Computational Thinking Skills Research Articles

Computational Thinking Assessment in Primary and Secondary Education: A Meta-synthesis of tools, Methods and Pedagogical Approaches

Despite the widespread adoption of computational thinking (CT) across educational levels, challenges persist in its assessment due to diverse definitions, frameworks, and its practical application in classroom settings. This meta-synthesis investigates the assessment of computational thinking (CT) in primary and secondary education, synthesizing evidence from 12 reviews across five international databases, focusing on tools, methods, and pedagogical practices employed in assessing CT, with the aim to outline practical approaches for evaluating CT components. The review delves into the primary focuses of these syntheses, the CT skills and components assessed, and the methods and tools utilized, identifying gaps in current practices. The findings highlight a prevalent focus on programming skills, with less emphasis on cognitive processes and collaborative aspects of CT. The synthesis also points to the need for developing assessment tools and methods that encompass the broader spectrum of CT skills, suggesting avenues for future research and practical application in educational settings.

Examining Teachers’ Computational Thinking Skills, Collaborative Learning, and Creativity Within the Framework of Sustainable Education

This study seeks to explore the relationship between science teachers’ computational thinking skills, collaborative learning attitudes, and their creativity in the context of sustainable education. The study adopted an explanatory sequential design, which is one of the designs used in mixed-method research. A total of 369 science teachers were included in the quantitative phase of the study. Quantitative data were collected using three different scales. These scales included the “Computational Thinking Scale”, “Online Cooperative Learning Attitude Scale (OCLAS)”, and “Creative Self-Efficacy Scale”. Structural Equation Modelling (SEM), confirmatory factor analysis, and path analysis were conducted to analyze the quantitative data. The qualitative phase of the study consisted of nine science teachers. Data were collected with a semi-structured interview form by considering the scores obtained from the scales. Qualitative data were analyzed through descriptive analysis. It was found that science teachers’ computational thinking skills and collaborative learning attitudes significantly predicted their creativity within the framework of sustainable education. As a result of the interviews conducted, it was concluded that science teachers lacked computational thinking skills. It is critical to provide teachers with guidance on how to integrate computational thinking skills into their subject areas. Science teachers’ knowledge of computational thinking skills can be enhanced, and computational thinking skills can be included in all teacher education programs.

Strengthening Computational Thinking in Engineering and Health Students Through Iot Activities and Block-Based Programming

Objective: The objective of this study is to evaluate computational thinking skills in engineering and health students at a public university in Peru. Theoretical Framework: To support the research, various theories on computational thinking, IoT, and block-based programming were reviewed. Additionally, evaluation instruments and problem-solving steps were analyzed. Method: These activities were developed using technological resources and block-based programming, integrated into an IoT environment. A quasi-experimental design with pre- and post-tests was employed to measure the impact of IoT activities and block-based programming in the classroom. Results and Discussion: The results obtained revealed [synthesize the main results of the research]. In the discussion section, these results are contextualized in light of the theoretical framework, highlighting the implications and relationships identified. Possible discrepancies and limitations of the study are also considered in this section. Research Implications: The results revealed that both engineering and health students improved their computational thinking skills in a balanced manner. However, it was observed that health students placed greater emphasis on the use of sensors, actuators, and block-based programming. Originality/Value: This study enriches the literature by applying methods that integrate technological resources in the classroom. The relevance and value of this research are evident in the urgent need to develop innovations that break the monotony of traditional educational approaches, offering students more dynamic learning experiences.

