Advancements in computational thinking research in science education: a bibliometric analysis of reputable international journals (2014-2024)
-
Published: September 12, 2025
-
Page: 225-237
Abstract
This research investigates the development of Computational Thinking (CT) studies in science education by examining selected science journals. It focuses on 1) the distribution of CT research, 2) the proportion of CT-related articles, 3) research methods, 4) authors and citations, 5) education levels, and 6) scientific disciplines and topics. Despite limited systematic literature reviews on CT, its importance in science education is evident as it fosters critical thinking and problem-solving skills. This bibliometric review uses Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to analyze 13 articles from five reputable international journals: Journal of Science Education (IJSE), International Journal of Science and Mathematics Education (IJMA), Journal of Research in Science Teaching (JRST), Science Education (SE), and Research in Science Education (RISE). Findings show that CT research began to develop in 2019. The mixed method is the most widely used in CT research (40%), with JRST publishing the most CT articles (70%). Citations for CT articles are not yet significant, with the highest being 119. Research at the elementary level needs more attention, as many studies focus on secondary schools. CT STEM is the most focused topic in these journals. Other findings are discussed in detail.
- Bibliometric review
- Computational thinking
- Science education

This work is licensed under a Creative Commons Attribution 4.0 International License.
- Aslan, U., Horn, M., & Wilensky, U. (2024). Why are some students “not into” computational thinking activities embedded within high school science units? Key takeaways from a microethnographic discourse analysis study. Science Education, 108(3), 929–956. https://doi.org/10.1002/sce.21850
- Atmatzidou, S., & Demetriadis, S. (2016). Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences. Robotics and Autonomous Systems, 75, 661–670. https://doi.org/10.1016/j.robot.2015.10.008
- Autor, D. H. (2015). Why are there still so many jobs? the history and future of workplace automation. Journal of Economic Perspectives, 29(3), 3–30. https://doi.org/10.1257/jep.29.3.3
- Binkley, M., Erstad, O., Herman, J., Raizen, S., Ripley, M., Miller-Ricci, M., & Rumble, M. (2012). Defining Twenty-First Century Skills. In Assessment and teaching of 21st century skills (Vol. 9789400723, pp. 17–66). Dordrecht, The Netherlands: Springer. https://doi.org/10.1007/978-94-007-2324-5
- Cabrera, L., Ketelhut, D. J., Mills, K., Killen, H., Coenraad, M., Byrne, V. L., & Plane, J. D. (2023). Designing a framework for teachers’ integration of computational thinking into elementary science. Journal of Research in Science Teaching, (October 2022). https://doi.org/10.1002/tea.21888
- Caena, F., & Redecker, C. (2019). Aligning teacher competence frameworks to 21st century challenges: The case for the European Digital Competence Framework for Educators (Digcompedu). European Journal of Education, 54(3), 356–369. https://doi.org/10.1111/ejed.12345
- Caramaschi, M., Cullinane, A., Levrini, O., & Erduran, S. (2022). Mapping the nature of science in the Italian physics curriculum: from missing links to opportunities for reform. International Journal of Science Education, 44(1), 115–135. https://doi.org/10.1080/09500693.2021.2017061
- Cheung, K. K. C., & Erduran, S. (2023). A systematic review of research on family resemblance approach to nature of science in science education. Science & Education, 32(5), 1637–1673.
- Christensen, D., & Lombardi, D. (2023). Biological evolution learning and computational thinking: Enhancing understanding through integration of disciplinary core knowledge and scientific practice. International Journal of Science Education, 45(4), 293–313.
- Denning, P. J. (2009). The profession of IT Beyond computational thinking. Communications of the ACM, 52(6), 28–30.
- Grover, S., & Pea, R. (2018). Computational thinking: A competency whose time has come. Computer science education: Perspectives on teaching and learning in school. London: London: Bloomsbury Academic.
- Gunckel, K. L., Covitt, B. A., Berkowitz, A. R., Caplan, B., &, & Moore, J. C. (2022). Computational thinking for using models of water flow in environmental systems: Intertwining three dimensions in a learning progression. Journal of Research in Science Teaching, 59(7), 1169–1203.
- Hsu, T. C., Chang, S. C., & Hung, Y. T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers and Education, 126(July), 296–310. https://doi.org/10.1016/j.compedu.2018.07.004
- Jiang, H., Islam, A. A., Gu, X., &, & Guan, J. (2024). How do thinking styles and STEM attitudes have effects on computational thinking? A structural equation modeling analysis. Journal of Research in Science Teaching, 61(3), 645–673.
- Kite, V., & Park, S. (2024). Context matters: Secondary science teachers’ integration of process‐based, unplugged computational thinking into science curriculum. Ournal of Research in Science Teaching, 61(1), 203–227.
