MAPPING GLOBAL RESEARCH TRENDS ON COMPUTATIONAL THINKING IN PRE-SERVICE TEACHER EDUCATION: A BIBLIOMETRIC ANALYSIS (2015-2025)
DOI:
https://doi.org/10.35631/IJMOE.829009Keywords:
Computational Thinking (CT), Bibliometric Analysis, Educational Robotics and STEM Integration, Pre-Service Teacher Education, Teacher Preparation and TrainingAbstract
Computational Thinking (CT), which involves systematic, algorithmic problem-solving processes, is widely known as a critical 21st-century skill, making its incorporation into pre-service teacher education vital for preparing future educators. However, many teacher training programs worldwide have yet to fully integrate CT, and a comprehensive mapping of the field’s development is needed to understand its evolution and inform curriculum enhancements. This research bridges that gap via a bibliometric analysis of 439 Scopus-indexed publications from 2015 to 2025 on CT in pre-service teacher education. Relevant literature was identified via advanced Scopus search queries combining keywords such as “computational thinking,” “pre-service teacher,” and “teacher education,” filtered to English-language documents. The dataset was analyzed using Scopus Analyzer for descriptive statistics, cleaned with OpenRefine, and visualized via VOSviewer for co-occurrence mapping of keywords and co-authorship networks. Results indicate a steady growth in publications over the past decade, peaking in 2022, reflecting escalating global scholarly interest in this area. Citation analysis identified the most cited papers and prolific authors, and the United States, Turkey, and Germany emerged as the leading countries in publication output. Keyword co-occurrence mapping revealed dominant research themes such as “computational thinking,” “teacher education,” and “educational robotics,” while co-authorship analysis showed robust international collaborations among scholars and institutions. In conclusion, this bibliometric mapping provides a comprehensive overview of the field’s trajectory and reveals trends, influential works, geographical contributions, thematic focus, and collaboration patterns. Additionally, it offers future research directions to support the strategic development of CT curricula and training frameworks in pre-service teacher education.
Downloads
References
Al-Khoury, A., Hussein, S. A., Abdulwhab, M., Aljuboori, Z. M., Haddad, H., Ali, M. A., Abed, I. A., & Flayyih, H. H. (2022). Intellectual Capital History and Trends: A Bibliometric Analysis Using Scopus Database. Sustainability (Switzerland), 14(18). https://doi.org/10.3390/su141811615
Alves, J. L., Borges, I. B., & De Nadae, J. (2021). Sustainability in complex projects of civil construction: Bibliometric and bibliographic review. Gestao e Producao, 28(4). https://doi.org/10.1590/1806-9649-2020v28e5389
Angeli, C. (2022). The effects of scaffolded programming scripts on pre-service teachers’ computational thinking: Developing algorithmic thinking through programming robots. International Journal of Child-Computer Interaction, 31. https://doi.org/10.1016/j.ijcci.2021.100329
Angeli, C., & Jaipal-Jamani, K. (2018). Preparing pre-service teachers to promote computational thinking in school classrooms. In Computational Thinking in the STEM Disciplines: Foundations and Research Highlights (pp. 127–150). Springer International Publishing. https://doi.org/10.1007/978-3-319-93566-9_7
Angeli Valanides, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). A K-6 computational thinking curriculum framework: Implications for teacher knowledge. Educational Technology and Society, 19(3), 47–57.