Analysis of Gender Issues in Computational Thinking Approach in Science and Mathematics Learning in Higher Education

In the contemporary era, Computational Thinking has emerged as a crucial skill for individuals to possess in order to thrive in the 21st century. In this context, there is a need to develop a methodology for cultivating these skills within a science and mathematics content education framework, particularly among pre-service teachers. This study aimed to investigate the impact of Educational Robotics on the development of Computational Thinking skills, with a particular focus on the role of gender, through a scientific and mathematical content teaching approach. A pre-experimental design with a quantitative approach was employed, and it was implemented with a total of 116 pre-service teachers, 38 males and 78 females. The results demonstrated a notable enhancement between the pre-test (8.11) and post-test (9.63) scores, emphasising specific concepts such as simple functions, while, and compound conditional. With respect to gender, statistically significant differences were identified prior to the intervention, but not following its implementation. The high level of Computational Thinking exhibited by both genders was comparable (53.85% in females and 55.26% in males) following the intervention. This indicates that the intervention is a promising approach for enhancing Computational Thinking proficiency, independent of gender and initial proficiency levels. The implementation of Educational Robotics in the teaching of science and mathematics enables the enhancement of Computational Thinking abilities among pre-service teachers, while reducing the observed gender disparity in this area of skill development.

Improving the Computational Thinking Abilities of Junior High School Students Through Problem-Based Learning

Computational Thinking is a crucial skill that students must master in the 21st century. Computational Thinking encompasses a systematic process that enables individuals to formulate problems, develop strategies, and find effective, efficient, and reusable solutions. This research aims to enhance students' Computational Thinking abilities through the application of the Problem-Based Learning (PBL) model, which is effective in facilitating active learning and problem-solving. The methodology used in this study is Classroom Action Research (CAR) with a spiral approach developed by Stephen Kemmis and Robin McTaggart. Data collection is conducted through post-tests administered at the end of each cycle phase. The obtained data are analyzed using a designed assessment rubric, wherein students are categorized based on their Computational Thinking abilities and foundational Computational Thinking skills. The results indicate that by the end of Cycle II, of students achieved a moderate to high level of Computational Thinking ability. These findings affirm that the implementation of the Problem-Based Learning learning model can significantly improve students' Computational Thinking skills.

Promote students’ computational thinking in rural areas: The moderating role of gender

The purpose of this study was to assess rural students’ computational thinking abilities. The following proofs were observed: (1) Students’ abstraction affected algorithmic thinking skills; (2) Students’ decomposition influenced algorithmic thinking skills; (3) Students’ abstraction impacted evaluation skills; (4) Students’ algorithmic thinking affected evaluation skills; (5) Students’ abstraction impacted generalization skills; (6) Students’ decomposition impacted generalization skills; (7) Students’ evaluation affected generalization skills. Gender differences were observed in the relationship among the computational thinking factors of junior high school students. This included the abstraction-generalization skills; evaluation-generalization skills; and decomposition-generalization skills relationships, which were moderated by the gender of the students. 258 valid surveys were collected, and they were utilized in the study. Conducting the descriptive, reliability, and validity analyses used SPSS software, and the structural equation modeling (SEM) was also conducted through Smart PLS software to assess the hypothetical relationships. There were gender disparities in the correlation among computational thinking components of the junior high school students’ studying in rural areas. Research has shown that male and female students may have different abstractions, evaluations, and generalizations related to computational thinking, with females being more strongly associated than males in non-programming learning contexts. These results are expected to provide relevant information in subsequent analyses and implement a computational thinking curriculum to overcome the still-existing gender gaps and promote computational thinking skills.

Expanding Digital Literacies Beyond the Digital: Infusing Computational Thinking into Unplugged Pedagogical Tools - Two Case Studies from Mathematics Education

Computational Thinking (CT), the conceptual foundations required for solving complex problems effectively and efficiently, is an imperative skill for today’s learners, across disciplines and across ages. As for its importance in the wide network of digital literacies, CT has been implemented in various educational contexts, however mostly via digital artifacts, specifically in programming-related activities. This approach does not fulfill the potential of such integration for promoting learning. In this paper, we argue that digital literacies should not be bound to the digital realm, and present a novel approach to fully integrate CT into learning and teaching by the development of CT-infused “unplugged” pedagogical tools that are fully embedded in the subject matter. We demonstrate the advantages to student learning of these tools in two case studies from K-12 mathematics education: 1) An assistive tool for function investigation in high-school calculus – in this case, we point out to how CT skills that were implemented in the tool promoted students’ problem solving; 2) A teaching unit for pattern sequences in elementary school – in this case, we show how students in the CT research group outperformed students in the other groups, and how they implemented CT to solve pattern sequence problems effectively and efficiently. We highlight that besides enhancing learning, this approach can help address the important issue of equity in education, and suggest ways to promote it via dedicated professional development.

