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365
Yildiz E. P., Alkan A., & Tezer M. (2025). Enhancing Early Childhood Students’ Computational Thinking Competency Through
Digital Game-Based Learning, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE),
13(2), 365-378.
Original scientific paper
Received: May 17, 2025.
Revised: July 21, 2025.
Accepted: July 31, 2025.
UDC:
37.091.39:004.9
159.955.6-057.874
10.23947/2334-8496-2025-13-2-365-378
© 2025 by the authors. This article is an open access article distributed under the terms and conditions of the
Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
*
Corresponding author:
murat.tezer@neu.edu.tr
Abstract: This study investigated how the computational thinking competencies of students classified in the early
childhood category can be developed through digital game-based learning. Computational thinking is a way of thinking
that includes problem solving, algorithmic thinking and logical inference skills is considered an important competence that
should be acquired at an early age. Digital game-based learning stands out as a powerful tool for developing computational
thinking skills while providing a fun and motivating environment by ensuring the active participation of students. Within the
scope of the research, the effects of digital game-based learning activities on students’ computational thinking skills were
examined by experimental method, one of the quantitative research methods. In this study, a 4-week training activity was
conducted for the experimental and control groups determined during the research process to develop computational think-
ing skills in 5-year-old pre-school children. The study group consists of 50 students in the 5-year-old age group studying in
the pre-school class of a state institution. In the study, student groups were divided into experimental and control groups.
The experimental and control groups consisted of 25 students. The achievement test prepared for the cognitive domain was
used as a pre-test and post-test as the data collection tool. In addition to this data collection tool, an evaluation rubric was
also used in the study. The findings showed that digital game-based learning methods positively affect the development of
computational thinking skills in early childhood. In light of these findings, recommendations were made in the study for the
integration of digital games into relevant educational programs and the promotion of computational thinking at an early age.
Keywords: digital game-based learning, computational thinking, early childhood, experimental method.
Ezgi Pelin Yildiz
1
, Ayşe Alkan
2
, Murat Tezer
3*
1
Kafkas University Kazım Karabekir Vocational School of Technical Sciences Department of Computer Technology, Turkey,
e-mail:
yildizezgipelin@gmail.com
2
Samsun Provincial Directorate of National Education, Turkey, e-mail:
ayshe_alkan@hotmail.com
3
Near East University Faculty of Arts and Sciences Department of Mathematics, Cyprus, e-mail:
murat.tezer@neu.edu.tr
Enhancing Early Childhood Students’ Computational Thinking
Competency Through Digital Game-Based Learning
Introduction
The early childhood period, which covers the age range of 0-6, is a critical period in which the cogni-
tive, social and emotional development of individuals is based. Skills acquired during critical periods affect
children’s future learning processes and academic success. Therefore, it is of great importance to imple-
ment such effective learning methods at an early age. During this period, children show rapid change in mul-
tiple areas of cognitive development (Bakioglu and Karamustafaoglu, 2022). It is important to organize the
educational materials prepared for children in this age group in accordance with their developmental areas
in order to create an environment that includes stimuli for learning experiences (Can Yasar and Aral, 2010).
Early childhood is a period in which the brain develops rapidly. During the cognitive development
process, children gain skills such as acquiring knowledge, using language appropriately, reasoning, and
problem solving (Gardiner and Garner, 2010). According to related research, state that in order to support
the cognitive development of children, presenting appropriate content or organizing educational materials
in line with the thoughts, hypotheses, and solution suggestions they put forward is of great importance for
their cognitive development (Yıldız and Zengin, 2021).
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Yildiz E. P., Alkan A., & Tezer M. (2025). Enhancing Early Childhood Students’ Computational Thinking Competency Through
Digital Game-Based Learning, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE),
13(2), 365-378.
In another study, it was stated that environmental richness can be created through play to support
cognitive development in children (
Fisher et al., 2018). Other research emphasizes that games play an
important role in the emotional, linguistic, social, physical, and especially cognitive development of chil-
dren (Yavuzer, 2010).
The 21st century is a period in which digitalization has accelerated and can be called the computer
age. In this age, it is becoming increasingly important for individuals to develop the ability to think with
computer logic and acquire programming skills. It has developed the computational thinking skill that
the logical functioning of computers can also affect humans. Acquiring computational thinking skills and
applying them in daily life stands out as a great necessity for individuals. According to related research,
states that programming or computer skills are not needed specifically for computer scientists (Wing,
2008). In other research, also define computational thinking as a type of logical thinking that everyone
has (Kim et al., 2013). In addition, it is stated that cognitive thinking skills, which are shown among the
21st century skills, include basic competencies such as algorithmic thinking and problem solving expected
from individuals (Tezer et al., 2024).
