Computational Thinking Research Articles

Exploring parents' perceptions of computational thinking and its role in children's television

AbstractThe rise in children's media use and the prioritization of STEM learning has led to the development of new STEM‐related apps, TV shows, and other media for young children, with several recent examples focused on computational thinking (CT). Learning CT at a young age can be beneficial to children's analytical and problem solving skills. Positive effects of educational media are best realized when the learning is scaffolded by a caregiver, but the ability of parents to scaffold CT lessons is understudied. This study explores parents' perceptions, understanding, and recognition of the CT cues embedded in a new television show for preschoolers. Qualitative semi‐structured interviews were conducted with 30 parents who, together with their children (ages 4–6), viewed two episodes of a new series. Interviews were transcribed and coded using thematic analysis. Most participants had never heard of CT before. When asked to define it, many parents highlighted aspects of CT in their definitions; however, their examples illustrated limited understanding of how CT might be taught to young children. Although some parents had reservations regarding the abstractness and age‐appropriateness of the topic, parents believed CT was an important topic for their children to learn. Research has shown that scaffolding can be beneficial to promoting CT learning in young children. Therefore, for creators of CT‐focused content, it is important that the curricular focus and learning goals are made very clear so that parents and caregivers can scaffold the material in a way that effectively supports their children's learning.

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.

Curriculum Framework and Assessment Approach for Computational Thinking in the Early Years

In light of current developments, there is an increasing effort to integrate computing-oriented activities into the education of children as young as two years old. Although the computing strand is not officially addressed in the Early Years Foundation Stage Statutory Framework (DfES, 2024), a small number of early years teachers in England implement computing-oriented activities to ensure that young children progress from early years to Key Stage 1. A particular gap in the field is that previous research on computational thinking concepts never or rarely establish curriculum links in a way that teachers can utilise in their practices. This theoretical article therefore proposes a curriculum-based framework for both teaching and assessing computational thinking (CT) in early years education as assessment is not possible without pedagogic guidelines. Offering a sample lesson plan with links to the Early Learning Goals, this framework aims to encourage teachers, including those without specific computing training, to integrate CT concepts more explicitly into their teaching and enables them to monitor and assess their pupils' progress in relevant skills.

Using Card Sorting Activity as a Strategy for Evaluating Students’ Learning of Computational Thinking Concepts

This study investigated the effectiveness of the ‘Match it’ card sorting activity for evaluating the prospective teachers’ knowledge and understanding of computational thinking (CT) concepts. 146 primary prospective teachers were asked to sort 26 scenarios and words alongside nine images under five main computational concepts: algorithmic thinking, abstraction, decomposition, patterns & generalisation, and evaluation. The study found that the card sorting activity, as a method for assessment was useful, however, the issues around the design and the content of the current card sorting activity were reported by students which suggests that further revisions should be made to improve the effectiveness of the tool.

Assessing Computational Literacy in First Language (L1) Teaching

This article addresses the multifaceted challenges of assessing computational literacy (CL) within the context of first language (L1) teaching. The article commences by examining the theoretical foundations and the need for an expanded understanding of CL, moving beyond the popular notion of computational thinking (CT). We then present an example from a 5th-grade classroom in a Danish middle school to illustrate how pupils integrate computational skills into their writing practices through a design-based intervention. Subsequent to this example, we propose a cross-disciplinary framework designed to assess CL in L1 settings, focusing on four principles that bridge traditional language arts with computational approaches. Finally, we reflect on how the application of these principles can help formulate new learning goals that better align with the emerging demands of 21st-century education. Throughout the article, we argue that a CL approach provides a more socially rooted and context-sensitive method for integrating computational methods into non-computer science subjects, offering theoretical clarity and practical benefits for both educators and researchers alike. The article commences with a discussion of the CL approach related to assessment.

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.

Trends of abstraction research in mathematics education: A bibliometric analysis

Abstraction is fundamental in mathematics learning because students can discover the studied concepts through abstraction. Bibliometric analyses of abstraction research in mathematics education have yet to be published. A bibliometric analysis is conducted to explore trends in abstraction research. The mathematics education researchers will gain insights from studying the development of abstraction research over the last fifteen years. The primary objective of this study is to evaluate the primary journals published, the most productive authors, universities, and countries and to identify current trends in abstraction research. Data were collected from the Scopus database and analysed using VOSviewer and R software. A thorough review was conducted on 271 articles published between 2008 and 2022. The collected data was analysed and presented using R studio and VOSviewer software. The publication of abstraction research has increased every year. Abstraction studies related to geometry, computational thinking, and preschool are trend and abstraction studies related to gesture, preschool child, arithmetic, physiology, mathematical concepts, geometry, language, and cognition. Abstraction research is exciting because it will still trend until 2022. This study offers valuable insights to researchers interested in mathematics education for exploring alternative research directions to the primary research trends. Based on these results, recommendations for further research are given so that they can explore various options for research trends.

