style and data structure learning, which is an integral part of programming learning. This article

describes the results of an experiment that examine the differences in the characteristics of cognitive styles

(field dependent and independent fields) in Programming Algorithms and Data Structure. This study involves

118 students who take Programming course and 108 students who take Data Structure course in the

Informatics Engineering Study Program at STMIK Bumigora. Based on the research findings, there is a

significant difference between the dependent field and the independent field in both courses. The Computer

Programming teacher should take importance of cognitive styles during preparing their instructional

strategies.

1 INTRODUCTION

Cognitive style is defined as psychological constructs

related to how individuals process information

(Brown et al., 2006). Cognitive style can be referred

to type of differences owned by an individual that is

generally nurtured since childhood. Perception,

memory, attitude in the problem-solving process, and

ways of expression development of individual can be

seen through the style; however it has no significant

relation to intelligence quotient (Riding, Smith and

Sadler-smith, no date). Cognitive styles are classified

into field dependent and field independent (Witkin et

al., 1977). The classification of the cognitive style is

based on the acceptance and retention of concept. The

formation of concept relates to how data/information

are observed and analyzed, whereas concept

formation and retention relates to hypothesis

submission, problem solving, and memory process.

Research results state that cognitive style is

influential in the learning process and consequently

brings different learning outcomes.

Students have different cognitive styles that can

affect the learning process which consequently leads

to different learning outcomes. Teaching styles and

content level that well-suited with an individual’s

cognitive development and cognitive style will be

most successful. Therefore, students who take

computer programming courses will receive more

benefits by having prerequisite that make them to be

in a course that suitable with their cognitive

characteristics (White and Sivitanides, 2002).

Students placed in classes that best fit their cognitive

characteristics have a higher probability of success.

Furthermore, cognitive style is closely related to

instructional strategy (White et al., 1997; Oh and

Lim, 2005; Shi, 2011) and it also has correlation with

instructional strategy (Dowlatabadi and Mehraganfar,

2014; Science and State, 2015). In a study about the

relation between cognitive styles and instructional

strategy, Cognitive style significantly affects the

choice of instructional strategy (Shi, 2011). It means

that learners with field independent learning style

have bigger potential to succeed in computer

programming learning, while learners with field

dependent learning style needs additional support to

be able to learn computer programming. This claim

appears in a study conducted by (R. Mancy and Reid,

2004) suggesting that field independent cognitive

style is proven to be more effective than field

dependent.

In studying computer programming there are two

important courses that cannot be separated, namely

Programming Algorithm and Data Structure. In order

216

Susilowati, D., Degeng, I., Setyosari, P. and Ulfa, S.

The Role of Cognitive Styles in Computer Programming Learning.

DOI: 10.5220/0008410102160220

In Proceedings of the 2nd International Conference on Learning Innovation (ICLI 2018), pages 216-220

ISBN: 978-989-758-391-9

to learn about the fundamentals of data structures and

algorithms approaches used in software design and

development, computer programming students

require to take data structures and algorithms course

since it is an essential foundation course in computer

science. In addition to be used in software design and

development, basic data structures and algorithms are

also used to solve various problems in computer

science fields (Liu, Wang and Wang, 2013). Data

structures are important because they are the most

important tool that is going to be directed by a

programmer. By knowing the use of each data

structure as well as its weakness and strengths the

programmers could solve problems effortlessly.

Several studies related to cognitive style and

computer programming have been carried out;

however, there are no studies that examine the

influence of cognitive style on learning outcomes of

data structures. Therefore, this study aims to identify

the influence of cognitive style on learning outcomes

of programming algorithm and data structure. The

following research hipotesis will been tested

 There is a significant difference in

programming algorithms learning outcome of

students with different cognitive styles

 There is a significant different in data structure

learning outcome of students with different

cognitive styles

2 METHOD

The research was a descriptive correlational research

aimed to describe the correlation between cognitive

style and students’ learning outcomes in

Programming Algorithm and Data Structure courses.

There were two variables observed, cognitive styles

as the independent variable and learning outcomes as

the dependent variable.

The research subjects were students of

Informatics Engineering Study Program at STMIK

Bumigora Mataram consisted of 181 students

participated in the Programming Algorithms course

semester of the first year) and 108 students

participated in Data Structures course (2

semester of

the first year).

The instrument used in the research was Group

Embedded Figure Test (GEFT) cognitive style test

adopted from (Witkin et al., 1977) and post test. The

measurements of learning outcome were done using

comprehension test on programming algorithm and

data structure developed by the lecturer.