In the century we are in, technological developments have also created radical changes in the
game of playing. The proliferation of digital platforms has enabled children to move from traditional games
to digital games that they interact with through electronic devices. This process has changed both chil-
dren’s understanding of entertainment and their social relationships. The increasing popularity of digital
games in all age groups indicates that they have positive effects on children’s development (Talan and
Kalınkara, 2020). It is stated that digital games have the potential to provide a more interesting learning
environment and support learning by structuring learning processes, as well as having positive effects
on cognitive skills such as reasoning, critical thinking, problem solving, and ensuring the permanence
of learning (Granic et al., 2014; Guntepe and Donmez, Usta, 2017; Li et al., 2020). According to other
research, digital games improve children’s skills such as planning, problem solving, observation, math-
ematical thinking, hypothesizing and testing, creativity, and collaborative learning (Gozum and Kandır,
2021). Another research stated that the correct use of technology by children in the pre-school period can
have positive effects, improve their creativity and contribute to their self-confidence (Haugland, 2000).
The concept of computational thinking, first put forward by Wing (2006), includes ways of solving
problems, designing systems, and understanding human behavior. Computational development in early
childhood includes children’s skills in problem solving, logical thinking, decision making, and participation
in creative processes. Utilizing common points between digital games and computational thinking can
contribute to this development process. That games help children develop problem-solving strategies,
support algorithmic thinking skills, and establish logical connections (Bers, 2018).
Computational thinking includes the skills to analyze complex problems, develop solution strate-
gies by breaking these problems into smaller pieces, create algorithms, and optimize solution processes.
That the challenges encountered in games are similar to the basic principles of computational thinking,
where players systematically take the problem-solving process and try various solutions by (Shute et
al., 2017; Wing, 2006), states that overcoming an obstacle encountered in the game requires the player
to solve this obstacle by dividing it into smaller sub-parts and establishing relationships between these
parts, which is one of the basic principles of computational thinking. Additionally, the repetitive experience
and opportunities to learn from failure that games offer are very similar to the trial-and-error processes
encountered in computer programming. In this case, computer games can be considered as tools that
provide players with the basics of computational thinking in a fun and interactive way.
A quasi-experimental research design with a pretest-posttest control group was used for this study.
The study group consisted of sixth-grade middle school students. Lessons were conducted for the ex-
perimental group using a BID block-based coding tool. The results show that the experimental group had
much higher mathematics achievement than the control group (
Top and Arabacıoglu, 2024).
In this study, the Bee-Bot application was preferred for early childhood robotic coding education.
Bee-Bot is an educational robot specifically designed to develop preschool children’s algorithmic thinking,
understanding of directional concepts, problem-solving, and sequencing skills. Its physical structure and
ease of programmability support children’s learning through concrete experiences. However, the literature
also includes other robotic tools that can be used in early childhood education. For example, Doc Robot,
developed by the company Clementoni, is another educational robot that similarly aims to enhance chil-
dren’s coding-based thinking skills. In addition to fostering logical thinking, directional awareness, and
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Yildiz E. P., Alkan A., & Tezer M. (2025). Enhancing Early Childhood Students’ Computational Thinking Competency Through
Digital Game-Based Learning, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE),
13(2), 365-378.
problem-solving, Doc Robot is designed to teach basic concepts such as letters, numbers, colors, and
animals (dikkatatolyesi.com, turascandinavia.com). Notably, its “smart mode” feature allows the robot to
recognize its position on game cards and provide children with various tasks, making the learning process
more interactive. In this context, Doc Robot, like Bee-Bot, is a programmable educational tool suitable
for preschool use and offers an alternative depending on the goals and conditions of implementation.
However, in this study, Bee-Bot was deemed a more appropriate choice considering the targeted learning
outcomes and the practical conditions of the application.
Related Research
A game was designed by (
Zhao, 2017), that includes the basic elements of computational thinking,
such as problem solving, abstraction, algorithmic thinking, conditional logic, iterative thinking, and debug-
ging. The results of the study revealed that students showed a significant increase in their computational
thinking skills after playing the game for less than two hours. As a result of the study conducted by (Ciftci
et al., 2018), it was revealed that digital games have positive effects on programming self-efficacy, com-
putational thinking, reflective thinking about problem solving and the ability to follow developments in the
field of computers. Investigated the effects of educational games on students’ basic knowledge of object-
oriented programming and computational thinking skills. According to the findings of the study, the devel-
oped educational digital game contributed to the students’ learning the basic concepts of object-oriented
programming and developing their computational thinking skills, were presented by Akkaya (2018).
In their research to determine at which education levels digital games can be used, Aksoy (2021)
stated that digital games can be used at all levels of education, but they are more suitable, especially for
younger age groups. In other research, the effects of science teaching with educational digital games and
in-class educational games on the cognitive development levels of pre-school students were examined
(
Yıldız and Zengin, 2021
). At the end of the research, it was revealed that the relevant methods were
effective in increasing the cognitive development of pre-school students. In this study (Aksoy, 2021), the
views of pre-school teachers on the use of technology in education were examined. According to teachers,
technological educational tools contribute to language and cognitive development, while also increasing
students’ interest in learning and supporting the permanence of information. This shows that technology is
more than just a tool; it can play an active role in pedagogical processes. Especially in early childhood, the
use of such tools can help make learning more fun and engaging. examined the effects of science courses
conducted through educational digital games on students’ knowledge retention, academic achievement,
and attitudes. As a result of the research, it was concluded that science courses conducted through educa-
tional digital games positively increased the cognitive development levels of students (Agırgol et al., 2022).