- Krakowski, A., Greenwald, E., Roman, N., Morales, C., & Loper, S. (2023). Computational Thinking for Science: Positioning coding as a tool for doing science. Journal of Research in Science Teaching, (August). https://doi.org/10.1002/tea.21907
- 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. https://doi.org/10.1002/tea.21751
- Lore, C., Lee, H.-S., Pallant, A., Connor, C., & Chao, J. (2023). Integrating Computational Thinking into Geoscientific Inquiry About Volcanic Eruption Hazards and Risks. International Journal of Science and Mathematics Education. https://doi.org/10.1007/s10763-023-10426-2
- Lye, S. Y., & Koh, J. H. L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12? Computers in Human Behavior, 41, 51–61. https://doi.org/10.1016/j.chb.2014.09.012
- Mason, S. L., & Rich, P. J. (2020). Development and analysis of the Elementary Student Coding Attitudes Survey. Computers and Education, 153(August 2019), 103898. https://doi.org/10.1016/j.compedu.2020.103898
- Miller, J. (2019). STEM education in the primary years to support mathematical thinking: using coding to identify mathematical structures and patterns. ZDM - Mathematics Education, 51(6), 915–927. https://doi.org/10.1007/s11858-019-01096-y
- Mohaghegh, M., & Mccauley, M. (2016). Computational Thinking: The Skill Set of the 21st Century. International Journal of Computer Science and Information Technologies, 7(3), 1524–1530.
- Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & PRISMA Group*, T. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals of Internal Medicine, 151(4), 264–269.
- Niemi, H., & Multisilta, J. (2016). Digital storytelling promoting twenty-first century skills and student engagement. Technology, Pedagogy and Education, 25(4), 451–468. https://doi.org/10.1080/1475939X.2015.1074610
- Peel, A., Sadler, T. D., & Friedrichsen, P. (2019). Learning natural selection through computational thinking: Unplugged design of algorithmic explanations. Journal of Research in Science Teaching, 56(7), 983–1007.
- Peters‐Burton, E., Rich, P. J., Kitsantas, A., Stehle, S. M., &, & Laclede, L. (2023). High school biology teachers’ integration of computational thinking into data practices to support student investigations. Journal of Research in Science Teaching, 60(5), 1353–1384.
- Rachmatullah, A., & Wiebe, E. N. (2022). Building a computational model of food webs: Impacts on middle school students’ computational and systems thinking skills. Journal of Research in Science Teaching, 59(4), 585–618.
- Saykili, A. (2019). Higher Education in The Digital Age: The Impact of Digital Connective Technologies. Journal of Educational Technology and Online Learning, 2(1), 1–15. https://doi.org/10.31681/jetol.516971
- Schanzer, E., Fisler, K., & Krishnamurthi, S. (2018). Assessing Bootstrap. 15, 8–13. https://doi.org/10.1145/3159450.3159498
- Scherer, R., Siddiq, F., & Sánchez Viveros, B. (2018). The cognitive benefits of learning computer programming: A meta-analysis of transfer effects. Journal of Educational Psychology, 115(5), 764–792. https://doi.org/https://doi.org/10.1037/edu0000314
- Sengupta, P., Dickes, A., & Farris, A. (2018). Toward a phenomenology of computational thinking in STEM education. Computational Thinking in the STEM Disciplines: Foundations and Research Highlights, 49–72. https://doi.org/10.1007/978-3-319-93566-9_4
- Soderberg, C. K., Errington, T. M., Schiavone, S. R., Bottesini, J., Thorn, F. S., Vazire, S., … Nosek, B. A. (2021). nitial evidence of research quality of registered reports compared with the standard publishing model. Nature Human Behaviour, 5(8), 990–997.
- Sullivan, A., R. Kazakoff, E., & Umashi Bers, M. (2013). The Wheels on the Bot go Round and Round: Robotics Curriculum in Pre-Kindergarten. Journal of Information Technology Education: Innovations in Practice, 12, 203–219. https://doi.org/10.28945/1887
- Tran, Y. (2019). Computational Thinking Equity in Elementary Classrooms: What Third-Grade Students Know and Can Do. Journal of Educational Computing Research, 57(1), 3–31. https://doi.org/10.1177/0735633117743918
- Tuomi, P., Multisilta, J., Saarikoski, P., & Suominen, J. (2018). Coding skills as a success factor for a society. Education and Information Technologies, 23(1), 419–434. https://doi.org/10.1007/s10639-017-9611-4
- Voogt, J., & Roblin, N. P. (2012). A comparative analysis of international frameworks for 21 st century competences: Implications for national curriculum policies. Journal of Curriculum Studies, 44(3), 299–321. https://doi.org/10.1080/00220272.2012.668938
- Wang, C., Shen, J., & Chao, J. (2022a). Integrating computational thinking in STEM education: A literature review. International Journal of Science and Mathematics Education, 20(8), 1949–1972.
- Wang, C., Shen, J., & Chao, J. (2022b). Integrating computational thinking in STEM education: A literature review. International Journal of Science and Mathematics Education, 20(8), 1949–1972.
- Wing, J. (2008). Computational thinking and thinking about computing. IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM, 1. IEEE. https://doi.org/10.1109/IPDPS.2008.4536091
- Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1201/b16812-3