Computational Thinking Skills Research Articles

Comparative Experiment of the Effects of Unplugged and Plugged-in Programming on Computational Thinking in Primary School Students: A Perspective of Multiple Influential Factors

Recently, the development of computational thinking (CT) skills has become widespread in the whole world. There is a consensus to develop students’ CT skills through unplugged and plugged-in programming. However, the choice of programming approaches taught in schools is arbitrary and few studies have compared the effectiveness differences between unplugged and plugged-in programming. This study aimed to explore the differences between unplugged and plugged-in programming in developing CT skills of students in Grades 1-2 students. It also explored the joint effects of students’ gender, programming experience, programming interest, and programming confidence with different programming approaches on CT skills. The quasi-experimental research approach was used to conduct 10 weeks of unplugged, plugged-in, and regular programming activities with 124 Grades 1-2 students. The results found that unplugged programming promoted CT skills more in the early primary grades than plugged-in programming. We found that boys and students with programming experience in unplugged group performed significantly better in CT skills than in plugged-in group. Moreover, the improvement of CT skills of students in unplugged group was positively correlated with the level of their programming interest and programming confidence. However, these were not observed in plugged-in group. The results of this study can provide precise guidance for teaching CT skills to early primary school students and provide references for CT education.

Entrepreneurship education, digital literacy and computational thinking insights for business sustainability among housewives

Introduction. Development of digital literacy and computational thinking among housewives lie in its potential to address a critical gap in the understanding of digital education and empowerment. This study seeks to ascertain the viability of family enterprises based on digital marketing. In detail, this study examines the relationship between entrepreneurship education, digital literacy, and business sustainability through computational thinking. Study participants and methods. This research involved a quantitative approach using a self-administered survey method. The population in this study were housewives in several regions in Indonesia and the data will be analyzed using partial least square structural equation modeling (PLS-SEM). Sumatra, Java, and Bali homemakers participated in this study. The three islands represent Indonesia's west, center, and east regions. We offered 350 Google Forms questions sent via WhatsApp. Results. The results indicates that entrepreneurship education has a significant effect on business sustainability (t-value =16.620, p-value =.000), and computational thinking skills (t-value =10.916, p-value =.000). In addition, digital literacy has a significant effect on business sustainability (t-value =4.612, p-value =.000), and computational thinking skills (t-value =3.738, p-value =.000). Later, there is robust link between computational thinking and business sustainability (t-value =3.712, p-value =.000). The mediating estimation indicates that computational thinking can mediate the connectivity between entrepreneurship education and business sustainability (t-value =3.398, p-value =.001), as well as digital literacy and business sustainability (t-value =2.516, p-value =.012). Conclusion. Empowering housewives with entrepreneurship education, digital literacy, and computational thinking holds practical significance in managing their business and community development. This research extends beyond housewives empowerment to potential policy assistance and housewives educational reforms to build inclusive business matters.

Investigating the psychometric features of a locally designed computational thinking assessment for elementary students

ABSTRACT Background and Context Educators and researchers are interested in building the computational thinking (CT) skills of K-12 students. However, the availability of language-agnostic assessments for lower elementary graders remains limited. Objective We present preliminary insights into the reliability and validity of the Computational Thinking Assessment for Elementary Students (CTAES), a new assessment to measure 3rd-5th grade students’ CT abilities. Method The CTAES was administered to 222 3rd-5th grade students. We conducted Rasch analyses, focusing on dimensionality, separation characteristics, and differential item functioning. Findings The CTAES appears to be unidimensional, primarily assessing students’ CT skills. Students with lower CT proficiency demonstrate lower likelihood of correctly responding to assessment items compared to peers with higher CT proficiency levels. Preliminary evidence suggests that the assessment does not exhibit bias based on gender or racial/ethnic background. Implications Initial findings suggest that the CTAES holds promise as a reliable and valid assessment tool, although there remain opportunities for further refinement.