Examined the effects of a digital game-based education program on the phonological awareness
skills of 60-72-month-old children. The research results revealed that the children in the study group
showed a significant improvement in their phonological awareness skills in the pre-test and post-test com-
parisons. Additionally, according to the post-test results, it was found that the experimental group scored
higher than the control group. These findings show that digital game-based educational programs contrib-
ute to children’s language development and improve phonemic awareness skills (Gole and Temel, 2023).
Emphasized that the use of digital game-based learning in early childhood has increased in recent
years. They analyzed 37 articles to determine the effects of the relevant method in childhood. According
to the results of the study, it was seen that digital game-based learning can have an active impact on de-
veloping children’s thinking skills and strengthening their learning processes. These findings demonstrate
that digital game-based learning is a potentially powerful tool in early childhood education, supporting
cognitive development (Behnamnia et al., 2023).
In their study (Unal and Erbil, Kaya, 2024), they investigated the use of digital games in mathemat-
ics education in early childhood. According to the findings of the study, it has been revealed that the
integration of digital games and applications into mathematics education contributes to the development
of children’s mathematical skills. However, in order for these technologies to be implemented effectively,
pre-school teachers need to include digital games appropriately in the learning process, take into account
children’s individual needs and interests, and establish a strong collaboration with parents. Examined
studies on the use of digital games in mathematics classes can be found in Turkey by
Aydın and Ata
(2024). When the instructional features of the studies were evaluated, it was observed that digital game-
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Yildiz E. P., Alkan A., & Tezer M. (2025). Enhancing Early Childhood Students’ Computational Thinking Competency Through
Digital Game-Based Learning, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE),
13(2), 365-378.
based learning generally had positive effects on mathematical achievement and cognitive and affective
skills related to mathematics. In addition, the studies examined showed that digital games were mostly
used for reinforcement purposes in classes.
According to the results of another study, which investigated the effects of educational mobile
games on the critical thinking skills of pre-school children. The results of the study show that integrat-
ing educational mobile games into the existing pre-school curriculum improves children’s critical thinking
skills (Calhan and Goksu, 2024). Digitalization could potentially benefit children’s creative and cognitive
development, and aimed to examine the effect on a sample of pre-school children. The digital intervention
used in the study is a specially designed digitally supported learning program called “Pre-schoolers: Digital
Adventures”(Chen and Ding, 2024). The current findings of the study reveal that digital enrichment of the
learning process in pre-school education can help improve certain aspects of children’s creative-cognitive
development. This case shows that digital tools can play a supporting role in education in early childhood.
The Purpose of the Study:
This study proposes to analyze the contributions of digital games to computational thinking and
to develop educational materials and digital game-based learning experiences that are appropriate for
children’s developmental needs. The purposes of this study are as follows:
• To determine how computational development can be supported with digital games in early childhood.
• To examine the effect of providing computational thinking skills in early childhood on children’s prob-
lem solving, reasoning, and algorithmic thinking abilities.
• To discuss the usability of information technologies and digital games as an educational tool in devel-
oping children’s computational thinking skills.
The sub-objectives determined in line with these general objectives are presented below:
• Is there a significant difference between the pre-test and post-test achievement test scores of the
experimental group?
• Is there a significant difference between the pre-test and post-test achievement test scores of the
control group?
• Is there a significant difference between the pre-test achievement test scores of the experimental and
control groups?
• Is there a significant difference between the post-test achievement test scores of the experimental and
control groups?
• What are the learning outcomes at the end of the 4-week training process?
The Importance of the Study:
This study aims to examine the concurrence of these two topics by addressing the impact of digital
games on computational thinking in early childhood. This study draws attention to the need to investigate the
role of digital games and computational thinking that can contribute to the cognitive, social, and emotional
development processes of children aged 0-6 and to create educational materials suitable for this age group.
It can be said that children’s perception of play has changed in parallel with technological develop-
ments today. While children used to play with their peers on the streets in the past, today technological
devices have become play tools for the children we call Generation Z. Therefore, digital games have
become indispensable in children’s lives (Bird, 2012; Korkusuz and Karamete, 2013). It is known that
digital games have positive and negative effects on children, especially in a critical period such as early
childhood. It is seen that digital games are effective in developing hand-eye coordination, focusing atten-
tion, and problem-solving skills in children (Kim and Smith, 2017; Lin and Hou, 2016). In addition, it is
known that if creative games suitable for children’s ages are selected, it can contribute to the development
of children’s creativity through these games (Arslan and Gorgulu, Arı, 2023).
