Research Trends Of Computational Thinking For Advancing Sustainable Development Goals (SDGs) In Science Learning: Bibliometric Analysis
DOI:
https://doi.org/10.15294/jpii.v14i2.23645Keywords:
Bibliometric, Computational Thinking, Science Learning, Scopus Database , SDGsAbstract
Computational Thinking (CT) emerged as a crucial competency that bridges digital literacy and scientific problem solving in the context of achieving Sustainable Development Goal (SDG) 4 on quality education. However, the model of integrating CT in science learning is still poorly explored, hindering progress towards SDG Targets 4.4 (technical skills) and 4.7 (scientific literacy). This study is the first bibliometric analysis to map the trends of CT research in science learning (2021–2023) through Scopus. The novelty lies in the identification of global collaboration patterns, knowledge gaps, and research priorities that are aligned with the 2030 Agenda. Three research questions were guided: (1) Publication distribution, (2) Dominant journals and subject areas, (3) Keyword dynamics/co-occurrence networks. Data retrieved from Scopus using the strings TITLE-ABS-KEY("Computational Thinking" AND "Science Education/Learning") (47 articles, open access, 2021–2023). Analysis techniques include: Performance analysis (publication/citation metrics), Science mapping (author affiliation), Network analysis (keyword grouping via VOSviewer). Key findings show: (1) Peak publication in 2022 (19 articles), (2) Education Sciences (Q1) as the top journal (7 articles), (3) Dominance of Social Sciences (43 articles) and Computer Science (21), (4) Most cited articles: Lodi & Martini (2021; 43 citations), (5) Main keywords: Computational Thinking (27 appearances), Computer Science Education (15), (6) US-led geographic contributions (>20 publications), (7) Co-occurrence analysis reveals that Scratch (a block-based application) is a less researched CT tool (3 occurrences) than technical languages such as Python. CT integration improves science literacy but is constrained by teacher training gaps (SDG 4.c) and access to resources. The scarcity of research on gamified tools like Scratch signals a critical innovation gap. This study provides an evidence-based roadmap to prioritize teacher professional development, scale accessible CT tools (e.g., Scratch) for science education, and direct future research toward SDG-aligned classroom-based practices.
References
Abdullah, A., & Mahmud, S. N. D. (2024). Applying TPACK in STEM Education Towards 21-St Century: Systematic Literature Review. International Journal of Academic Research in Progressive Education and Development, 13(1).
Apriana, D., Suarni, N. K., Margunayasa, I. G., & Hudri, M. (2024). Meta Analisis Implementasi Computational Thinking untuk Meningkatkan Hasil Belajar Ipas di Sekolah Dasar. Journal of Elementary School (JOES), 7(1), 35–42.
Arman, A., Bellini, P., Bologna, D., Nesi, P., Pantaleo, G., & Paolucci, M. (2021). Automating IoT Data Ingestion Enabling Visual Representation. Sensors, 21(24), 8429.
Baas, J., Schotten, M., Plume, A., Côté, G., & Karimi, R. (2020). Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies. Quantitative Science Studies, 1(1), 377–386.
Basu, S., Biswas, G., Sengupta, P., Dickes, A., Kinnebrew, J. S., & Clark, D. B. (2016). Identifying Middle School Students’ Challenges in Computational Thinking-Based Science Learning. Research and Practice in Technology Enhanced Learning, 11(1).
Bukar, U. A., Sayeed, M. S., Razak, S. F. A., Yogarayan, S., Amodu, O. A., & Mahmood, R. A. R. (2023). A method for analyzing text using VOSviewer. MethodsX, 11, 102339.
Bulathwela, S., Pérez‐Ortiz, M., Holloway, C., Cukurova, M., & Shawe‐Taylor, J. (2024). Artificial Intelligence Alone Will Not Democratise Education: On Educational Inequality, Techno-Solutionism and Inclusive Tools. Sustainability, 16(2), 781.
