Computational Thinking Skills Research Articles

Advancing computational thinking education: Insights from systems thinking applications

BACKGROUND: In today’s world, acquiring essential skills is crucial for empowering individuals, particularly children, to handle everyday challenges and tasks in a technologically advanced society. Among these skills, computational thinking (CT) plays a vital role in problem-solving and adapting to the complex and evolving demands of the 21st century. However, it is necessary to explore the role of other thinking skills alongside CT, considering that CT cannot be improved and applied in isolation. OBJECTIVE: This paper aims to address the gap in knowledge regarding the application of systems thinking to CT development and its integration into education settings. METHODS: Results from two studies, focusing on CT development using educational robotics and maker technologies, form the basis of this paper. The research findings are synthesized and consolidated using the systemic FMA (framework of ideas, methodology, and area of concern) model. RESULTS: The research findings illustrate that utilizing a diverse set of approaches, methods, and tools can improve CT skill development across different educational settings. CONCLUSIONS: The adapted FMA model promotes methodological pluralism and facilitates a critical examination of CT development boundaries, leading to both conceptual and practical changes. This approach enables the recognition of emergent properties, the design of interventions, and the incorporation of multiple perspectives.

The Vocational High School Student’s Computational Thinking Skills Comparison between Online and Offline Instructional Process in The Computer Network Subject Context

The Vocational High School Student’s Computational Thinking Skills Comparison between Online and Offline Instructional Process in The Computer Network Subject Context

Enhancing computational thinking in students with autism spectrum disorder and intellectual disabilities: a robot programming approach

Objectives Research examining computational thinking skills development via programming education using robotic teaching tools for students with Autism Spectrum Disorder and Intellectual Disabilities remains limited. This study aims to analyze the advancements in computational thinking skills among middle school students with Autism Spectrum Disorder and Intellectual Disabilities through participation in robot programming classes. Methods Problem-solving proficiency in computational thinking was assessed utilizing Brennan and Resnick’s three dimensions framework. A tailored teaching and learning approach was implemented for robot programming education, accounting for participants’ cognitive abilities and required levels of support. Four middle school students, comprising one with Autism Spectrum Disorder and three with Intellectual Disabilities, were enrolled. Results Significant enhancements were observed in all participants’ computational thinking skills across conceptual understanding, practical application, and perspective. Notably, all participants successfully resolved the final project problem at their individual proficiency levels. The acquisition of computational concepts was found to correlate positively with improved practical computational skills. Additionally, all participants demonstrated keen interest in and positive attitudes toward both robots and programming. Conclusions This study underscores the efficacy of robotic teaching tools in enhancing computational thinking skills through programming education. Additionally, it highlights considerations for enhancing students’ accessibility in future programming class design.

Nordic Approaches to Computational Thinking in Teaching and Learning

Nordic countries have recently implemented changes in the curriculum introducing computational thinking integrated in Mathematics, Natural Science, Arts and Crafts and Music. This poses challenges as well as opportunities, in particular for teacher education, as it is responsible for educating teachers who can teach computational thinking skills within these subjects.

Designing activities and tools to support university students' creative and collaborative exploration of physical computing

Today’s digital world requires students to gain skills in collaborative problem solving and digital literacy. One approach is to teach people how to design computational artefacts that require both electronics and programming. Physical computing platforms offer an endless amount of possible opportunities for people to design and develop technological artefacts. However, many times students are overwhelmed when trying to learn both software and hardware simultaneously. The students struggle to be innovative and creative in their projects. Also, they focus on mastering the tool and following instructions for existing projects rather than being able to creatively explore the tool and understand the process of designing and developing new artefacts. For that reason, we aimed to answer the question: What type of tools and activities can be developed to support university students creative exploration of physical computing? Programming and electronics are fundamental design disciplines in today's digital world, and therefore they should be taught through design activities rather than limiting education to textbook readings and laboratory exercises. We introduce our process of designing activities combined with a supportive tool to ease these challenges. The activities and tools were developed iteratively in three phases with a series of workshops with 126 students and teachers. The tool consists of a set of paper cards that provide necessary details (hints) about the electronics and software and help provide structure for the students to conceptualise how their artefact interacts. We additionally, introduced a learning Jigsaw pattern (orchestration script) for the later intervention that enabled individual students in the groups to focus on design, hardware, or software. For evaluation, we used the Creativity Support Index (CSI), which is a psychometric survey designed to assess the support of the creative process. The instrument investigates collaboration, efforts worth the result, exploration, immersion, enjoyment, and expressiveness. The results between the phases showed improvement with the use of the refined versions of the cards and orchestration of the learning activity. This study has demonstrated that design activities can provide a more accessible approach for the introduction of physical computing to students from various majors. Moreover, learning physical computing through design activities allows the learner to develop computational and design thinking skills for collaboratively solving problems.