In this context, it is foreseen that the relevant research will offer an innovative perspective in
developing educational materials by drawing attention to the importance of digital game-based learning
experiences that develop computational thinking skills of children in early childhood, how they can be
integrated into the educational process, and revealing the learning opportunities offered by digital games.
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Yildiz E. P., Alkan A., & Tezer M. (2025). Enhancing Early Childhood Students’ Computational Thinking Competency Through
Digital Game-Based Learning, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE),
13(2), 365-378.
Materials and Methods
This section includes the research model, study group, process steps, structure of groups, data
collection tools and data analysis sections.
Research Model
In this study, the fully experimental method, one of the experimental research designs, was used.
Experimental studies are studies aimed at testing the effect of the differences created by the researcher
on the dependent variable (
Buyukozturk et al., 2019). The reason for using experimental research, one of
the quantitative research methods, in this study is that it is the most appropriate method for applying digital
game applications to a group with defined limits and properties. For this reason, experimental and control
groups were randomly created, and a comparison was made after the implementation.
Table 1. Study groups
Groups Girl Boy
Experimental group 13 12
Control group 12 13
Research Model
This study was conducted with kindergarten students studying in a pre-school institution in Turkey
in the 2024 – 2025 academic year. The experimental and control groups in the study consisted of 25 stu-
dents each. The 50 students (25 girls, 25 boys) included in the study were aged 5.
Sample Method
In this study, the convenience sampling method was selected from the sampling methods. Con-
venience sampling method is the collection of data from a sample that the researcher can easily reach.
For example, the selection of schools that are easy for the researcher to access and permit. The relevant
sampling method is a method that accelerates the research. Because in this method, the researcher se-
lects a situation that is close and easy to access (
Kılıc, 2017).
Process Steps
Table 2 shows the path followed during the study. The study was carried out in 3 steps: pre-imple-
mentation, implementation, and post-implementation.
Table 2. Process steps
Process Steps
Preparation Process
Before Implementation
Preparing activity
Obtaining permissions to use Rubric
Creating an achievement test
Implementation
Conducting pre-tests
4-week implementation process
Conducting post-tests
After Implementation
Analyzing data
Presenting the findings
Determination of learning outcomes
For this study, firstly, the activities and games to be used in the lessons were prepared. Rubric
permissions were obtained, and the achievement test was created. Then, the validity and reliability study
of the achievement test was carried out. After the preparations of the achievement test were completed,
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Yildiz E. P., Alkan A., & Tezer M. (2025). Enhancing Early Childhood Students’ Computational Thinking Competency Through
Digital Game-Based Learning, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE),
13(2), 365-378.
experimental and control groups were created and pre-tests were applied to the groups. Then the teach-
ing plan was applied to the students who participated in the study. After the application was completed,
the post-tests were applied to the students and the data were analyzed and the findings were presented.
In this study, a 4-week training activity was conducted on experimental and control groups to devel-
op the computational thinking skills of 5-year-old pre-school children. The aim of the study was to children
understand the commands of going forward-backward, turning right and turning left through activities using
Bee Bot, paper activities and digital games. With Bee Bot (https://www.robokids.com.tr/bee-bot-okul-onc-
esi-programlama-robotu ), paper activities and digital games were designed by researchers in accordance
with the applications themed around shapes and colors. The designed activities and games were restruc-
tured after being submitted to expert opinion, and necessary revisions were made. The students participat-
ing in the study had not been taught algorithms or coding before. Students from two different classes were
randomly selected as one class control group and the other class experimental group. During the 4-week
study, the educational activities applied to both groups were differentiated, and in this context, student de-
velopment was measured with rubric evaluations made by two different computer teachers. The cognitive
development of the 5-year-old students who made up the study group was tested through observation by
the course teachers. Observation is mostly used as a way to easily reveal behavioral changes in children
and to understand and detail this behavior. It is also a way to predict behavior in advance.
Structure of Groups
Experimental Group: The group consisting of 5-year-old children who have not taken a coding
course and who received Bee Bot training supported by digital games.
Control Group: A group of 5-year-old children who had not taken a coding course and received Bee
Bot training through paper activities.
The planned activities for the groups are shown in Table 3-Table 3.1. below.
Table 3. Experimental group study plan
Weeks Activities
Week 1 Getting to know Bee Bot
Week 2
Basic forward-backward, turn right-turn left command exercises with Bee Bot. Activity practices, achievement
test (pre), and rubric pre-test.
Week 3 Digital Game-1 Digital Game 2 Applications.
Week 4 Achievement test (post), rubric post-test, determination of teaching outcomes
Table 3.1. Control group study plan
Weeks Activities
Week 1 Getting to know Bee Bot
Week 2
Basic forward-backward, turn right-turn left command exercises with Bee Bot. Activity practices, achievement
test (pre) and rubric pre-test.
Week 3 Paper activity 1-2, Paper activity 3-4.
Week 4 Achievement test (post), rubric post-test, determination of teaching outcomes
Experimental group activities: Includes digital game activities in addition to Bee Bot.