Chen, P., Yang, D., Metwally, A. H. S., Lavonen, J., & Wang, X. (2023). Fostering computational thinking through unplugged activities: A systematic literature review and meta-analysis. International Journal of STEM Education, 10(1), 47.
Cheng, L., Wang, X., & Ritzhaupt, A. D. (2022). The Effects of Computational Thinking Integration in STEM on Students’ Learning Performance in K-12 Education: A Meta-Analysis. Journal of Educational Computing Research, 61(2), 416–443.
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296.
Donthu, N., Kumar, S., Pattnaik, D., & Lim, W. M. (2021). A bibliometric retrospection of marketing from the lens of psychology: Insights from Psychology & Marketing. Psychology & Marketing, 38(5), 834–865.
Dorotea, N., Piedade, J., & Pedro, A. (2021). Mapping k-12 computer science teacher’s interest, self-confidence, and knowledge about the use of educational robotics to teach. Education Sciences, 11(8).
Dwiyanti, U. (2023). The Potential of Developing Computational Thinking Approach-Based Physics Learning Media as a Means of Increasing Students’ Problem-Solving Ability. Amplitudo Journal of Science & Technology Innovation, 2(2), 95–100.
Espinal, A., Vieira, C., & Magana, A. J. (2024). Professional Development in Computational Thinking: A Systematic Literature Review. ACM Transactions on Computing Education, 24(2), 1–24.
Farris, A. V., & McLaughlin, G. (2024). Getting a grip on how we talk about computational practices in science in settings of teacher learning. Journal of Computer Assisted Learning, 40(4), 1922–1940.
Fauzi, A. L., Kusumah, Y. S., Nurlaelah, E., & Juandi, D. (2024). Computational Thinking in Mathematics Education : A Systematic Literature Review on its Implementation and Impact on Students’ Learning. Jurnal Kependidikan: Jurnal Hasil Penelitian Dan Kajian Kepustakaan Di Bidang Pendidikan, Pengajaran Dan Pembelajaran, 10(2), 640.
Ferguson, T., & Roofe, C. (2020). SDG 4 in Higher Education: Challenges and Opportunities. International Journal of Sustainability in Higher Education, 21(5), 959–975.
Fields, D., Lui, D., Kafai, Y., Jayathirtha, G., Walker, J., & Shaw, M. (2021). Communicating about computational thinking: understanding affordances of portfolios for assessing high school students’ computational thinking and participation practices. Computer Science Education, 31(2), 224–258.
Hallinger, P., & Kovačević, J. (2019). A Bibliometric Review of Research on Educational Administration: Science Mapping the Literature, 1960 to 2018. Review of Educational Research, 89(3), 335–369.
Hincapie, M., Diaz, C., Valencia, A., Contero, M., & Güemes-Castorena, D. (2021). Educational applications of augmented reality: A bibliometric study. Computers and Electrical Engineering, 93(June), 107289.
Hueske, A., Pontoppidan, C. A., & Iosif-Lazăr, L.-C. (2021). Sustainable Development in Higher Education in Nordic Countries: Exploring E-Learning Mechanisms and SDG Coverage in MOOCs. International Journal of Sustainability in Higher Education, 23(1), 196–211.
Hurt, T., Greenwald, E., Allan, S., Cannady, M. A., Krakowski, A., Brodsky, L., Collins, M. A., Montgomery, R., & Dorph, R. (2023). The computational thinking for science (CT-S) framework: operationalizing CT-S for K–12 science education researchers and educators. International Journal of STEM Education, 10(1), 1.
Kite, V., & Park, S. (2022). What’s Computational Thinking?: Secondary Science Teachers’ Conceptualizations of Computational Thinking (CT) and Perceived Barriers to CT Integration. Journal of Science Teacher Education, 34(4), 391–414.
Kite, V., & Park, S. (2023). Context Matters: Secondary Science Teachers’ Integration of Process‐based, Unplugged Computational Thinking Into Science Curriculum. Journal of Research in Science Teaching, 61(1), 203–227.