Development of STEM-Based Science Educational Game Using Scratch to Train Computational Thinking Skill for Socondary School Students

Computational Thinking Skills (CTS) possessed by Indonesian students are not yet in the good category. This skills have not been integrated in learning. This is in accordance with the results of preliminary research at SMP Negeri 8 Semarang that CTS are a new concept for science teachers, including learning media used by teachers have not helped train students' CTS. Through preliminary research, it is known that science teachers give a positive response to the use of technology-based learning media that train students' CTS, one of which is a science educational game using Scratch. The purpose of this study was to analyze the validity and determine the profile of students' CTS after using science educational games. The type of research used is development research with the ADDIE model. The instruments used are expert validation questionnaires, student readability sheets, and tests after using science education games. The results showed that the science education game was valid with a score of 0.89. The readability of science education games is very good with a score of 96.7. Through the test, it was found that the percentage of students with high computational thinking ability was 56.66%, medium 26.66%, and low 16.66%. Based on the research that has been done, it can be concluded that the science education game is valid and can train CTS of junior high school students.

Enhancing computational thinking in children through logical puzzles: A machine learning approach for early coding education

This recent growth in early education in coding evidences the rising need for the computing-thinking-skills development in children. Though most of the programming curricula are based upon syntax and other basic concepts of coding, computational thinking encompasses broader cognitive skills, such as problem-solving, abstraction, and logical reasoning. This research therefore intends to fill a gap in research and will investigate the ways pre-coding games employ logical puzzles as an enhancement in developing computational thinking skills in children aged 7-10 years and how these affect the acquisition of programming knowledge. In all, there will be two groups assigned: one will be exposed to logical-oriented puzzle training, Group A, and the other will be a control group, Group B, which receives only regular standard lessons in programming introduction. Pre- and post-measures of computational thinking and basic programming skills will be obtained from the participants. The machine learning algorithms, such as Random Forest for prediction in terms of improvement in subject performance in computational thinking and K-Means clustering to identify patterns in their development of skills, will be implemented in their pure or integrated forms to analyze data. Logistic Regression will be executed in order to model the odds of improved performance in programming given an intervention of exposure to puzzles. The research study will, therefore, apply these algorithms in comparing the performance of the two groups and reveal the aspects of computational thinking to which the greatest influence in a positive way through puzzle activities is exerted. It is expected that children exposed to logical puzzles may show significant improvements in both computational thinking and programming skills. These findings should be useful to educators in their effort to show how logical puzzles can be integrated into the curricula of early coding education to build foundational skills and thereby contribute to a refinement of best practices in STEM education.

Investigation of Computational Thinking Skills through Instructional Techniques, Games and Programming Tools

Computational thinking (CT) has become a vital approach to problem-solving. This method has been proven successful in various areas, especially science, technology, engineering, mathematics (STEM), and professional development. The integration of CT in education provides a practical approach to solving problems. This concept paper investigated the various uses of instructional techniques and programming tools to enhance CT skills used in previous empirical research. CT consists of four main pillars: decomposition, which refers to breaking down identified problems into smaller parts; pattern recognition, which involves finding occurring patterns that can be seen; abstraction through identification of important details and removing unnecessary information; and algorithm, where a step-by-step procedure is solution is made. By exploring instructional strategies and programming environments, this paper outlines the possible impacts of these instructional strategies, games, and programming environments on improvement in CT skills, thus providing a theoretical basis for future empirical studies. The strength and combination of these approaches provide a comprehensive learning experience. This paper also suggests instructional techniques and programming tools to enhance underexplored CT skills based on research gaps.