Appio, F. P., Cesaroni, F., & Di Minin, A. (2014). Visualizing the structure and bridges of the intellectual property management and strategy literature: a document co-citation analysis. Scientometrics, 101(1), 623–661. https://doi.org/10.1007/s11192-014-1329-0
Assyakur, D. S., & Rosa, E. M. (2022). Spiritual Leadership in Healthcare: A Bibliometric Analysis. Jurnal Aisyah : Jurnal Ilmu Kesehatan, 7(2). https://doi.org/10.30604/jika.v7i2.914
Bers, M. U. (2021). Teaching Computational Thinking and Coding to Young Children. In Teaching Computational Thinking and Coding to Young Children. IGI Global. https://doi.org/10.4018/978-1-7998-7308-2
Chan, K. K. (2020). Fostering future teachers’ competence in computational thinking in an educational technology course. In Handbook of Research on Using Educational Robotics to Facilitate Student Learning (pp. 257–273). IGI Global. https://doi.org/10.4018/978-1-7998-6717-3.ch010
Das, S., & Mitra, A. (2024). Enhancing logic and problem-solving skills in the digital age. In Revolutionizing Curricula Through Computational Thinking, Logic, and Problem Solving (pp. 40–59). IGI Global. https://doi.org/10.4018/979-8-3693-1974-1.ch003
di Stefano, G., Peteraf, M., & Veronay, G. (2010). Dynamic capabilities deconstructed: A bibliographic investigation into the origins, development, and future directions of the research domain. Industrial and Corporate Change, 19(4), 1187–1204. https://doi.org/10.1093/icc/dtq027
Dong, W., Li, Y., Sun, L., & Liu, Y. (2024). Developing pre-service teachers’ computational thinking: a systematic literature review. International Journal of Technology and Design Education, 34(1), 191–227. https://doi.org/10.1007/s10798-023-09811-3
Fahimnia, B., Sarkis, J., & Davarzani, H. (2015). Green supply chain management: A review and bibliometric analysis. In International Journal of Production Economics (Vol. 162, pp. 101–114). https://doi.org/10.1016/j.ijpe.2015.01.003
Ghani, A., Griffiths, D., Salha, S., Affouneh, S., Khalili, F., Khlaif, Z. N., & Burgos, D. (2022). Developing Teaching Practice in Computational Thinking in Palestine. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.870090
Hoić-Božić, N., Mezak, J., & Tomljenović, K. (2019). Enhancing teachers’ computational thinking skills through game based learning.
In R. J. & L. M. (Eds.), CEUR Workshop Proceedings (Vol. 2494). CEUR-WS. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075288263&partnerID=40&md5=fc098b92d104efca0f7201502f77bd9e
Iwata, M., Laru, J., & Mäkitalo, K. (2022). How the Pre-service Teachers Associate Computational Thinking with Programming? A Case Study of an Introductory Programming Course in Teacher Education. In Z. X., G. C., F. N., & S. M. (Eds.), Proceedings of International Conference on Computational Thinking Education (pp. 68–71). The Education University of Hong Kong. https://doi.org/10.34641/ctestem.2022.467
Ketelhut, D. J., Mills, K., Hestness, E., Cabrera, L., Plane, J., & McGinnis, J. R. (2020). Teacher Change Following a Professional Development Experience in Integrating Computational Thinking into Elementary Science. Journal of Science Education and Technology, 29(1), 174–188. https://doi.org/10.1007/s10956-019-09798-4
Khiste, G. P., & Paithankar, R. R. (2017). Analysis of Bibliometric term in Scopus. International Research Journal, 01(32), 78–83.
Leonard, J., Mitchell, M., Barnes-Johnson, J., Unertl, A., Outka-Hill, J., Robinson, R., & Hester-Croff, C. (2018). Preparing Teachers to Engage Rural Students in Computational Thinking Through Robotics, Game Design, and Culturally Responsive Teaching. Journal of Teacher Education, 69(4), 386–407. https://doi.org/10.1177/0022487117732317
Li, Y., Schoenfeld, A. H., diSessa, A. A., Graesser, A. C., Benson, L. C., English, L. D., & Duschl, R. A. (2020). On Computational Thinking and STEM Education. Journal for STEM Education Research, 3(2), 147–166. https://doi.org/10.1007/s41979-020-00044-w
Morton, T. (2018). Reconceptualizing and describing teachers’ knowledge of language for content and language integrated learning (CLIL). International Journal of Bilingual Education and Bilingualism, 21(3), 275–286. https://doi.org/10.1080/13670050.2017.1383352