Kite, V., Park, S., & Wiebe, E. (2021). The Code-Centric Nature of Computational Thinking Education: A Review of Trends and Issues in Computational Thinking Education Research. Sage Open, 11(2).
Lee, H.-Y., Wu, T.-T., Lin, C.-J., Wang, W.-S., & Huang, Y.-M. (2024). Integrating Computational Thinking Into Scaffolding Learning: An Innovative Approach to Enhance Science, Technology, Engineering, and Mathematics Hands-On Learning. Journal of Educational Computing Research, 62(2), 431–467.
Li, K. C., & Wong, B. T. M. (2021). Research Landscape of Smart Education: A Bibliometric Analysis. Interactive Technology and Smart Education, 19(1), 3–19.
Lilly, S., McAlister, A. M., Fick, S. J., Chiu, J. L., & McElhaney, K. W. (2022). Elementary teachers’ verbal supports of science and engineering practices in an NGSS-aligned science, engineering, and computational thinking unit. Journal of Research in Science Teaching, 59(6), 1035–1064.
Lim, W. M., Kumar, S., & Donthu, N. (2024). How to combine and clean bibliometric data and use bibliometric tools synergistically: Guidelines using metaverse research. Journal of Business Research, 182, 114760.
Lodi, M., & Martini, S. (2021). Computational Thinking, Between Papert and Wing. Science and Education, 30(4), 883–908.
Love, T. S., Cysyk, J. P., Attaluri, A., Tunks, R. D., Harter, K., & Sipos, R. (2023). Examining Science and Technology/Engineering Educators’ Views of Teaching Biomedical Concepts Through Physical Computing. Journal of Science Education and Technology, 32(1), 96–110.
Martins, J., Gonçalves, R., & Branco, F. (2024). A bibliometric analysis and visualization of e-learning adoption using VOSviewer. Universal Access in the Information Society, 23(3), 1177–1191.
Mellor, N. (2023). The Digital Divide in the Journalism Sector. Convergence the International Journal of Research Into New Media Technologies, 30(3), 1120–1133.
Mendrofa, N. K. (2024). Computational Thinking Skills in 21st Century Mathematics Learning. JIIP - Jurnal Ilmiah Ilmu Pendidikan, 7(1), 792–801.
Merigó, J. M., & Yang, J. (2017). A Bibliometric Analysis of Operations Research and Management Science. Omega, 73, 37–48.
Ntourou, V., Kalogiannakis, M., & Psycharis, S. (2021). A Study of the Impact of Arduino and Visual Programming In Self-Efficacy, Motivation, Computational Thinking and 5th Grade Students’ Perceptions on Electricity. Eurasia Journal of Mathematics, Science and Technology Education, 17(5), 1–11.
Nurita, T., Yuliati, L., Mahdiannur, M. A., & Ilhami, F. B. (2024). The Effectiveness of Case-Based STEM Integrated With Mobile Simulation to Foster Students’ Creative Thinking Skills. International Journal of Interactive Mobile Technologies (Ijim), 18(07), 97–106.
Nuzzaci, A. (2024). Incorporating Computational Thinking into Education: From Teacher Training to Student Mastery. Journal of Education and Training, 11(2), 70.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, n71.
Palts, T., & Pedaste, M. (2020). A Model for Developing Computational Thinking Skills. Informatics in Education, 19(1), 113–128.
Park, Y.-S., & Green, J. (2019). Bringing Computational Thinking Into Science Education. Journal of the Korean Earth Science Society, 40(4), 340–352.
Peel, A., Sadler, T. D., & Friedrichsen, P. (2022). Algorithmic Explanations: an Unplugged Instructional Approach to Integrate Science and Computational Thinking. Journal of Science Education and Technology, 31(4), 428–441.
Potkonjak, V., Gardner, M., Callaghan, V., Mattila, P., Guetl, C., Petrović, V. M., & Jovanović, K. (2018). Virtual laboratories for education in science, technology, and engineering: A review. Computers and Education, 95, 309–327.
