Mapping the Research Trends of Computational Thinking in Mathematics Education: A Bibliometric Analysis

https://doi.org/10.51574/jrip.v6i2.5633

Authors

Keywords:

Bibliometric Analysis, Computational Thinking (CT), Mathematics Education (ME), VOSviewer

Abstract

Computational thinking (CT) has become an important competency in mathematics education (ME), supporting students’ problem-solving, reasoning, and algorithmic thinking. However, the development of research on CT in ME, including publication trends, influential studies, collaboration patterns, and research themes, has not been comprehensively mapped. This study aims to map the research landscape of CT in ME through a descriptive bibliometric analysis. Publication data were retrieved from Google Scholar, Crossref, and Scopus using the keywords computational thinking, education, and mathematics. After relevance screening, 140 publications from 2016 to 2026 were selected for analysis. Publication trends, citation performance, collaboration networks, and keyword co-occurrence were analyzed using VOSviewer. The findings show a substantial increase in publications since 2020, with the highest output recorded in 2023 and 2024. Citation analysis identifies highly cited studies that have contributed to the conceptual development of CT in ME, while the Journal of Pedagogical Research emerged as the most productive journal. The collaboration network indicates emerging but still limited international collaboration, particularly involving researchers from Sweden, Denmark, and the United Kingdom. Keyword co-occurrence analysis reveals three interconnected research areas: CT implementation in mathematics learning, core CT processes such as decomposition, pattern recognition, abstraction, and generalization, and CT assessment and measurement. The findings show that CT research remains focused on measurement and assessment, while pedagogical approaches, creativity, teacher education, and elementary mathematics education are less explored, highlighting the need for systematic, contextual approaches that connect CT processes with meaningful mathematics learning.

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References

Abdullah, K. H. (2021). Mapping of marine safety publications using VOSviewer. ASM Science Journal, 16, 1–9. https://doi.org/10.32802/asmscj.2021.774

Angraini, L. M., Yolanda, F., & Muhammad, I. (2023). Augmented Reality: The Improvement of Computational Thinking Based on Students’ Initial Mathematical Ability. International Journal of Instruction, 16(3), 1033–1054. https://doi.org/10.29333/iji.2023.16355a

Barcelos, T. S., Muñoz-Soto, R., Villarroel, R., Merino, E., & Silveira, I. F. (2018). Mathematics Learning through Computational Thinking Activities: A Systematic Literature Review. . . Univers. Comput. Sci., 24(7), 815-845. https://doi.org/10.3217/jucs-024-07-0815

Budianto, E. W. H., & Dewi, N. D. T. (2023). Research mapping of Working Capital Turnover (WCT) ratio in Islamic and Conventional Banking: Vosviewer bibliometric study and literature review. Global Financial Accounting Journal, 7(2), 181. https://doi.org/10.37253/gfa.v7i2.7709

Chen, X., Wang, S., Tang, Y., & Hao, T. (2019). A bibliometric analysis of event detection in social media. Online Inf. Rev., 43(1), 29–52. https://doi.org/10.1108/oir-03-2018-0068

Chytas, C., Borkulo, S. P. Van, Drijvers, P., Barendsen, E., & Tolboom, J. L. J. (2024). Computational thinking in secondary mathematics education with GeoGebra: Insights from an intervention in calculus lessons. Digital Experiences in Mathematics Education, 10(2), 228–259. https://doi.org/10.1007/s40751-024-00141-0

Dettori, J. R., Norvell, D. C., & Chapman, J. R. (2022). Fixed-effect vs random-effects models for meta-analysis: 3 points to consider. Global Spine Journal, 12(7), 1624–1626. https://doi.org/10.1177/21925682221110527

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), 640–653. https://doi.org/10.33394/jk.v10i2.11140

Ferrer-Serrano, M., Fuentelsaz, L., & Latorre-Martínez, M. P. (2025). Knowledge Transfer and Networks: A Bibliometric Approach Through Performance Analysis, Science mapping, and Dynamic Network Analysis. Journal of the Knowledge Economy, 1–36. https://doi.org/10.1007/s13132-025-02814-6

Fitriyah, Y., Dahlan, J. A., & Wahyudin, W. (2024). Review and Trend Analysis of Computational Thinking Research in Mathematics Education (2013-2023). Jurnal Math Educator Nusantara: Wahana Publikasi Karya Tulis Ilmiah Di Bidang Pendidikan Matematika, 10(2), 381–394. https://doi.org/10.29407/jmen.v10i2.22039

Funa, A. A., & Prudente, M. S. (2021). Effectiveness of Problem-Based Learning on Secondary Students’ Achievement in Science: A Meta-Analysis. International Journal of Instruction, 14(4), 69–84. https://doi.org/10.29333/iji.2021.1445a

Gadanidis, G. (2017). Artificial intelligence, computational thinking, and mathematics education. The International Journal of Information and Learning Technology, 34(2), 133–139. https://doi.org/10.1108/ijilt-09-2016-0048

Gadanidis, G., Cendros, R., Floyd, L., & Namukasa, I. (2017). Computational thinking in mathematics teacher education. Contemporary Issues in Technology and Teacher Education, 17(4), 458–477.