Computational Thinking with a Multi-literacy Model Using Interactive PowerPoint Media: An Experiment in Elementary Schools

Elementary school students need to acquire computational thinking as a crucial skill in the digital age. Similar to mathematical skills, computational thinking is a fundamental competence in digital literacy. It is used to solve problems in learning. One approach is to facilitate children’s learning by emphasizing computational thinking, such as using the multi-literacy model with interactive PowerPoint slides. This study aimed to assess and characterize the influence of multi-literacy models aided by interactive PowerPoint media on the development of computational thinking skills in elementary school students, considering their prior knowledge. Involving a total sample of 56 4th-grade elementary school students, this quantitative study employed a 3 x 2 factorial design. The sample included 14 students in the high group, 28 in the medium group, and 14 in the high group. The research revealed that the implementation of a multi-literacy learning approach, assisted by interactive PowerPoint media, significantly enhances student’s acquisition and improvement of computational thinking skills. This is because children can develop computational thinking skills in an enjoyable environment using PowerPoint media. Another study revealed that students in the high group performed much better on average when it came to learning computational thinking skills. Meanwhile, the average gain of computational thinking skills in the medium group was only slightly different from that of the low group. Keywords: computational thinking, multi-literacy model, interactive PowerPoint media

STEM: Its Potential in Developing Students' Computational Thinking

Computational thinking skills are a person’s ability to solve problems with several passed processes. The process is recognizing patterns, decomposing patterns, compiling algorithms, making models, and doing abstractions. This ability is essential for students to master understanding aspects of computational problems. It also helps students evaluate the suitability of computational techniques to solve the problem. In addition, this computational thinking ability can also help students understand the limitations and strengths of computing techniques, apply or adapt computing tools/techniques to new uses, recognize opportunities to use computing in new ways, and apply computational strategies. The STEM approach, is learning that integrates science, technology, engineering, and mathematics to develop creativity in solving problems. The transformation of the educational process in the current era that requires a high level of technology makes STEM one of the keys to progress and innovation in developing human competence. Based on a study of more than 30 articles and research results related to the effect of STEM on student learning outcomes, we can conclude that learning using STEM has the potential to develop students’ computational thinking skills. This article discusses how, theoretically, we can acquire computational thinking skills through education with a STEM approach. Keywords: STEM, developing students’, computational thingking

A Critical Appraisal: Elementary School Coding Education Effectiveness with Scratch in Alignment with Cognitive Development, Analyzed through Piagetian Lens

The digitalization has revolutionized the education sector by integrating technology and bringing about significant changes. Computational Thinking (CT), an indispensable skill for the 21st century, has now become an integral part of school curricula in several countries worldwide. Focused on enhancing CT skills, programming education, especially through Scratch, Scratch simplifies programming concepts, making it suitable for elementary school children aged 7 to 11 years. Aligned with Piaget's concrete operational stage, emphasizing organized and rational thinking. Hence, this study aims to delve deeper into how Scratch programming education can meet the cognitive developmental needs of children in this phase. The research methodology used is a literature review, employing data from textbooks, journals, scholarly articles, and literature reviews that contain concepts central to the research focus. The data analysis involves collecting relevant research findings, organizing, and systematically recording information. The results indicate that Scratch not only provides a platform for learning programming but also supports the development of concrete operational cognitive skills taught in Piaget's theory. Through creativity in designing Scratch projects, children can apply and strengthen their understanding of concepts such as seriation, classification, reversibility, conservation, and the elimination of egocentrism. But, it's essential to consider an approach tailored to the developmental characteristics of children when designing programming education at the elementary level. This study is expected to provide concise guidance for educators and policymakers in formulating programming education that optimally fosters cognitive development in elementary school children.

Computational Thinking in Secondary Mathematics Education with GeoGebra: Insights from an Intervention in Calculus Lessons

AbstractNowadays, mathematics teachers in K–12 strive to promote their students‘ mathematical knowledge and computational thinking (CT) skills. There is an increasing need for effective CT-embedded mathematics learning material and a better understanding of students’ views toward them. In this work, we present the results of a research study, which included the design of a six-lesson learning activity aimed at fostering 16- to 17-year-old secondary students’ CT skills in calculus lessons using the dynamic mathematics software GeoGebra. Our goal was to investigate how students experienced the CT-embedded calculus lessons with GeoGebra and what challenges they faced during their interaction with the learning material and software. We collected and analyzed data from students’ code in GeoGebra, workbooks, semi-structured interviews, and questionnaires. Our findings suggest that most students mastered using CT concepts in calculus activities to a satisfactory degree and could reason about their computational solutions using GeoGebra and the generated graphs. Students’ understanding of the mathematical content knowledge introduced was essential to complete the lesson series successfully and unnoticed gaps in prior knowledge emerged. Our study shows that students appreciate the CT-embedded calculus lessons and GeoGebra’s exploratory approach to mathematics problems when provided with appropriate support. We conclude that an integrated approach to mathematics education and CT is viable and can contribute not only to fostering CT but also to increasing interest in mathematics.