Control group activities: Includes Bee Bot apps and paper activities. Bee Bot applications were
used to teach the same commands to both groups. The inclusion of digital games in addition to the experi-
mental group was done to observe the effect of digital games on computational thinking skills.
Data CollectionTools
The achievement test prepared for the cognitive domain consists of 15 multiple-choice questions
prepared for target achievements to be used as a pre-test and post-test. In the preparation of the achieve-
ment test, expert opinions were taken from 3 faculty members, who teach in the Pre-School Education
Department of the Basic Education Department. Following the expert opinion received, expert faculty
members confirmed that the achievement test was suitable for the relevant teaching level. It has been
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Yildiz E. P., Alkan A., & Tezer M. (2025). Enhancing Early Childhood Students’ Computational Thinking Competency Through
Digital Game-Based Learning, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE),
13(2), 365-378.
recommended by expert faculty members that the questions be read to pre-school students by assistant
teachers and their answers be obtained.
With the Ladybug U bot coding tool supported by digital games and paper activities used throughout
the 4-week teaching period, children were taught game-supported and paper activity topics and commands
such as algorithm creation, sequencing, function creation, loops, and debugging. The questions developed
for the achievement test were prepared to measure the learning of these topics and commands. While de-
veloping the achievement test, the process applied by Seker and Gencdogan (2014) for the achievement
test was taken into consideration. The procedures carried out in this direction are presented below
:
a) Determining the scope: The purpose of the test is to determine the readiness level of the students in
the experimental and control groups.
b) Determination of targets/learning outcomes: The learning outcomes are within the scope specified in the
pre-school curriculum. In this direction, there are 5 basic achievements expected to be achieved in the unit.
c) Creation of evaluation rubrics: A rubric sample developed by the researchers was used to evaluate
student performances with various criteria.
d) Preparation of test questions: Expert opinion was obtained on the item pool created based on the achieve-
ments, and it was decided to prepare multiple-choice questions. A question pool of 23 items was created.
e) Test implementation/scoring: In line with the opinions received from a program developer, a meas-
urement & evaluation and a field expert, 3 questions in the item pool were removed, and it was
decided to apply 20 questions as is.
f) Implementation of the test, validity and reliability study: The achievement test, consisting of 5
achievements and 15 items, was applied to the experimental and control groups of 50 people, and
KR-20 was calculated for reliability.
Performing item analysis: The highest score that can be obtained from the test was determined as
20, the lowest score as 0. Each question was determined as 5 points. As a result of the analysis of the an-
swers given to the test, the item difficulty index (p) and the item discrimination index (D) were calculated.
Accordingly, at least one question remained that measured each gain.
Kuder Richardson-20 was used in reliability analysis because of the coding of right and wrong answers
as 1 and 0 while developing the achievement test. In the item difficulty index calculated using the formulas
shown in Table 4, .20 to .00: very difficult; .21 to .40: difficult; .41 to .60: medium difficulty; .61 to .80: easy;
.81 to 1.00: very easy. In item discrimination values, items with values below .20 were removed from the test.
Table 4. Scores regarding the analysis of the test
Question Item Difficulty Index (p) Item Discrimination Index (D)
Q1 .62 .30
Q2 .70 .21
Q3 .65 .30
Q4 .66 .34
Q5 .69 .30
Q6 .66 .30
Q7 .60 .31
Q8 .67 .33
Q9 .63 .36
Q10 .59 .31
Q11 .59 .30
Q12 .56 .34
Q13 .59 .30
Q14 .62 .31
Q15 .58 .30
Q16 .46 .28
Q17 .73 .31
Q18 .65 .36
Q19 .73 .31
Q20 .83 .21
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Yildiz E. P., Alkan A., & Tezer M. (2025). Enhancing Early Childhood Students’ Computational Thinking Competency Through
Digital Game-Based Learning, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE),
13(2), 365-378.
According to Table 4.1; an achievement test consisting of 20 items was developed by the research-
ers in order for students to comprehend the relevant structures. The KR-20 reliability of the test was found
to be 0.84. Getting a high score from the test shows that the level of achievement of the gains is high. KR-
20 value of 0.80 or greater is desirable. However, 0.70 and above is also acceptable. Scales with KR-20
value of less than 0.70 are not good enough (
Shepard, 2005).
Creation of Evaluation Rubrics
Rubrics are usually in the form of tables based on horizontal and vertical axes. The vertical axis
usually contains performance criteria, and the horizontal axis contains increasing performance levels from
the lowest level to the highest level. At the intersection of the horizontal and vertical axes, there are per-
formance definitions related to the performance level of the performance criterion. Performance criteria
allow the components of performance to be seen.
Table 5. Evaluation rubric
Excellent(6) Very good(5) Good(4) Average(3) Limited(2) Very limited(1)
Analysis
Separate a problem into
smaller parts accurately,
precisely and
confidently. Explains the
problem systematically
Properly
separate
the problem
into smaller
pieces
Separates the
problem into
smaller pieces
with minor
mistakes
Separates the
problem into
smaller pieces
with significant
mistakes
Separates
the problem
into smaller
pieces with
the teacher’s
guidance
Shows no
evidence of
analysis.