Game On: A Journey into Computational Thinking with Modern Board Games in Portuguese Primary Education

Recent studies highlight the potential of modern board games (MBGs) to foster computational thinking (CT) skills in students. This research explored the impact of integrating MBGs into a primary education classroom through an embedded concurrent mixed-methods approach, with a pre-experimental design in its quantitative aspect and content analysis in its qualitative dimension, with 20 fourth-grade students from a school in Portugal. The students participated in 10 game sessions, each lasting 50 min, and their CT skills were assessed using Bebras tasks in both the pre-test and post-test phases. Statistical analysis, including the Shapiro–Wilk test for normality and paired sample t-tests, revealed significant improvements in key CT areas, particularly abstraction, algorithmic thinking, and decomposition. Descriptive statistics were also calculated, and content analysis using Nvivo software was conducted on field notes, corroborating the quantitative data. The results suggest that MBGs can serve as a valuable educational tool for developing CT skills in young learners. This study not only highlights the effectiveness of MBGs but also emphasises the need for further research using more robust experimental designs to enhance CT development in educational settings.

Arduino-Based Mobile Robotics for Fostering Computational Thinking Development: An Empirical Study with Elementary School Students Using Problem-Based Learning Across Europe

The present article explores the impact of educational robotics on fostering computational thinking and problem-solving skills in elementary school students through a problem-based learning approach. This study involved the creation of a framework which includes a robot and two eBooks designed for students and teachers. The eBooks serve as a guide to the construction and programming of a small Arduino-based robot. Through integration with gamification elements, the model features a narrative with three characters to boost a student’s engagement and motivation. Through iteration of heuristic evaluations and practical tests, we refined the initial theoretical framework. An empirical study was conducted in two phases involving 350 students. The first empirical test involved a small group of 21 students, similar to end users, from five European schools. With a 100% completion rate for the tasks, 73.47% of these tasks were solved optimally. Later, we conducted a larger validation study which involved 329 students in a Portuguese school. This second phase of the study was conducted during the 2022–2023 and 2023–2024 school years with three study groups. The results led to a 91.13% success rate in problem-solving activities, and 56.99% of those students achieved optimal solutions. Advanced statistical techniques, including ANOVA, were applied to account for group differences and ensure the robustness of the findings. This study demonstrates that the proposed model which integrates educational robotics with problem-based learning effectively promotes computational thinking and problem-solving skills, which are essential for the 21st century. These findings support the inclusion of robotics into primary school curricula and provide a validated framework for educators.

Investigation of Higher Education Students' Computational Thinking Skill Levels

Computational thinking skill is a skill that has its origins in ancient times but has gained importance today. The competences provided to individuals by computational thinking skills are also of great importance for the education system. Therefore, it is important for students to acquire and develop these skills in order to adapt to the requirements of the modern world. Based on this, in this study, the level of information processing thinking skills of higher education students was examined and the level of this skill was investigated in line with different variables. 'Computational Thinking' scale was used as a data collection tool in the study. Cronbach Alpha internal consistency coefficient of the scale. 96 was calculated as. Demographic characteristics such as gender, department, class and education level were taken into consideration. Quantitative research method was used in the study. The research was conducted with 298 participants studying in higher education. In the analysis of the data, independent t-test and ANOVA analyses were applied to determine the score differences between the groups. As a result of the study, higher education students were found to have high levels of computational thinking skills. Gender was found to be effective on computational thinking skills. As the level of education increased, it was determined that computational thinking skills increased. It was seen that the education given in different departments had an effect on computational thinking skills. Finally, it was found that there were significant changes in students' computational thinking skills as their grade level increased.