Secondary science teachers' conceptualizations and modifications to support equitable participation in a co‐designed computational thinking lesson

AbstractIncreasing access to computational ideas and practices is one important reason to integrate computational thinking (CT) in science classrooms. While integrating CT into science classrooms broadens exposure to computing, it may not be enough to ensure equitable participation in the science classroom. Equitable participation is crucial because providing students with an environment in which they are able to fully engage and participate in science and computing practices empowers students to learn and continue pursuing CT and science. To foreground equitable participation in CT‐integrated curricula, we undertook a research project in which researchers and teachers examined teacher conceptualizations of equitable participation and how teachers design for equitable participation by modifying a lesson that introduces computational modeling in science. The following research questions guided the study: (1) What are teachers' conceptualizations of equitable participation? (2) How do teachers design for equitable participation through co‐design of a CT‐integrated unit? Our findings suggest that teachers conceptualized and designed for equitable participation in the context of a CT‐integrated curriculum across three primary dimensions: accessibility, inclusion, and relevancy. Our contributions to the field of science teaching and learning are twofold: (1) obtaining an initial understanding of how teachers think about and design for equitable participation is crucial in order to support teachers in their pursuit of creating equitable learning experiences for CT and science learners, and (2) our findings show that we can study teacher conceptualizations and their design choices by examining specific modifications to a CT‐integrated science curriculum. Implications are discussed.

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.

Research on school-based AI curriculum design and practice for cultivating computational thinking in high school students

Research on school-based AI curriculum design and practice for cultivating computational thinking in high school students

Computational thinking in mathematics instruction integrated STEAM education: Global trend and students’ achievement in two last decades

[English]: Computational thinking (CT) becomes an essential ability in the 21st century whereby mathematics instruction integrated STEAM education is expected to be an effective intervention for optimizing CT. CT studies in this instructional approach have been increasingly grown in two last decades. Present study describes and synthesizes global trend and students’ CT achievement in mathematics instruction integrated STEAM education. A systematic review using bibliometric analysis and qualitative meta-synthesis was applied to do this study. 509 included studies indexed by Scopus and published between 2004 and 2023 were used as the data to bibliometric analysis, of those, particularly 14 empirically qualitative studies to be included in qualitative meta-synthesis. Results revealed that the publication development of CT studies slightly soared, whereas the citation development on CT studies relatively fluctuated in the period of 2004 - 2023. There were several emerging themes in CT studies, such as CT component, cognitive, affective, & psychomotor domain, mathematical content, CT learning environment, technological intervention in CT, research methodology, popular country involved in CT, participant, educational level, and STEAM component. Generally, students had achieved five CT components, such as pattern recognition, abstraction, decomposition, generalization, and algorithm. The conclusion and implications of this study for mathematics education are comprehensively discussed. [Bahasa]: Berpikir komputasi menjadi kemampuan yang esensial di abad 21 yang mana pembelajaran matematika yang terintegrasi pendekatan science, technology, engineering, art, and mathematics (STEAM) diharapkan menjadi intervensi yang efektif dalam mengoptimalkan kemampuan berpikir komputasi. Studi ini mendeskripsikan dan mensintesis tren global dan pencapaian berpikir komputasi siswa dalam pembelajaran matematika yang menggunakan pendekatan STEAM. Sebuah riviu sistematik yang menggunakan analisis bibliometrik dan meta-sintesis kualitatif diterapkan dalam studi ini. Lima ratus sembilan studi inklusi yang terindeks Scopus dan dipublikasikan antara tahun 2004 dan 2023 digunakan sebagai data dalam analisis bibliometrik. Secara khusus, 14 studi empiris kualitatif diinklusikan dalam meta-sintesis kualitatif. Hasil penelitian ini mengungkapkan bahwa perkembangan publikasi dari studi-studi berpikir komputasi cukup meningkat, sedangkan perkembangan sitasi terhadap studi-studi berpikir komputasi relatif berfluktuasi pada periode 2004 – 2023. Terdapat beberapa tema yang muncul terkait studi-studi berpikir komputasi, seperti: komponen berpikir komputasi, domain kognitif, afektif, dan psikomotor, konten matematika, lingkungan belajar berpikir komputasi, intervensi teknologi dalam berpikir komputasi, metodologi penelitian, negara popular yang terlibat dalam kajian berpikir komputasi, partisipan, jenjang pendidikan, dan komponen STEAM. Secara umum, siswa sudah mencapai lima komponen berpikir komputasi, seperti: pengenalan pola, abstraksi, dekomposisi, generalisasi, dan algoritma yang disebabkan oleh pengintegrasian pendekatan STEAM. Kesimpulan dan dampak dari penelitian ini terhadap pendidikan matematika dibahas secara komprehensif.