Pattern recognition
Recognizes patterns
accurately and reliably,
making accurate
predictions based on
pattern variations
Recognizes
patterns
accurately
Recognizes
patterns with
minor mistakes
Recognizes
patterns with
major mistakes
Recognizes
patterns under
the guidance of
the teacher
Shows no
evidence
of pattern
recognition.
Abstraction
Simplifies a problem,
identifies main ideas
accurately and
confidently, and explains
the most important
details of the problem
Simplifies a
problem and
identifies
main ideas
accurately
Simplifies a
problem and
identifies main
ideas with
minor mistakes
Simplifies a
problem and
identifies main
ideas with
significant
mistakes
Simplifies a
problem and
identifies
main ideas
with teacher
guidance
Does not show
any evidence
of abstraction.
Algorithm design
Creates a logical
sequence of steps, solves
a problem accurately,
effectively, and safely,
and can explain
procedures in detail
Creates
a logical
sequence
of steps to
correctly solve
a problem
Creates
a logical
sequence of
steps to solve
a problem with
minor mistakes
Creates
a logical
sequence of
steps to solve
a problem with
major mistakes
Creates
a logical
sequence of
steps to solve
a problem
with teacher
guidance
Shows no
evidence of the
algorithm.
Logical reasoning
Correctly predicts
the logical facts of a
problem
Accurately
determines
the logical
facts of a
problem
Guessing the
logical truths of
a question with
small mistakes
Guessing the
logical truths of
a problem with
major mistakes
Guess the
logical truths
of a problem
under the
guidance of the
teacher
Provides no
evidence of
logical truths.
Evaluation
Evaluates solutions,
identifies any mistakes,
successfully fixes
them and suggests
improvements
Evaluates
solutions,
identifies and
corrects any
mistakes
Evaluates
solutions,
identifies most
mistakes and
successfully
fixes them
Evaluates
solutions,
identifies and
corrects some
of the mistakes
Evaluates
solutions
under teacher
guidance
Shows no
evidence of
evaluation.
Rubrics are scoring scales developed by teachers or other assessment professionals to guide
students in their learning process or to help them understand how to analyze learning products and thus
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Yildiz E. P., Alkan A., & Tezer M. (2025). Enhancing Early Childhood Students’ Computational Thinking Competency Through
Digital Game-Based Learning, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE),
13(2), 365-378.
support their learning (Mertler, 2001; Truemper, 2004; Moskal, 2000; Shepard, 2005). According to the
table above a rubric sample developed by the researchers was used to evaluate student performances
with various criteria. The success criteria in the relevant rubric were observed and scored by two com-
puter teachers throughout the teaching-learning process. Rubric criteria are structured according to the
computational thinking approach developed by the (Panadero and Jönsson, 2013).
Analysis of Data
In cases where there are fewer than 30 participants in the experimental and control groups, it is difficult
to assume that the scores are normally distributed. In such cases, it is appropriate to use non-parametric tests
for analysis (Buyukozturk et al., 2011). Wilcoxon Signed Rank Test and Mann-Whitney U-Test were used in
the analysis of the data because the number of groups was small and the distribution did not show normality.
Results
Comparison of the experimental groups and the control group separately according to their scores
before and after the training was made using Kruskal-Wallis and Mann-Whitney U non-parametric tests,
as the data did not show a normal distribution. Since p<0.5 was obtained within the scope of the Kolmog-
orov-Smirnov test, it was accepted that the data did not show a normal distribution. The general average
was taken into account in explaining the differences in the data. The findings obtained in the study are
presented below through the relevant tables.
Comparison of Achievement Tests of Experimental and Control Groups:
Comparison of achievement tests of experimental and control groups was made using the Mann-
Whitney U test. The Mann-Whitney U-test can be used when the aim is to show the difference in the value
of an ordinal, interval, or proportional variable between two groups.
Table 6. Comparison of Pre-Test Success Scores of Experimental and Control Groups: Mann-Whitney U Test Result
Groups N Average Rank Total Rank U p Significant Difference
Experimental Groups
Control Groups
25
25
57.10
63.90
3426
3834
1596 .281
There is no significant difference
between the groups
According to the table, since the p value is .281> .05, there is no significant difference between the
pre-test success scores of the experimental group and the control group.
Table 6.1. Comparison of Post-Test Success Scores of Experimental and Control Groups: Mann-Whitney U Test Result
Groups N Average Rank Total Rank U p Significant Difference
Experimental Groups
Control Groups
25
25
67.68
53.32
4061
3199
1369 .004
There is a significant difference
between the groups
According to the table, since the p-value is .004 < .05, there is a significant difference between the
post-test success scores of the experimental group and the control group, and this difference is in favor
of the experimental group.