Improving Unplugged Computational Thinking Skills Through Integrated Problem-Based and Differentiated Learning in Indonesia

Industry 4.0 era is characterized by the development of technology and the existence of flexible and effective data exchange. This has an impact on the emergence of new jobs that require the ability to solve problems effectively and efficiently, especially computational thinking. This Classroom Action Research aims to improve students’ computational thinking (abstraction, data collection, data analysis and algorithms) in solving problems about probability through problem-based learning integrated with differentiation learning. This research was conducted in four stages: planning, implementation, observation, and reflection. Thirty-four students of class X-E7 SMA Negeri 5 Surakarta in Indonesia were the subjects of this research. It was concluded that the application of problem-based learning model integrated with differentiated learning (content and process) significantly improves students’ computational thinking skills and promotes cognitive development through problem-solving activities. The improvement of computational thinking ability is caused by: data collection activities in the form of dice/coin simulations, abstraction activities of sample points and important information in the problem, activities to formulate solution steps (algorithms) and data analysis activities in the form of interpretation of results and calculations. Differentiated learning (content and process) plays a role in improving students’ computational thinking through ability-based scaffolding and content based on their interests and learning modalities.

Development of Computational Mathematic Thinking Test Instruments Based On Computered Based Test

This reseacrh is a type of development reseacrh. The aims of this research is to develop an instrument for mathematical computational thinking tests based on Computer Based Testing (CBT) using the Quizizz application, evaluate the validity of the developed test instrument, and analyze the mathematical computational thinking abilities of students. The ADDIE model (Analysis, Design, Development, Implementation, and Evaluation) is adopted as the method in this research. A total of 52 students from classes X and XI of SMA Muhammadiyah 1 Surakarta were involved in this study as research subjects. Data analysis was conducted using the Rasch model with the assistance of Winsteps Rasch software. The results of this research indicate that 20 items are categorized as valid. The overall test reliability is 0.62, classified as sufficient, while the reliability of the test items is 0.88, classified as good. Test analysis of the level of difficulty of test items reveals that there are 3 items categorized as very difficult, 7 items categorized as difficult, 5 items categorized as moderate, and 5 items categorized as easy. In general that the computational thinking skills test does not show a tendency to be biased in any question item, because all probability values for the question items exceed 0.05. Items are considered unbiased if they do not give an unfair advantage to any one individual. Based on the experiment in this study, the average mathematical computational thinking ability of class X students is 75.53, while for class XI students it is 79.37.

High-Capacity Robots in Early Education: Developing Computational Thinking with a Voice-Controlled Collaborative Robot

This study investigates the potential of a voice-controlled collaborative robot to promote computational thinking (CT) skills in preschoolers aged 4 to 6 in Southern Chile. During a week-long workshop, 34 children engaged in activities designed to develop several CT components while interacting with a robotic arm. Pre- and post-workshop assessments utilizing the TechCheck-K tool revealed significant improvements in CT skills. The findings of this preliminary study demonstrate the effectiveness of voice-controlled robots as innovative tools in early education, significantly enhancing young learners’ understanding of CT concepts, practices, and perspectives. This research advocates for further exploration of robotic integration in educational settings, highlighting their potential to improve or extend preschool learning environments and foster CT skill development.