Measuring mutual engagement in the context of middle-school pair programming: Development and validation of a self-reported questionnaire

With the increasing importance of equipping young learners with computational thinking skills through learning to code, pair programming has emerged as a prevalent collaborative learning strategy in this context. Successful pair programming interventions necessitate mutual engagement between partners within a dyad. However, the measurement of mutual engagement in dyadic collaborative learning remains an under-researched area. This research represents a foundational stage in bridging this gap by developing a comprehensive 20-item Pair-Programming Mutual Engagement Questionnaire (PPME-Q) as a measure of mutual engagement in pair programming at the activity level. The questionnaire was validated through a sample of 86 eighth-grade students. Confirmatory factor analysis confirmed the existence of a four-factor structure comprising of the behavioral, cognitive, emotional, and social engagement factors. The findings demonstrate the validity (χ2/df = 1.32) and reliability (Cronbach's α = 0.888) of the PPME-Q, establishing it as an effective tool for assessing eighth graders' mutual engagement in pair programming activities. As this tool is in the nascent stages of development the measurement, we emphasize the need for further empirical studies to establish criterion validity. We also discuss the implications of these findings for future research and educational practices. This targeted instrument can then potentially be adapted or scaled to other age groups based on the insights gained.

Implementation of an Online Programming Software to Explore the Computational Thinking Ability of Biological Education Students

This study aimed to explore the Computational Thinking (CT) ability of biology education students in artificial intelligence courses through code.org programming, an online programming software. Students were required to solve problems systematically and design systems with coding for beginners. The research method used a qualitative approach because it was based on observational data from computational media produced in accordance with artificial intelligence learning for education and based on CT indicators. The subjects of this study were 73 students of the Biology Education Study Program in 2021. How students responded to using the code.org platform was captured through a questionnaire distributed via a Google form. The results showed that students could follow each stage of educational game projects through the code.org platform to practice computational thinking skills in accordance with the success of the stages of doing simple projects through good, systematic and problem-solving coding. Student responses to the code.org platform as an online program tool that can hone computational thinking can provide creativity and enthusiasm for student learning. As evidenced by the questionnaire results, 63.3% of students strongly agree that this increases creativity.
 Keywords: online programming, computational thinking, biological education, students

Relationships Between Executive Functions and Computational Thinking

Addressing cognitive disparities has become a paramount concern in computational thinking (CT) education. The intricate and nuanced relationships between CT and cognitive variations emphasize the needs to accommodate diverse cognitive profiles when fostering CT skills, recognizing that these cognitive functions can manifest as either strengths or limitations in different students. Consequently, understanding the connections between students’ cognitive functions and CT skills assumes pivotal importance in the design of personalized instructional strategies for CT. Despite a general consideration of learning variability in CT education, empirical insights exploring the correlation between cognitive skills and CT competencies remain notably scarce. This study endeavors to bridge this research gap by investigating the links between executive functions and CT skills, as well as the associations between their sub-dimensions. The results reveal a statistically significant correlation coefficient of 0.452 between these two domains, underscoring the notable connection between executive functions and CT abilities. Furthermore, the sub-dimensional analysis offers a comprehensive understanding of how specific executive functions uniquely contribute to certain CT skills. In light of these findings, this research offers a promising pathway for the development of tailored CT education programs that can cater to the unique needs of each individual, ultimately facilitating inclusive CT programs and making significant contributions to broaden STEM education and future workforce.

Exploratory factor analysis-instrument for self-assessment of computation thinking skills and collaboration skills

This study focuses on developing and validating instruments to assess the computational thinking skills (CTS) and collaboration skills (CS) of undergraduate students in Indonesia. Employing a quantitative research approach with the exploratory factor analysis (EFA) technique, the research process unfolded in three validation steps. First, face validity was established through expert judgment. Second, discriminant validity was examined using product-moment correlations and Cronbach’s alpha. Finally, EFA were employed to assess the factorial structure. The instrument development process followed five phases: drafting the instrument, face validity assessment by experts, data collection involving 242 undergraduate students as samples, discriminant validity analysis (product moment and Cronbach’s alpha), and EFA analysis to group items and construct dimensions. This study identified six dimensions for CTS (algorithmic thinking, cooperative thinking, problem reformulation, creativity, critical thinking, and systematic testing) and three dimensions for CS (knowledge sharing, planning, and responsibility). These findings support validating the CTS and CS self-assessment scale, making it a valuable tool for evaluating undergraduate student learning and researching computational thinking and CS in Indonesia. Researchers and educators are encouraged to utilize the CTS and CS instrument for self-assessment purposes and further exploration of these competencies among undergraduate students.