Experimental Group Pre-Test & Post-Test Achievement Test:
Table 6.2. Wilcoxon signed rank test results of achievement test scores before and after the experimental group
Groups Pretest-Post test N Average Rank Total Rank Z P Significant Difference
Experimental
Group
Negative Orders
Positive Orders
Equal
1
24
0
.00
30.25
.00
1830.0
-6.736 .000
There is a significant differ-
ence between the groups
Pre-test and post-test achievement test scores of the experimental group students were tested with
the Wilcoxon signed-rank test. According to Table 6.2, the learning outcomes of the experimental group
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Yildiz E. P., Alkan A., & Tezer M. (2025). Enhancing Early Childhood Students’ Computational Thinking Competency Through
Digital Game-Based Learning, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE),
13(2), 365-378.
students participating in the study were examined. In this context, the Wilcoxon Signed Rank Test was
used to determine the significant difference between the pre-test and post-test academic achievement
scores. When the academic achievement scores of the experimental group students were compared to
the relevant test, a significant difference was found in favor of the post-test (z=-6.736; p<.05).
Table 6.3. Wilcoxon signed rank test results of achievement test scores before and after the control group
Groups Pretest-Post test N Average Rank Total Rank Z P Significant Difference
Experimental
Group
Negative Orders
Positive Orders
Equal
1
24
0
4.88
32.33
19.5
1810.5
-6.593 .000 There is a significant
difference between
the groups
According to Table 6.3, the learning outcomes of the control group students participating in the study
were examined. In this context, the Wilcoxon Signed Rank Test was used to determine the significant
difference between the pre-test and post-test academic achievement scores. Accordingly, when the aca-
demic achievement scores of the control group students were compared with the relevant test, a signifi-
cant difference was found in favor of the post-test (z=-6.593; p<.05).
Evaluation Rubric Analysis:
The responses from 50 students to the relevant rubric developed by Panadero and Jönsson (2013)
were analyzed and delivered to 2 computer teachers. In addition, teachers were given a graded scoring
key and a scoring table with student names. Teachers first graded the problems without using a scoring
rubric. Each question is worth 15 points in the evaluation. Since there are 6 problems, a student who
answers all of them correctly will receive a total of 90 points, and the student with the lowest score will
receive a total score of 0. The scores made by the teachers without using the rubric were collected. The
same teachers scored the same papers with the rubric, and they did these scores 2 weeks later to reduce
the memory effect. The consistency between the scores given by the teachers to the student answers
using the graded scoring key was examined separately for the 1st-6th problems.
Table 7. Correspondence between the scores given by teachers to student responses using a rubric
N Kendall w Sd p
1. Problem 50 .85 26 .000
2. Problem 50 .83 26 .000
3. Problem
50 .82 26 .000
4. Problem 50 .83 26 .000
5. Problem 50 .81 26 .000
6. Problem 50 .82 26 .000
When Table 4-1 is examined, the Kendall w result between the scores given by 50 raters to the stu-
dent answers using the rubric was found to be .85 for problem 1, .83 for problem 2, .82 for problem 3, .83
for problem 4, .81 for problem 5, and .82 for problem 6. These values show that there is a high consistency
between the scores given by the teachers using the rubric for each problem. Since the Kendall W test is a
test used to evaluate the compatibility of raters, it can be said that the consistency between the separate
scores of the teachers for each question is at a high level. Although the Kendall w coefficients of all 6 prob-
lems are close to each other, it is seen that the highest consistency is in problem (Buyukozturk et al., 2011).
Discussion
In their research, Pan et al. (2024) studied improving the computational thinking competence of
secondary school students through game-based learning. The findings of the study confirmed that game
experience positively affected students’ computational thinking self-efficacy, but did not affect their game-
based engagement. When comparing the demographic factors of age (grade) and previous gaming expe-
rience, it was found that the gender factor tended to play a more important role in students’ self-efficacy
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Yildiz E. P., Alkan A., & Tezer M. (2025). Enhancing Early Childhood Students’ Computational Thinking Competency Through
Digital Game-Based Learning, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE),
13(2), 365-378.
regarding computational thinking competence and in the extent to which it moderated game-based par-
ticipation. At the end of the study, implications and possible directions for future research on using game-
based learning to improve computational thinking competence are discussed.
According to the results of another study, researchers studied middle school students on the subject
of computational thinking through game design and contributed a case study to the literature in the relevant
field. This study used Code.org’s block-based programming curriculum and evaluated its impact on middle
school students’ Computer Technology (CT) skills and attitudes toward CT and CS (Computational Science).
The findings of the study proved that the participants showed a significant increase in algorithmic thinking,
debugging, and pattern recognition skills, but not in abstraction skills (Cafarella and Vasconcelos, 2024).
In their study, Cheng et al. (2023) examined the development of computational thinking skills
throughout program question strategies in a game-based learning platform. The study group consisted
of 53 primary school students, and the data were collected during four lesson hours consisting of ex-
perimental Computational Thinking (CT) activities. This study shows that the experimental group using
the student-generated questions (SGQ) strategy with the game-based learning (GBL) platform exhibited
significantly higher information technology (IT) skills than the control group.