Supporting Educators to Co-Design Interdisciplinary Projects Integrating Educational Robotics and Arts

The growing call to foster interdisciplinary learning has found educators struggling to co-design learning across disciplinary boundaries. Aiming to contribute to the area of interdisciplinary learning design, we explored how to support educators in co-designing interdisciplinary projects integrating Educational Robotics (ER) and Arts, hereafter called Artful ER projects. Our research included developing the "FERTILE" Learning Design methodology as a conceptual tool scaffolding the integration of discipline-oriented viewpoints while educators co-design. Acknowledging that one of the challenges in interdisciplinary collaboration derives from educators’ different intentions for students’ learning outcomes, the "FERTILE" methodology introduces Computational Thinking (CT) skills as an Artful ER project’s primary learning outcome. In this line, the “FERTILE” methodology adapts the Creative Computational problem-solving model, which has been reported to cultivate CT skills through its staged process. Furthermore, we developed the "FERTILE" Community Platform as an online environment providing two-fold support to educators as designers of interdisciplinary learning. The "FERTILE" Community Platform incorporates community functionalities that address collaboration practicalities while educators co-design. Additionally, it integrates authoring functionalities scaffolding educators in designing Artful ER projects based on the "FERTILE" Learning Design methodology. This paper explores how the authoring functionalities of the "FERTILE" Community Platform support educators in designing interdisciplinary learning. We report on a pilot study conducted with Greek and Spanish educators. In this study, we applied a mixed-method research design with a quantitative strand adopting indicators from the Usability Metric for User Experience (UMUX) model and a qualitative strand providing insights into participants’ perceptions. The findings indicate that scaffolding disciplinary elaboration (e.g., robot technical requirements and art forms) and systematising interdisciplinary context (e.g., through project categories) may trigger educators’ mutual understanding. The participants endorsed authoring functionalities that adopted high contextualisation levels for learning design representation to communicate their design ideas across disciplinary boundaries. Also, the participants valued CT skills as the primary outcome of interdisciplinary learning, indicating that CT skills’ cultivation may be the broker among disciplines and trigger educators to overcome disciplinary barriers. Finally, we discuss the findings and implications for refining the "FERTILE" Community Platform as an online environment for educators co-designing Artful ER projects.

Review on pedagogical practices for computational thinking in teacher education

As computational thinking (CT) enters school curricula, and research on teaching of CT emerges, the time has come to spotlight CT in teacher education (TE). To this end, we conducted a literature review on CT in TE for STEM subjects with particular focus on research into pre-service teachers’ (PSTs) learning of pedagogical practices. We found 31 articles addressing CT in TE for STEM subjects between 2012 and 2023, applying qualitative, quantitative, and mixed methods, mainly with smaller sample sizes. Almost all describe teaching interventions with research on PSTs’ CT skills or attitudes. Only five articles include research questions explicitly addressing pedagogical practices for learning to teach CT. However, 13 articles explicitly describe such pedagogical practices and another seven implicitly do so. The review shows that the practices for teaching CT is an under-researched area, and the field lacks a common language and systematic research approaches. However, we do find that TE has clear ambitions for teaching PSTs about pedagogical practices as well as CT skills and attitudes.

Model Implementation Problem-Based Learning with a Differentiated Learning Approach to Improve Abilities, Computational Thinking Student

Based on the results of the non-cognitive diagnostic assessment conducted by the author in class X PPLG 1 SMK Negeri 11 Bandung, the computational thinking abilities possessed by students still need to improve. In addition, based on the results of observations, teachers have not implemented differentiated learning optimally. This study aims to improve students' computational thinking abilities by applying problem-based and product-differentiated learning models. The research method used is Classroom Action Research (CAR), carried out in 3 cycles. The subjects of this study were 20 students of class X PPLG 1. The results of this study show that applying the PBL model and product-differentiated learning can improve student learning outcomes in the DPLG subject, with the achievement of completeness in cycle I at 45%, cycle II at 70%, and cycle III at 45%. Students' computational thinking abilities also increased from achieving completeness of 10% to 75%. The effectiveness of learning carried out in cycles I and II are included in the reasonably practical category, as evidenced by the N-gain of 60% and cycle III of 41%, which can improve students' computational thinking skills.

Instrumen Literasi Numerasi Berbasis Kemampuan Berpikir Komputasi pada Matematika SMP: Pembuktian Validitas Isi dengan Aiken’s.