Situational judgment test measures administrator computational thinking with factor analysis

Computational thinking skills (CTS) play a crucial role across diverse domains, involving a thinking process that allows the execution of solutions by information processing agents. Measuring the level of CTS becomes essential to ensure that administrators effectively leverage technology. However, finding suitable instruments to measure and justify CTS levels in administration can be challenging. The selection of situational judgement test (SJT) is supported by its validity and reliability in assessing attributes, including professionalism. The instrument’s development includes face validity, discriminant validity (using Pearson correlation and Cronbach’s alpha), and exploratory factor analysis (EFA). The study involved 111 undergraduate administration students from various Indonesian universities, and data were collected in 2023. Following a discriminant validity analysis, ten items were eliminated, while 23 met the criteria with p0.185. Subsequently, EFA yielded 16 items forming seven components, covering algorithmic thinking, problem-solving, technology literacy, problem abstraction, problem reformulation, data management in administration technology, and administrative data presentation with loading factor variations (0.421-0.868). The final instrument, consisting of 16 valid items and seven components, effectively evaluates the level of administrator computational thinking skills (ACTS) among administration students.

The intentions of the designers of digital educational tools in early childhood education

The popularity of programmable robots in early childhood education is growing. Such robots are discussed in the literature from the points of view of teachers, parents and children. We add the role of robot designers to this list. Focusing on designers and specifically their intentions is beneficial in two settings: in teacher training and whenever using the robots in playing activities in ECE. We present a qualitative study on robot designer intentions, conducted by group interviews with designers of two common but significantly different programmable robots, the Kubo robot and the Rugged robot. Using Activity Theory as the underlying framework for the thematic analysis of the interviews, our data reveal a large overlap of the intentions of both groups. They express the common goal of preparing children for the future although through slightly different competencies: enhancing computational thinking and 21st century skills, respectively. Both groups highlight the relevance of subjects outside computer science, specifically beyond coding. Our data also show a design process difference the Rugged robot was developed with a teacher-oriented approach whereas the Kubo robot with an object-oriented approach.

Implementation of STEM-Oriented MEA learning model to improve computational thinking skills of learners

Low computational thinking skills cause students to have difficulty solving problems. This study aims to analyze whether there is an increase in students' CT abilities using the STEM-oriented MEA model with conventional learning. The research method is an experiment using an experimental group of 30 students and a control class of 32 students. The research instrument uses questionnaires and rubrics to assess students' CT abilities. The results of the T-test analysis used are Equal variances not assumed, which is 0.000 (Sig. (2-tailed)) > 0.05 means There is an increase in student's CT abilities using the STEM-oriented MEA model with conventional learning, so There is an increase in student's CT abilities using the STEM-oriented MEA model with conventional learning. Thus, there is an increase in the ability of students to think computationally using the STEM-oriented MEA model with conventional learning.

How to learn and teach a foreign language through computational thinking: Suggestions based on a systematic review

There has been an increasing interest in the integration of technology into language education. Meanwhile, computational thinking (CT) skills are fostered which influence communicative language teaching and learning. Despite CT's established importance in science education, its significance in language teaching remains scarce. This study contributes to knowledge synthesis and methodological development by reviewing 16 journal articles, analyzing CT applications in language learning across educational contexts, intervention tools, CT skills, language acquisition, and assessment methods. The results indicate that (a) more CT-involved activities are needed for primary, secondary, and tertiary education, (b) educational robots and Scratch stand out as the most trending intervention tools, (c) CT skills such as decomposition, abstraction, generalization and so on have a positive effect on students’ foreign language acquisition, especially in grammar and writing, (d) assessment of CT development can be surveyed through a validated and reliable instrument such as computer programming self-efficacy scale or an online platform: Dr. Scratch; Conversely, there is a diversity of evaluation tools in foreign language learning. This study is the first to review experimental research on integrating computational thinking into foreign language learning and offers significant implications for future research.

Effect of PBL-Based Scratch E-module in Improving Computational Thinking and Physics Concepts

The rapid and sophisticated development of science and technology requires education to present learning by developing IT skills in students. At the same time, mastery of physics concepts is needed to solve abstract problems. This material packaged using technology and computer programming can be an alternative solution to this problem. This study aims to measure the improvement of computational thinking and physics concepts of senior high school students in applying the problem-based learning-based Scratch experimental module. This research method is quantitative with a quasi-experimental design of the type of Pretest-Posttest Control Group Design. The results showed a significant increase in computational thinking skills in order changing straight motion, free fall motion, vertical upward motion, and concept mastery after using the E-module Scratch experiment based on problem-based learning for high school students are significant. Based on the results of this study, it can be interpreted that using the Scratch digital experimental E-module can improve computational thinking skills and physics concepts.