Conclustion and Recommendation
This study proposes to analyze the contributions of digital games to computational thinking and
to develop educational materials and digital game-based learning experiences that are appropriate for
children’s developmental needs. This study was conducted with kindergarten students studying in a pre-
school institution in Turkey in the 2024 – 2025 academic year. The experimental and control groups in the
study consisted of 25 students each. The 50 students (25 girls, 25 boys) included in the study were aged
5. Within the scope of relevant purposes, a 4-week training activity was conducted on experimental and
control groups to develop the computational thinking skills of 5-year-old pre-school children. The study
aimed to help children understand the commands of going forward-backward, turning right and turning left
through activities using Bee Bot, paper activities, and digital games. With Bee Bot, paper activities and
digital games were designed by researchers in accordance with the applications themed around shapes
and colors. The designed activities and games were restructured after being submitted to expert opinion,
and necessary revisions were made. The students participating in the study had not been taught algo-
rithms or coding before. Students from two different classes were randomly selected as one class control
group and the other class experimental group. During the 4-week study, the educational activities applied
to both groups were differentiated, and in this context, student development was measured with rubric
evaluations made by two different computer teachers.
In this study, the fully experimental method, one of the experimental research designs, was used.
In cases where there are fewer than 30 participants in the experimental and control groups, it is difficult
to assume that the scores are normally distributed. Non-parametric tests were preferred in the analysis of
data because the number of groups was small and the distribution did not show normality. The test results
for the sub-objectives determined in the research are presented below:
There is a significant difference between the pre-test and post-test academic achievement scores
of the experimental group participating in the program regarding the course outcomes. A significant differ-
ence was found in favor of the post-test in terms of achievement scores. There is a significant difference
between the pre-test and post-test academic achievement scores of the experimental group participat-
ing in the program regarding the course outcomes, and no significant difference was found in favor of
the post-test in terms of academic achievement scores. According to the results of the Mann-Whitney
Test conducted to compare the pre-test and post-test achievement tests of the experimental and control
groups, there is no significant difference between the pre-test success scores of the experimental group
and the control group. There is a significant difference between the post-test success scores of the experi-
mental group and the control group, and this difference is in favor of the experimental group.
The responses from 50 students to the relevant rubric developed by the researchers were ana-
lyzed and delivered to 2 computer teachers. In addition, teachers were given a graded scoring key and
a scoring table with student names. Each question is worth 15 points in the evaluation. Since there are 6
problems, a student who answers all of them correctly will receive a total of 90 points, and the student with
the lowest score will receive a total score of 0. The consistency between the scores given by the teachers
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376
Yildiz E. P., Alkan A., & Tezer M. (2025). Enhancing Early Childhood Students’ Computational Thinking Competency Through
Digital Game-Based Learning, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE),
13(2), 365-378.
to the student answers using the graded scoring key was examined separately for the 1st-6th problems.
the Kendall W result between the scores given by 50 raters to the student answers using the rubric was
found to be .85 for problem 1, .83 for problem 2, .82 for problem 3, .83 for problem 4, .81 for problem 5,
and .82 for problem 6. These values show that there is a high consistency between the scores given by
the teachers using the rubric for each problem.
Within the scope of the study, the following suggestions are presented for future research and
researchers:
• This study was conducted with kindergarten students studying in a pre-school institution in Turkey
in the 2024 – 2025 academic year. In order to obtain different and/or similar results within the scope
of the situation, the same research can be repeated by different researchers, in different educational
environments and with different study groups.
• Studies can be conducted in educational institutions to determine to what extent students are informed
about the theory, application, and evaluation methods of the computational thinking approach or to
what extent the relevant approach is adopted by students.
• It is recommended that similar research be conducted by updating the learning content and materials
in line with the developments in the field.
Acknowledgments
The authors would like to express their sincere gratitude to Near East University and Kafkas Univer-
sity for their institutional support throughout the development of this study. We also thank the anonymous
reviewers for their valuable feedback and suggestions that helped improve the quality of this manuscript.
Conflict of interests
The authors declare no conflict of interest.
Author Contributions
Conceptualization, Ayse ALKAN; methodology, Ezgi Pelin YILDIZ; software, Murat TEZER; vali-
dation, Ezgi Pelin YILDIZ, Ayse ALKAN & Murat TEZER; formal analysis, Ezgi Pelin YILDIZ; research,
Ayse ALKAN; resources, Murat TEZER; data curation, Ezgi Pelin YILDIZ; writing - review & editing, Ezgi
Pelin YILDIZ; visualization, Murat TEZER; supervision, Ezgi Pelin YILDIZ, Ayse ALKAN & Murat TEZER;
project administration, Ezgi Pelin YILDIZ. The authors read the final version of the article together and
decided to publish together.
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