Learning Style Factors in Achieving Mathematical Computational Thinking Ability in Mathematics Education Students

Learning styles refer to the methods students use in absorbing and processing information. This study aims to look at learning style factors in the achievement of mathematical computational thinking skills of mathematics education students in the Algebraic Structure course. This research method is a correlational method with a quantitative approach. The research subjects were all mathematics education students who took the Algebraic Structure course in the 2023/2024 academic year as many as 34 students. The data collection methods used include: (1) computational thinking test; (2) questionnaire; and (3) documentation. The research data were processed with the Product Moment correlation statistical test. The results obtained a positive correlation of 0.44 which indicates that there is a positive relationship between learning styles and computational thinking in the observed students. That is, overall, individuals who have a more effective or intensive learning style also tend to have better computational thinking ability.

Analysis of mathematical computational thinking skills in the context problem solving based on gender

Analysis of mathematical computational thinking skills in the context problem solving based on gender

Analisis Bibliometrik: Fokus Penelitian Metode Scaffolding terhadap Kemampuan Computational Thinking (2016-2022)

The aim of this bibliometric analysis is to identify opportunities and trends in research related to the Scaffolding method's impact on Computational Thinking skills. The bibliometric method was used with data collection of articles from 2016-2022 through Google Scholar using the Publish or Perish software, yielding 1,000 articles. The study results showed that 50 articles were published from 2016-2022. Visualizations in the analysis using VOSviewer can be seen in the form of network visualization, overlay visualization, and density visualization. The network visualization map is used to see the interrelationships and clusters of research themes based on keywords. Overlay visualization is used to identify the years when related research themes were conducted. Meanwhile, density visualization is used to analyze research themes that are saturated and those that are still rarely studied. Based on data analysis using VOSviewer, the research trend on Scaffolding dan Computational Thinking from 2016 to 2022 is relatively new and has rarely been conducted previously.

Gender Differences in Computational Thinking Skills among Primary and Secondary School Students: A Systematic Review

With the rise of the concept of gender equality and the emphasis on computational thinking, more and more research on computational thinking is being placed in the context of gender differences to promote gender equality. This systematic review examines and analyzes 23 articles that focus on gender differences in computational thinking skills among primary and secondary school students, providing a comprehensive overview of the existing literature while also providing direction and framework for future research. The results show that (1) the current research is imbalanced across regions and age groups, and the research on inherent gender differences in computational thinking skills remains insufficient; (2) the development of a clearer and more specific definition of computational thinking and corresponding assessment instrument is required for a more specific identification of gender differences; (3) under the existing educational environments, gender differences in computational thinking skills among students in different regions exhibit different pattern; and (4) interventional factors contributing to gender effects in interventions have also been identified.

Educational policy as predictor of computational thinking: A supervised machine learning approach

AbstractBackgroundComputational thinking is derived from arguments that the underlying practices in computer science augment problem‐solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational policies on computational thinking remains unclear.ObjectivesThis study examines the impact of basic and technology‐related educational policies on the development of computational thinking.MethodsUsing supervised machine learning, the computational thinking achievements of 31,823 eighth graders across nine countries were analysed. Seven rule‐based and tree‐based classification models were generated and triangulated to determine how educational policies predicted students' computational thinking.Results and conclusionsPredictions show that students have a higher propensity to develop computational thinking skills when schools exercise full autonomy in governance and explicitly embed computational thinking in their curriculum. Plans to support students, teachers and schools with technology or introduce 1:1 computing have no discernible predicted influence on students' computational thinking achievement.ImplicationsAlthough predictions deduced from these attributes are not generalizable, traces of how educational policies affect computational thinking exist to articulate more fronts for future research on the influence of educational policies on computational thinking.