Primary school students' perceptions and developed artefacts and language from learning coding and computational thinking using the 3C model

AbstractBackgroundA resurgence in teaching coding in primary school classrooms has led to a pedagogical swing towards using physical computing and coding to develop students' use of algorithms, computational thinking, and problem‐solving skills. Two obstacles impede the optimal development of these objectives: the availability of a suitable pedagogy and an instructional sequencing model for primary school teachers to effectively present coding and computational thinking concepts and skills to students in alignment with their developmental stage.ObjectiveThis study aims to address both obstacles by introducing the 3C Model, a newly developed instructional sequence grounded in established pedagogies and designed to effectively teach coding and computational thinking skills to primary school students based on their developmental stage.MethodsThe qualitative study employed two data sources to triangulate findings, using: (1) semi‐structured interviews and thematic analysis to investigate 11 primary school students' perceptions of their learning experiences with the 3C Model, and (2) researcher observations along with reflections of the students' developed and demonstrated learning through the method of knowing‐in‐action, reflection‐in‐action, and reflection‐on‐action.Results and ConclusionsThe findings of this study fill a gap in the existing literature by demonstrating that the pedagogical and sequential approach embedded in the 3C Model not only enhanced students' engagement levels but also resulted in improved curriculum learning outcomes. The 3C Model provides teachers with a coherent and age‐appropriate instructional structure. It uses physical computing devices and digital coding platforms to introduce coding concepts, furthering the development of computational thinking skills in primary school students beyond mere procedural and rote learning.ImplicationsThe study holds important implications for practical applications, as it addresses an absence in the literature of an established pedagogy and instructional sequencing model for effectively teaching coding and computational thinking concepts and skills to primary school students. Drawing on established pedagogical and developmental learning theories, the 3C Model provides primary school teachers with an engaging, age‐appropriate instructional method that avoids decontextualised teaching and surface‐based learning. Instead, it encourages collaborative student work and contextualised learning, steering away from isolated and generic approaches.

Enhancing Computational and Data Science Thinking Skills for K-12 Education

Enhancing Computational and Data Science Thinking Skills for K-12 Education

Gamification and Computational Thinking in Education: A systematic literature review

The rapid development of gamification and computational thinking seems to open up new educational horizons by providing new opportunities for students to acquire the basic digital skills needed for their cognitive development. Gamification, on the side, flourishes because it brings about high degree of participants’ engagement in an activity. Accordingly, on the other side, the growing scientific interest in computational thinking centers on the fact that it provides a fruitful field of dialogue in the research community for the development of critical and analytical thinking of students. Hence, this paper aims to synthesize knowledge about gamification and computational thinking for improving education for the benefit of students. Specifically, this paper describes: (a) the theoretical background of gamification in learning and education, (b) relevant studies in literature and their findings, and (c) specific gamified applications of STEM [Science, Technology, Engineering, Mathematics] which have been developed to this subject area. Four databases were searched, and 37 papers were finally selected for this review. The findings from the presented learning theories set the foundation on how students obtain knowledge, and the relevant studies in the field of gamification and computational thinking showed some first positive outcomes stemming some first research attempts which need further examination. Furthermore, it seems that with the right use of game mechanics and elements, well-designed applications of STEM gain students’ interest to learn through gameplay and motivate them to cultivate computational thinking and problem-solving skills.

Level of Computational Thinking and Technological Literacy Skills to Improve pre-Service Teacher Learning Innovation

This study aims to assess the extent to which teachers' technology literacy skills contribute to their ability to implement innovative teaching methods through computational thinking. This study used a quasi-experimental method with a 2x2 factorial design. This research used 84 samples of prospective teacher students from the Educational Technology Study Program. The instrument used questionnaires to assess the level of instructional innovation demonstrated by aspiring teachers, utilizing three indicators: the utilization of interactive learning media, the incorporation of information technology, and the diversity of learning resources. The statistical method employed to examine the hypothesis is a two-way analysis of variance (two-way ANOVA). The results of this study showed significant correlation between the level of students' Instructional Learning Innovation skills and Computational Thinking; the statistical analysis reveals a p-value greater than 0.05. Additionally, the research findings indicate that the level of Technological Literacy Skills has an impact on Instructional Innovation Learning skills. This research made significant contributions, such as the introduction of the Computational Thinking Level, which enables teachers to enhance their capacity to create effective learning strategies that align with the most recent advancements in technology. Technological Literacy Skills assist educators in incorporating digital tools and resources into the educational process, fostering a cutting-edge and dynamic classroom setting.