Pratama, K. A., & Widjajanti, D. B. (2024). STEM: Its Potential in Developing Students’ Computational Thinking. KnE Social Sciences.
Puganesri, K., & Puteh, S. (2019). Computer Science Education in Malaysia Schools: The Challenges of Enhancing Computational Thinking Skills. International Journal of Engineering and Advanced Technology, 8(6s3), 441–444.
Punjani, K. K., Kumar, V., & Kadam, S. (2019). Trends of Puffery in Advertising – A Bibliometric Analysis. Benchmarking an International Journal, 26(8), 2468–2485.
Sánchez, M. R., Palos‐Sánchez, P. R., & Folgado-Fernández, J. A. (2022). Systematic Literature Review and Bibliometric Analysis on Virtual Reality and Education. Education and Information Technologies, 28(1), 155–192.
Shukshina, L. V, Gegel, L. A., Erofeeva, M. A., Levina, I. D., Chugaeva, U. Y., & Nikitin, O. D. (2021). STEM and STEAM Education in Russian Education: Conceptual Framework. Eurasia Journal of Mathematics, Science and Technology Education, 17(10), 1–14.
Sierra, J., & Suárez-Collado, Á. (2021). The Transforming Generation: Increasing Student Awareness About the Effects of Economic Decisions on Sustainability. International Journal of Sustainability in Higher Education, 22(5), 1087–1107.
Sun, D., Ouyang, F., Li, Y., & Zhu, C. (2021). Comparing learners’ knowledge, behaviors, and attitudes between two instructional modes of computer programming in secondary education. International Journal of STEM Education, 8(1).
Triantafyllou, S. A., Sapounidis, T., & Farhaoui, Y. (2024). Gamification and Computational Thinking in Education: A systematic literature review. Salud, Ciencia y Tecnología - Serie de Conferencias, 3, 659.
van Eck, N. J., & Waltman, L. (2017). Citation-based clustering of publications using CitNetExplorer and VOSviewer. Scientometrics, 111(2), 1053–1070.
Verma, S., & Gustafsson, A. (2020). Investigating the emerging COVID-19 research trends in the field of business and management: A bibliometric analysis approach. Journal of Business Research, 118, 253–261.
Wahyunengseh, R. D., Hastjarjo, S., Mulyaningsih, T., & Suharto, D. G. (2020). Digital Governance and Digital Divide: A Matrix of the Poor’s Vulnerabilities. Policy & Governance Review, 4(2), 152.
Waterman, K. P., Goldsmith, L. T., & Pasquale, M. (2019). Integrating Computational Thinking Into Elementary Science Curriculum: An Examination of Activities That Support Students’ Computational Thinking in the Service of Disciplinary Learning. Journal of Science Education and Technology, 29(1), 53–64.
Weintrop, D., Wise Rutstein, D., Bienkowski, M., & McGee, S. (2021). Assessing computational thinking: an overview of the field. Computer Science Education, 31(2), 113–116.
Yadav, A., Heath, M., & Hu, A. D. (2022). Toward justice in computer science through community, criticality, and citizenship. Communications of the ACM, 65(5), 42–44.
Yin, S. X., Hoe-Lian Goh, D., & Quek, C. L. (2024). Collaborative Learning in K-12 Computational Thinking Education: A Systematic Review. Journal of Educational Computing Research, 62(6), 1440–1474.
Zhang, Y., & Savard, A. (2023). Defining Computational Thinking as an Evident Tool in Problem-Solving: Comparative Research on Chinese and Canadian Mathematics Textbooks. ECNU Review of Education, 6(4), 677–699.
Zviel Girshin, R., Rosenberg, N., & Kukliansky, I. (2024). Early Childhood Robotics: Children’s Beliefs and Objective Capabilities to Read and Write Programs. Journal of Research in Childhood Education, 38(2), 317–335.