Comprehension test was in form of essays test.

Data collection was carried out with cognitive

style tests on students who took Programming

Algorithms and Data Structures courses. In the

following stage, the research also collected the post

test scores in Programming Algorithm and Data

Structure.

Data tabulation was conducted and followed by t-

test using SPSS to test the following hypothesis:

= the average score of students with FI

cognitive style and the average score of students with

FD cognitive style is identical

= the average score of students with FI

cognitive style and the average score of students with

FD cognitive style is not identical

The testing criteria are as follows:

 H

is accepted and H

is rejected if probability

(Sig.) > 0.05

 H

is rejected and H

is accepted if probability

(Sig.) < 0.05

3 RESULT AND DISCUSSION

To find out the influence of cognitive style on the

learning outcome, a statistical analysis was conducted

to obtain a difference in mean score between students

with field dependent (FI) and field dependent (FD)

cognitive styles in Programming Algorithms and

Data Structures courses. The result of the analysis can

be seen in Table 1 and Table 2 for Programming

Algorithms and Data Structures courses, respectively.

Table 1: Mean scores of programming algorithms based on

cognitive style group statistics.

Cognitive

Style

Mean

Std.

Deviation

Std.

Error

Mean

Programming

Algorithms

Score FD

92.8879

82.0833

14.07064

19.02923

1.84757

2.45666

It can be seen in Tables 1 that the mean score of

students with field independent (FI) cognitive style

(92.88) was higher than the mean score of students

with field dependent (FD) cognitive style (82.08),

both in Programming Algorithms and Data

Structures. Therefore, it can be concluded that

students participating in Programming Algorithms

who had field independent cognitive style could

achieve better learning outcomes than students who

had field dependent cognitive style.

The Role of Cognitive Styles in Computer Programming Learning

217

Table 2: Mean scores of data structures based on cognitive

style group statistics.

Cognitive

Style

Mean

Std.

Deviation

Std.

Error

Mean

Data

Structures

Score

86.5196

77.6316

15.58107

19.44211

2.18179

2.57517

Based on data analysis in Table 2, it can be

concluded that the mean score of students with field

independent cognitive style was higher (88.51) than

the mean score of students with field dependent

cognitive style (77.63). Therefore, students

participating in Data Structure course who had field

independent cognitive style could achieve better

learning outcomes than those who had field

dependent cognitive style.

Hypothesis testing was conducted using t-test in

order to find out whether or not the average score of

students with the FI cognitive style and the average

score of students with FD cognitive style is identical.

The result of hypothesis testing for Programming

Algorithm and Data Structures Courses is presented

in Table 3 and 4, respectively.

Based on Table 3, it can be concluded that H1 was

accepted since the sig. Value (0.001) < 0.05. It means

that both data had non-identical average (significantly

different). The Algorithm average value of students

with field independent cognitive style (92.8879) was

higher than that of students with field independent

cognitive style (82.0833).

Based on Table 4, it can be concluded that H1 was

accepted since the sig. Value (0.011) < 0.05. It means

that both data were non-identical average

(significantly different). The Data Structure test’s

mean score of students with field independent

cognitive style (86.5196) was higher than those

students with field dependent cognitive style

(77.6316).

This finding is in line with the findings of (Ford,

Miller and Moss, 2001) confirmed that cognitive style

has influence on learners’ learning outcomes. The

finding also supports a claim that students should

have the needed cognitive style to succeed in

programming (White and Marcos, 2012) and that

programming learning needs some prerequisites

(White, 2007). Furthermore, this finding is in line

with the finding of (Rebecca Mancy and Reid, 2004)

stated that working memory space had a marginal

influence on levels of achievement on the course,

whereas field dependency become an essential

success determinant factor.

Table 3: T-test result independent samples test.

Algorithm Score

Lavene’s Test

for Equality of

Variances

t-test for Equality of Means

Sig

(2-

tailed)

Mean

Difference

Std. Error

Difference

95% Confidence

Interval of the

Difference

Lower

Upper

Equal variances

assumed

Equal variances

not assumed

4.800

.030

3.497

3.515

116

108.641

.001

10.80460

3.08931

3.07387

4.68583

4.71206

16.92336

16.89714

Table 4: T-test result independent samples test.