Mouza, C., Yang, H., Pan, Y.-C., Ozden, S., & Pollock, L. (2017). Resetting educational technology coursework for pre-service teachers: A computational thinking approach to the development of technological pedagogical content knowledge (TPACK). Australasian Journal of Educational Technology, 33(3), 61–76. https://doi.org/10.14742/ajet.3521
Oliveira, E. C., Correia, R. C. M., Azevedo, R., Telles, S., MacEdo, A. A., & Bittencourt, R. A. (2022). A Computational Thinking Course for Pre-Service Teachers. In J. M., K. I., & A. A. (Eds.), IEEE Global Engineering Education Conference, EDUCON (Vols. 2022-March, pp. 1082–1088). IEEE Computer Society. https://doi.org/10.1109/EDUCON52537.2022.9766601
Prayogi, S., Yuanita, L., & Wasis, L. (2018). Critical inquiry based learning: A model of learning to promote critical thinking among prospective teachers of physic. Journal of Turkish Science Education, 15(1), 43–56. https://doi.org/10.12973/tused.10220a
Putra, Z. H., Sumadinata, H., Witri, G., Barokah, R. G. S., Gunawan, Y., & Mohd. Jamil, M. R. (2025). The effect of gender, high school major, admission process, and year of study towards pre-service elementary teachers’ computational thinking skills. Education and Information Technologies, 30(11), 15871–15889. https://doi.org/10.1007/s10639-025-13429-4
Rajapakse Mohottige, N. U. S., Bjerke, A. H., & Andersen, R. (2024). Teacher education as stakeholder: teacher educator perspectives on the integration of computational thinking into mathematics and science courses. Teachers and Teaching: Theory and Practice. https://doi.org/10.1080/13540602.2024.2313635
Rinke, C. R., Gladstone-Brown, W., Kinlaw, C. R., & Cappiello, J. (2016). Characterizing STEM Teacher Education: Affordances and Constraints of Explicit STEM Preparation for Elementary Teachers. School Science and Mathematics, 116(6), 300–309. https://doi.org/10.1111/ssm.12185
Rodrigues, R. N., Costa, C., Brito-Costa, S., Abbasi, M., & Martins, F. (2025). Impact of a Training Program on Developing Computational Thinking in Pre-Service Primary School Teachers: From Theory to Practice. Educational Process: International Journal, 14. https://doi.org/10.22521/edupij.2025.14.37
Rodrigues, R. N., Costa, C., & Martins, F. (2024). Integration of computational thinking in initial teacher training for primary schools: a systematic review. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1330065
Sentance, S., & Csizmadia, A. (2017). Computing in the curriculum: Challenges and strategies from a teacher’s perspective. Education and Information Technologies, 22(2), 469–495. https://doi.org/10.1007/s10639-016-9482-0
van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3
Van Eck, N. J., & Waltman, L. (2007). Bibliometric mapping of the computational intelligence field. International Journal of Uncertainty, Fuzziness and Knowldege-Based Systems, 15(5), 625–645. https://doi.org/10.1142/S0218488507004911
Verbeek, A., Debackere, K., Luwel, M., & Zimmermann, E. (2002). Measuring progress and evolution in science and technology - I: The multiple uses of bibliometric indicators. International Journal of Management Reviews, 4(2), 179–211. https://doi.org/10.1111/1468-2370.00083
Voon, X. P., Wong, S. L., Wong, L. H., Khambari, M. N. M., & Syed-Abdullah, S. I. S. (2023). Developing pre-service teachers’ computational thinking through experiential learning: hybridization of plugged and unplugged approaches. Research and Practice in Technology Enhanced Learning, 18. https://doi.org/10.58459/rptel.2023.18006
Walton, M., Walkoe, J., Elby, A., Fofang, J., & Weintrop, D. (2020). Teachers’ conceptualizations of computational and mathematical thinking. In G. M. & H. I.S. (Eds.), Computer-Supported Collaborative Learning Conference, CSCL (Vol. 4, pp. 2053–2060). International Society of the Learning Sciences (ISLS). https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102874401&partnerID=40&md5=3568175c3ea2d299009296cf9344d40f
Wu, Y. C. J., & Wu, T. (2017). A decade of entrepreneurship education in the Asia Pacific for future directions in theory and practice. In Management Decision (Vol. 55, Issue 7, pp. 1333–1350). https://doi.org/10.1108/MD-05-2017-0518
Yadav, A., Stephenson, C., & Hong, H. (2017). Computational thinking for teacher education. Communications of the ACM, 60(4), 55–62. https://doi.org/10.1145/2994591