This research aims to prove the content validity of a numeracy literacy instrument based on computational thinking skills using Aiken's method. There are five questions divided into nine parts, all of which focus on the material “Algebraic Forms”, ​​and have been validated by five validators from two leading universities. The data analysis technique applied is the Aiken's method, which is used to assess the extent to which this instrument meets the validity criteria. The results of the analysis show that most of the questions in the instrument received good validity scores, with an average validity of 0.81. This score indicates that this instrument is relevant and effective for measuring students' abilities in numeracy literacy and computational thinking. Apart from that, input from validators regarding the use of simpler language for grade 8 students is very valuable and is expected to improve students' understanding of the questions given. It is hoped that these results can contribute to the development of higher quality educational evaluation instruments, as well as being the basis for further research involving instrument testing to prove construct validity and reliability in the context of mathematics learning

Enhancing Computational Thinking, Spatial Reasoning, and Executive Function Skills: The Impact of Tangible Programming Tools in Early Childhood and Across Different Learner Stages

Enhancing Computational Thinking, Spatial Reasoning, and Executive Function Skills: The Impact of Tangible Programming Tools in Early Childhood and Across Different Learner Stages

Developing Computational Thinking through Mathematics Learning in Indonesia: Scientific Mapping and Bibliometric Analysis

This research aims to explore and map the teaching methods used in developing Computational Thinking (CT) through mathematics learning in Indonesia, using a bibliometric analysis approach. Based on a literature review from Scopus and Sprott-indexed databases, this research analyzes trends, contributions and challenges in the implementation of CT at various levels of education. Teaching methods such as Scratch, Problem-Based Learning (PBL), Augmented Reality (AR), and robotics were identified as the most effective strategies in improving students' computational thinking skills. The findings show that the majority of publications published in educational and CT-related sources about teaching mathematics are mostly about teaching computational skills and teaching computer programming using practice and algorithmic thinking, although these methods have had a significant impact, some limitations, such as lack of instrumentation, limited technological resources, and curriculum adaptation are still challenges. This analysis also highlights opportunities for further research in developing more comprehensive evaluation instruments and improving technology access in computational education. It is hoped that the results of this research can provide guidance for educators, policymakers and researchers to increase the integration of CT in the mathematics curriculum, as well as expand the scope of computational research in the Indonesian educational context. This research opens new insights to overcome barriers and optimize the potential of CT in the future.

지식재산 일반 교과를 통한 특허명세서 작성 교육의 시사점 및 개선 방안

Objectives This study scrutinizes the teaching of patent specification writing through the general intellectual property course, draws implications, and suggests ways to improve the 2022 curriculum. Methods This study was conducted in the following ways First, we compared and analyzed the documents of the general intellectual property curriculum of the 2015 and 2022 curricula to identify changes in the achievement standards related to patent specification writing education. Second, we systematically reviewed textbooks, teacher guides, and teaching and learning materials to investigate the content and methods of patent specification writing education in actual educational settings. Third, we analyzed the requirements of patent specification writing education and the differences between domestic and foreign countries by reviewing relevant laws and regulations such as the Patent Act and the Patent Act Enforcement Rules, and identifying international trends through overseas cases. Fourth, we verified the feasibility and effectiveness of patent specification writing education through generative AI by utilizing actual patent specification and Chet Giffity. Through this multifaceted analysis, we identified problems in the current patent specification writing education through general intellectual property courses and proposed improvement measures. Results The implications of patent specification writing education through general intellectual property courses are, first, that it does not fulfill both relevant performance standards and legal requirements. Second, there is a lack of consideration on the selection of invention ideas that are the subject of patent specification writing education. Third, the number of class hours required to teach patent specification writing through general intellectual property courses and the number of teachers to implement the program are insufficient. Conclusions To improve, first, all of the components of a patent specification should be available for writing. Second, it should be possible to protect student-generated invention ideas while broadening the scope of the patent specification. Third, generative AI can be utilized as an assistant teacher to solve the problem of lack of educational content, time, and teacher resources in patent specification writing education. If these improvements are applied and expanded, it is expected that the patent specification writing education through the general intellectual property curriculum in the 2022 curriculum will be more applicable in schools and have a significant educational effect on problem-solving and computational thinking skills.