The Effects of Designing Scientific Experiments with Visual Programming Language on Learning Outcomes

AbstractWhen the studies on the effectiveness of visual programming language are examined, it is seen that studies on coding teaching have been carried out frequently recently. In this study, Scratch was used as a teaching tool in teaching science lessons. In this way, a new perspective has been brought to Scratch applications. In the related study, the effects of designing science experiments with visual programming language (Scratch) on students’ beliefs of self-efficacy related to computational thinking (CT) skills, metacognitive awareness levels, and motivation levels for science learning are examined. This study was carried out using a single-group research design based on pretest and posttest applications. Students attending the fifth grade participated in this study. Sixty-five students attending the fifth grade participated in the research. Research data were obtained using “Self-Efficacy Perception Scale for CT Skills (SEP_CTS),” “Metacognitive Awareness Scale (MAS),” and “Motivation Scale for Science Learning (MSSL).” The research process is 10 weeks and 3 days in total. It was determined that designing science experiments in visual programming language applications based on Scratch improved students’ CT self-efficacy perceptions, but did not have the expected effect on students’ science learning motivation and metacognitive awareness. This research provides evidence that some skills can be improved by using Scratch as a teaching tool in different courses. With the focus of research on this subject, it can contributed to the development of new understandings of Scratch in teaching processes.

The Effect of Computer-Supported Stem Applications on Secondary Students' Achievement and Computational Thinking Skills

In this study, the effect of STEM applications integrated with computer- supported materials on mathematics achievement in the subject of ratio-proportion and percentages was examined. In addition, it was aimed to reveal the effect of these applications on computational thinking skills. Furthermore, we aimed to reach the opinions of the experimental group students about the materials they used, STEM applications, and the application process. A mixed method was used with a sample consisting of 89 students in grade 7 of a secondary school. An achievement test, a scale of levels of computational thinking, and learning diaries were used as tools for data collection. The data were analyzed using t-test and content analysis. It was found that there was a significant difference between the experimental and control groups in terms of achievement in favor of the experimental groups. In terms of computational thinking, there was a significant difference in favor of the experimental groups, except for the creativity aspect of computational thinking skills. Based on the findings obtained with the computational thinking skills scale the study had a positive impact on most aspects of computational thinking. Accessed through the learning diaries students' views on learning with STEM applications were generally positive. In particular, the opinions on computer-supported materials pointed to a very satisfactory process. The findings suggest that the inclusion of STEM activities and the use of computer technology in education contribute to students' computational thinking skills and learning.

The use of makerspaces for the development of computational thinking skills and dispositions: pedagogical practices facilitators use

ABSTRACT Background and Context Focusing on computational thinking (CT) as the process to integrate computer science across subjects, and making as the activity to engage in this process, is a promising way to introduce students to computing. However, there is little guidance on what practices instructors should employ in maker activities to support CT skill/disposition development. Objective With this study, I aim to answer the question: Within makerspace activities what evidence exists regarding promising practices that support youth development of CT skills and dispositions? Method This case study takes place in a summer makerspace program, in which I examine the interactions of four facilitators with seventeen high school-aged participants through video, audio, screen recordings, participant notebooks, and observer field notes. Findings Findings inform our understanding of practices instructors can utilize in making activities to assist students in advancing their CT skills/dispositions: tinkering, embodiment, walkthroughs, drawing, and debugging. Implications In a making environment where tinkering is promoted, instructors need to provide explicit guidance in the application of CT while tinkering . This guidance can happen through the intentional application of practices that connect making to CT using cognitive apprenticeship, making conceptual knowledge more explicit. What the findings also suggest is that there is no clear-cut delineation between computational thinking, doing, or designing.

The Analyze Comparative of Physics Computational Thinking Skill (CTs) in Experiment Laboratory