Grover, S., Fisler, K., Lee, I., & Yadav, A. (2020). Integrating computing and computational thinking into K-12 STEM learning. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education (pp. 481–482). ACM. https://doi.org/10.1145/3328778.3366970

Guss, S. S., Clements, D. H., Sharifnia, E., Sarama, J., Holland, A., Lim, C.-I., & Vinh, M. (2024). Designing Inclusive Computational Thinking Learning Trajectories for the Youngest Learners. Education Sciences, 14(7), 733. https://doi.org/10.3390/educsci14070733

Hickmott, D., Prieto-Rodriguez, E., & Holmes, K. (2018). A Scoping Review of Studies on Computational Thinking in K–12 Mathematics Classrooms. Digital Experiences in Mathematics Education, 4(1), 48–69. https://doi.org/10.1007/s40751-017-0038-8

Hinterplattner, S., Skogø, J. S., Kröhn, C., & Sabitzer, B. (2020). The Children’s Congress: A Benefit to All Levels of Schooling by Strengthening Computational Thinking. International Journal of Learning and Teaching, 6(4), 241–246. https://doi.org/10.18178/ijlt.6.4.241-246

Hu, J., Li, C., Ge, Y., Yang, J., Zhu, S., & He, C. (2024). Mapping the Evolution of Digital Health Research: Bibliometric Overview of Research Hotspots, Trends, and Collaboration of Publications in JMIR (1999-2024). Journal of Medical Internet Research, 26, e58987. https://doi.org/10.2196/58987

Irawan, E., Rosjanuardi, R., & Prabawanto, S. (2024). Research trends of computational thinking in mathematics learning: A bibliometric analysis from 2009 to 2023. Eurasia Journal of Mathematics, Science and Technology Education, 20(3), em2417. https://doi.org/10.29333/ejmste/14343

Kallia, M., van Borkulo, S. P., Drijvers, P., Barendsen, E., & Tolboom, J. (2021). Characterising computational thinking in mathematics education: a literature-informed Delphi study. Research in Mathematics Education, 23(2), 159–187. https://doi.org/10.1080/14794802.2020.1852104

Kamalodeen, V. J. (2022). Computational thinking for all: a new skill for the digital age. Caribbean Curriculum, 29, 223–250. https://doi.org/https://journals.sta.uwi.edu/ojs/index.php/cc/article/view/8324

Lee, K. W., Loh, H. C., Ching, S. M., Devaraj, N. K., & Hoo, F. K. (2020). Effects of Vegetarian Diets on Blood Pressure Lowering: A Systematic Review with Meta-Analysis and Trial Sequential Analysis. Nutrients, 12(6), 1604. https://doi.org/10.3390/nu12061604

Lehmann, T. H. (2025). Examining the interaction of computational thinking skills and heuristics in mathematical problem solving. Research in Mathematics Education, 27(2), 269–290. https://doi.org/10.1080/14794802.2025.2460460

Leung, S. K. Y., Wu, J., & Li, J. W. (2024). Children’s knowledge construction of computational thinking in a play-based classroom. Early Child Development and Care, 194(2), 208–229. https://doi.org/10.1080/03004430.2023.2299405

Lismaya, L., Hartono, H., Subali, B., Sumarni, W., Ridlo, S., & Nuswowati, M. (2025). Higher order thinking skills research trends: a bibliometric analysis in selected journals (2014 to 2023). International Journal of Evaluation and Research in Education (IJERE), 14(1), 695. https://doi.org/10.11591/ijere.v14i1.29590

Montuori, C., Gambarota, F., Altoé, G., & Arfé, B. (2024). The cognitive effects of computational thinking: A systematic review and meta-analytic study. Computers & Education, 210, 104961. https://doi.org/10.1016/j.compedu.2023.104961

Muhammad, I., Rusyid, H. K., Maharani, S., & Angraini, L. M. (2023). Computational Thinking Research in Mathematics Learning in the Last Decade: A Bibliometric Review. International Journal of Education in Mathematics, Science and Technology, 12(1), 178–202. https://doi.org/10.46328/ijemst.3086

Nurlaelah, E., Usdiyana, D., & Fadilah, N. (2024). The Relationship Between Computational Thinking Ability and Logical Mathematical Intelligence. Mosharafa: Jurnal Pendidikan Matematika, 13(1), 87–96. https://doi.org/10.31980/mosharafa.v13i1.1978

Passas, I. (2024). Bibliometric Analysis: The Main Steps. Encyclopedia, 4(2), 1014–1025. https://doi.org/10.3390/encyclopedia4020065