A scoping review of the literature on computational thinking in education in the Arab world

This study aims to identify the nature and the extent of recent research studies on computational thinking in the Arab educational systems. The analyzed studies were gathered from English and Arabic educational sources. The selected publications were peer-reviewed journal articles over the past ten years that dealt with computational thinking in education in the Arab world. The selected studies were analyzed based on language, publication date, educational setting, educational discipline, site, primary purpose, research method, sample, and adopted definition of computational thinking. Twenty-eight research articles were selected for the investigation. The analysis revealed that the majority of the examined research studies were published in the Arabic language after the year 2020 in K-12 educational settings. The majority of the examined studies were conducted in programming and computer science in a few Arab countries. In addition, the majority of the examined studies focused on how to develop students’ computational thinking levels using various interventions. The majority of the studies employed a limited number of participants and used different forms of experimental research designs. The studies adopted different forms of the definition of computational thinking. Based on the findings, recommendations for future studies were presented.

Bibliometric Analysis of Artificial Intelligence Studies in Computational Thinking

Computational thinking is an approach used to solve complex problems with basic skills such as decomposition, pattern recognition, abstraction and algorithm design. Especially artificial intelligence and its sub-fields make significant contributions to the development of these skills. This study aims to evaluate the research in the field of artificial intelligence in the computational thinking process through bibliometric analysis. The data of the study were obtained from the Web of Science (WoS) database on May 1, 2024. The VOSviewer software program, which is frequently used in bibliometric analysis and can be used free of charge, was used to analyze the data obtained from the WoS database. Analyses using the data obtained from the WoS database enabled the analysis of research in this field in terms of countries, authors, co-authorship status, publication journals, publication years and keywords. The findings of the study show that Taiwan is the country with the highest number of studies in this field, while Spain is the country with the highest number of citations. Hooshyar, D and Hsu, T are among the authors who contributed to the most publications. Collaboration plays an important role in research and Lai, C stands out as the author with the most co-authorship. Education and Information Technologies and Kunstliche Intelligenz are among the journals where the most studies are published. As a result of the examination of the 5 most cited studies, it was determined that different research methods and participant groups were used, data collection tools varied and different data analysis methods were used. These studies provide a broad perspective on artificial intelligence studies in the field of computational thinking and make important contributions to the literature in this field.

Implementation of Augmented Reality Media in Physics Learning to Develop Students' Cognitive Abilities: A Systematic Literature Review

Augmented reality as a learning media has the ability to explain physics concepts contextually and concretely to students in three dimensions, so this study aims to identify the trend that influence the use of augmented reality Media in physics learning on the cognitive abilities of students. This research is composed of the results of a synthesis of the findings of previous research articles that are relevant in the 2017-2022 period. This study adapted systematic literature review method with Publish or Perish software, then filtered and extracted data according to the criteria for the research objectives to produce 47 relevant articles and compiled using PRISMA Protocol. From the results of several research syntheses, it was found that the use of augmented reality in physics learning can improve students' cognitive abilities which include self-efficacy, conceptual understanding, critical thinking, high order thinking, visual representation, abstract thinking, scientific literacy, creative thinking, computational thinking, reasoning and problem solving. In addition, the use of augmented reality media provides optimal learning outcomes for students and has a positive influence on affective abilities. Future research is expected to be able to present in depth the influence of augmented reality media in physics learning to develop students' affective abilities and attitudes.

Correction to: The infuence of scafolding for computational thinking on cognitive load and problemsolving skills in collaborative programming

Correction to: The infuence of scafolding for computational thinking on cognitive load and problemsolving skills in collaborative programming

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.

Evolving Computer Science Education Research in Teaching and Learning: A Bibliometric Analysis

This study performed a bibliometric analysis of computer science education (CSE) publications in teaching and learning. The research trend in computer science education was analysed using publications from the Scopus-indexed database between 1970 and 2021. This study aims to summarize this information to assist three groups of stakeholders: educators, researchers and policymakers. Our review goal to document and analyse the trends in CSE research publications for teaching and learning. A total of 800 publications were derived for further assessment based on computer science education in the article title with multiple tools. We used, Microsoft Excel, VOSviewer and Harzing’s Publish or Perish were utilized for frequency analysis data visualization and citation metrics and assessment. The study outcomes were documented with standard bibliometric indicators: publication growth, authorship trends, collaboration, prolific authors, national contribution, most active establishments, top-cited articles, preferred journals, intellectual structure and topical trends. Resultantly, CSE research publications have perpetually grown for the past 51 years since 1970 with the United States highlighting the largest study contributor, followed by Germany and the United Kingdom. The ACM SIGCSE Bulletin published the highest number of CSE research publications. The analysis of the cluster on topical trends indicates that curriculum design and implementation (e.g., assessment, broadening participation), elements of teaching and learning (e.g., constructivism, e-learning, game-based learning) and other areas of interest comprise pedagogical approach (e.g., computational thinking, k-12 education, motivation). Based on the research results, we expand on the findings and propose how authors might enhance the CSE function in curriculum design, implementation and shifts could eventually substitute past study clusters.

From conception to fruition: Co-designing a digital exhibit incorporating embodied cognition to encourage young children’s computational thinking in a Science Discovery Centre

From conception to fruition: Co-designing a digital exhibit incorporating embodied cognition to encourage young children’s computational thinking in a Science Discovery Centre

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.