Data Structures

Score

Lavene’s Test

for Equality

of Variances

t-test for Equality of Means

Sig

(2-

tailed)

Mean

Difference

Std. Error

Difference

95% Confidence

Interval of the

Difference

Lower

Upper

Equal variances

assumed

Equal variances not

assumed

11.06

.001

2.601

2.633

106

104.78

.011

.010

8.88803

3.41664

3.37516

2.11421

2.19555

15.6618

15.5805

ICLI 2018 - 2nd International Conference on Learning Innovation

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The research finding proved the cognitive style

theory. Cognitive style is a characteristic self-

consistent mode of functioning which individuals

show in their perceptual and intellectual activities as

well as the two dimensions of FI and FD cognitive

styles (Witkin et al., 1977). The finding of this study

indicated that students with field independent

cognitive style were better in programming and data

structure learning abilities compared to student with

field dependent cognitive style. It was due to students

with field independent cognitive style have a good

analytical ability, which is an ability to view

information and perception as a separated part of its

surrounding context as well as to compile and

assimilate them. FI students have a tendency to be

smarter and faster in looking for problem solving

alternatives. Students are required to have various

abilities during computer programming learning,

such as, ability in analysis, logic, mathematics,

problem solving, and programming language syntax

(Sarpong and Arthur, 2013). In addition,

programming is a complicated process with various

stages and different content knowledge as well as

cognitive processes would be required for each sub

process (Ambrósio et al., 2011). Therefore, it will

require a strong analytical ability and this ability

owned by students with field independent cognitive

style. Students with field dependent cognitive style,

on the other hand, have a tendency to face difficulty

in separating a concept or perception from its

surrounding context thus information acceptance is

unclear and difficult to be assimilated. Therefore,

students with field dependent cognitive style tend to

face difficulty in problem solving process. The

condition is likely to be the cause of students with

field dependent cognitive style would need more hard

work and extra time in computer programming

learning process compared to students with field

independent cognitive style. The research result is in

line with previous research results stated that students

with field independent cognitive style are better at

identifying and representing problems (Rebecca

Mancy and Reid, 2004b). In addition, another

research result also stated that the learners with field-

independent cognitive style outperformed those with

field-dependent cognitive style (Lu and Lin, 2018)

Considering the significant role of student

cognitive style in computer programming learning, an

appropriate learning strategy plan is needed that

accommodates student cognitive style to achieve

learning objectives. Teacher/learners of computer

programming should identify student cognitive style

in the beginning of learning that subsequently can be

used as one of bases to compile an appropriate

learning strategy thus learning objectives can be

achieved optimally. It is in line with previous research

stated that teaching styles and content level that well-

suited for an individual’s cognitive development and

cognitive style will be most successful. Therefore,

students who take computer programming courses

will receive more benefits by having prerequisite that

make them to be in a course that suits their cognitive

characteristics (White et al., 1997). Due to resources

limitation, class division based on cognitive style

group is hard to obtain. A specific method should be

considered for students with FD cognitive style along

with specific time service for assistance outside the

classroom. The use of flowchart in programming

learning process could be an alternative to facilitate

students with field dependent cognitive style in

computer programming learning process.

Considering the work pattern of computer science

graduates that mostly work in a team and in response

to twenty-first century learning and skill, learners

could implement group assignment (group

programming). The formation of work group should

be consisted of students with different cognitive style

(there are students with field dependent and field

independent cognitive styles in one group). It is in

line with previous research result stated that scholars

found that a heterogeneous group that consisted of

learners with field independent and field dependent is

significantly better in performance compared to those

groups that divide based on other methods (Gagné

and Gagné, 2009). The grouping pattern is expected

to give mutual benefit among individuals in a group.

Based on the previous research, learners with field-

independent cognitive style had less active discussion

messages but more passive responses. When the

learners with field-independent cognitive style

assisted others to complete the task, they can also

benefit by it (Lu and Lin, 2018). Students with

independent cognitive style who have strong

analytical ability in problem solving could share in

the learning process. On the other hand, students with

dependent cognitive style who like to socialize and

make friends tend to be more active in discussion.

4 CONCLUSION

Based on the research findings, it can be concluded

that students with field independent cognitive style

were superior in computer programming learning

than those with field dependent. Therefore, it can be

suggested to the lecturers of computer programming

that they should pay attention to student’ cognitive

style in formulating instructional strategies in order to

The Role of Cognitive Styles in Computer Programming Learning

219

improve the learning process, especially for students

with field dependent cognitive style.

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