Objective: This study aimed to analyze students' response to the use of computational thinking from the perspective of computational tools and to analyze the influence of gender on students' computational thinking skills. Method: Research design using a comparative approach with data collection techniques involved a survey using a Likert scale questionnaire comprising 25 items, covering five dimensions of computational thinking skills: abstraction, decomposition, algorithm thinking, evaluation, and generalization. The study subjects involved five classes: physics, physics education, geography, mining engineering, and vocational-technical education, focusing on students' ability to analyze data using JASP and IBM SPSS. The data analyze methods included: (1). Comparative Analyze; (2). Correlation analyzes (Spearman); (3). Chi-square test. Finding: The results showed that the computational thinking skills of students from various classes varied, with significant correlations between the skill dimensions. Physics and Physics Education stood out with exemplary achievements, while Geography and Mining Engineering also showed good progress. The vocational-technical education program displayed nearly perfect correlations in all aspects of computational thinking skills. Meanwhile, from the gender aspect, gender significantly influenced computational thinking skills (Sig<0.00). The analyze highlighted the differences in computational thinking skills between classes and the significant influence of gender. Implication: This emphasized the importance of developing computational thinking skills in higher education and the need for inclusive approaches to enhance computational excellence among students. The implications of this study give valuable insights for improving the teaching of computational thinking in physics education. Steps that might be addressed include identifying and enhancing weak components, such as abstraction and generalization, and using particular tactics to increase students' knowledge.

Effects of Teachers’ Media Utilization and Computational Thinking on Sustainable Development in Early Childhood Education

(1) Background: The study aims to analyze the degree of media use among early childhood teachers and the correlations between their computational thinking, playfulness, creativity, and problem-solving abilities. It confirms a strong correlation between playfulness and problem-solving abilities and investigates whether higher levels of computational thinking are associated with higher levels of playfulness. This research is positioned within the context of sustainable development in early childhood education, emphasizing the importance of integrating digital literacy and computational thinking skills to promote sustainability. (2) Methods: The research was conducted on teachers working in daycare centers and kindergartens in Jeju Island, South Korea. A total of 203 questionnaires were collected, employing descriptive statistics, frequency analysis, Pearson’s correlation coefficient analysis, one-way ANOVA, and multiple regression analysis. (3) Results: The study found that teachers’ degree of media literacy affects their media use. Additionally, the higher the degree of computational thinking, the more significant the effect on early childhood teachers’ playfulness. Furthermore, early childhood teachers’ playfulness, creativity, and problem-solving skills were all significantly correlated overall. (4) Conclusions: The findings suggest that if teachers take an interest in IT media and find ways to use it positively, it will have a positive effect on early childhood education. Moreover, increasing computational thinking skills will enable the effective use of various tools, positively impacting teachers’ roles. The study proposes that enhancing early childhood teachers’ playfulness, creativity, and problem-solving skills will contribute to sustainable development in early childhood education.

The relationship between computational thinking and mental rotation ability: a functional near-infrared spectroscopy study

ABSTRACT This study investigates the correlation between computational thinking (CT) skills and mental rotation ability, utilizing functional near-infrared spectroscopy (fNIRS) to assess neural efficiency as a potential underlying factor. We divided 38 participants into groups with high and low CT skills to perform mental rotation tasks. Prefrontal brain activity was monitored via a 48-channel fNIRS system. The experimental results suggested that participants possessing superior CT skills exhibited enhanced performance on the mental rotation test, accompanied by a higher neural efficiency index in the specified cerebral regions, as denoted by reduced oxygen consumption. This implies that individuals endowed with advanced CT capabilities can process information with greater efficacy, thereby attaining superior performance utilising lesser cognitive exertion. Our study offers some of the first empirical evidence regarding the neural basis underlying the relationship between CT skills and mental rotation ability in undergraduate students.

Extraction of Knowledge Models from Textbooks

Isaac Alpizar-Chacon is an assistant professor in the Software Technology for Learning and Teaching group at the Department of Information and Computing Sciences, Utrecht University. In addition to his primary role, he is also an associate professor at the Instituto Tecnológico de Costa Rica. His research interests focus on the impact of GenAI tools in computing education, the integration of these tools into the classroom, the teaching and learning of computational thinking skills, and knowledge extraction. Dr. Alpizar-Chacon holds a MSc degree in Computer Science from Saarland University (Saarbrücken, Germany) and a PhD degree in Information and Computing Sciences from Utrecht University (Utrecht, Netherlands). Homepage: https://isaacalpizar.info/