Pérez, A. (2018). A Framework for Computational Thinking Dispositions in Mathematics Education. Journal for Research in Mathematics Education, 49(4), 424–461. https://doi.org/10.5951/jresematheduc.49.4.0424

Rachman, K. (2026). Analisis kemampuan computational thinking dalam menyelesaikan materi pecahan matematika pada siswa kelas v sekolah dasar. Jurnal Riset Pendidikan Dasar (JRPD), 9(10). https://doi.org/https://doi.org/10.26618/cc8m8z68

Rana, S., & Pragati. (2024). A Bibliometric and Visualization Analysis of Human Capital and Sustainability. Vision: The Journal of Business Perspective, 28(3), 303–312. https://doi.org/10.1177/09722629221105773

Rich, K. M., Yadav, A., & Larimore, R. A. (2020). Teacher implementation profiles for integrating computational thinking into elementary mathematics and science instruction. Education and Information Technologies, 25(4), 3161–3188. https://doi.org/10.1007/s10639-020-10115-5

Rodríguez-Martínez, J. A., González-Calero, J. A., & Sáez-López, J. M. (2020). Computational thinking and mathematics using Scratch: an experiment with sixth-grade students. Interactive Learning Environments, 28(3), 316–327. https://doi.org/10.1080/10494820.2019.1612448

Roussou, E., & Rangoussi, M. (2020). On the Use of Robotics for the Development of Computational Thinking in Kindergarten: Educational Intervention and Evaluation. In Robotics in Education (pp. 31–44). Springer International Publishing. https://doi.org/10.1007/978-3-030-26945-6_3

Steingrimsson, J. A., Barker, D. H., Bie, R., & Dahabreh, I. J. (2024). Systematically missing data in causally interpretable meta-analysis. Biostatistics, 25(2), 289–305. https://doi.org/10.1093/biostatistics/kxad006

Sung, W., Ahn, J., & Black, J. B. (2017). Introducing computational thinking to young learners: Practicing computational perspectives through embodiment in mathematics education. Technology, Knowledge and Learning, 10(4), 1003–1029. https://doi.org/https://doi.org/10.1007/s10758-017-9328

Suseelan, M., Chew, C. M., & Chin, H. (2022). Research on Mathematics Problem Solving in Elementary Education Conducted from 1969 to 2021: A Bibliometric Review. International Journal of Education in Mathematics, Science and Technology, 10(4), 1003–1029. https://doi.org/10.46328/ijemst.2198

Tariq, R., Aponte Babines, B. M., Ramirez, J., Alvarez-Icaza, I., & Naseer, F. (2025). Computational thinking in STEM education: current state-of-the-art and future research directions. Frontiers in Computer Science, 6. https://doi.org/10.3389/fcomp.2024.1480404

Taslibeyaz, E., Kursun, E., & Karaman, S. (2020). How to Develop Computational Thinking: A Systematic Review of Empirical Studies. Informatics in Education. https://www.ceeol.com/search/article-detail?id=914762

Urhan, S. (2022). Using Habermas’ construct of rationality to analyze students’ computational thinking: The case of series and vector. Education and Information Technologies, 27(8), 10869–10948. https://doi.org/10.1007/s10639-022-11002-x

Valovičová, Ľ., Ondruška, J., Zelenický, Ľ., Chytrý, V., & Medová, J. (2020). Enhancing Computational Thinking through Interdisciplinary STEAM Activities Using Tablets. Mathematics, 8(12), 1–15. https://doi.org/10.3390/math8122128

Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining Computational Thinking for Mathematics and Science Classrooms. Journal of Science Education and Technology, 25(1), 127–147. https://doi.org/10.1007/s10956-015-9581-5

Xiao, Y., & Watson, M. (2019). Guidance on Conducting a Systematic Literature Review. Journal of Planning Education and Research, 39(1), 93–112. https://doi.org/10.1177/0739456X17723971

Yang, K., Liu, X., & Chen, G. (2020). The Influence of Robots on Students’ Computational Thinking: A Literature Review. International Journal of Information and Education Technology, 10(8), 627–631. https://doi.org/10.18178/ijiet.2020.10.8.1435

Zyoud, S. H., Shakhshir, M., Koni, A., Shahwan, M., Jairoun, A. A., & Al-Jabi, S. W. (2023). Olfactory and Gustatory Dysfunction in COVID-19: A Global Bibliometric and Visualized Analysis. Annals of Otology, Rhinology & Laryngology, 132(2), 164–172. https://doi.org/10.1177/00034894221082735

Published

2026-08-24

How to Cite

Rachman, K., & Andrijati , N. (2026). Mapping the Research Trends of Computational Thinking in Mathematics Education: A Bibliometric Analysis. Jurnal Riset Dan Inovasi Pembelajaran, 6(2), 901–914. https://doi.org/10.51574/jrip.v6i2.5633