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Integrating Generative Artificial Intelligence (AI) and Problem-based Learning (PBL) in Programming Education: Development of Learning Activities and Computational Thinking Performance

Nakkarin Laokhonkha(1), Jiraporn Chano(2),


(1) Mahasarakham University
(2) Mahasarakham University
Corresponding Author

Abstract


Generative Artificial Intelligence (AI) can assist students in programming, but generating correct code does not necessarily reflect computational thinking skills. Therefore, integrating AI with problem-based learning (PBL) may encourage students to analyze problems, evaluate solutions, and develop independent reasoning. This study developed eight programming lesson plans combining Generative AI and PBL to support Grade 11 students' computational thinking. A quasi-experimental pretest-posttest design involved 41 experimental and 38 control students studying HTML, PHP, SQL, and MySQL. Both groups completed assessments with AI assistance permitted. Mean scores increased in both groups, with greater observed improvement in the experimental group. These findings suggest potential instructional benefits, although classroom-level confounding and permitted AI assistance limit conclusions about causal effects and independent computational thinking development.

Keywords


Computational thinking; Generative artificial intelligence; Problem-based learning; Programming education; Secondary education.

References


Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.

Shute, V. J., Sun, C., and Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142-158.

Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn?. Educational Psychology Review, 16(3), 235-266.

Bai, H., Wang, X., and Zhao, L. (2021). Effects of the problem-oriented learning model on middle school students’ computational thinking skills in a Python course. Frontiers in Psychology, 12, 771221.

Reskianissa, A., Sakti, A. W., and Azizah, N. N. (2022). TikTok platform to train middle school students' computational thinking skills in distance learning. ASEAN Journal of Educational Research and Technology, 1(1), 79-86.

Abidin, Z., Herman, T., Wahyudin, W., and Farokhah, L. (2025). Bibliometric analysis using VOSviewer with Publish or Perish of computational thinking and mathematical thinking in elementary school. ASEAN Journal for Science Education, 4(1), 7-16.

Becker, B. A., Denny, P., Finnie-Ansley, J., Luxton-Reilly, A., Prather, J., and Santos, E. A. (2023). Programming is hard-or at least it used to be: Educational opportunities and challenges of AI code generation. Proceedings of the 54th ACM Technical Symposium on Computer Science Education, 1, 500-506.

Nurjamin, A., Nurjamin, L. R., Fajriah, Y. N., Nurjamin, A. K., and Firdaus, H. A. (2026). Integrating generative artificial intelligence (AI)-based multimodal learning in education to enhance literacy aligned with Sustainable Development Goals (SDGs). ASEAN Journal of Educational Research and Technology, 5(1), 71–88.

Biggs, J. (1996). Enhancing teaching through constructive alignment. Higher Education, 32(3), 347-364.

Arifiani, I., Hamidah, L. N., and Rahmawan, S. (2025). Problem based learning (PBL) learning model for increasing learning motivation in chemistry subject: Literature review with bibliometric analysis. ASEAN Journal for Science Education, 4(1), 17-30.

Katel, K. (2026). Artificial intelligence (AI) ChatGPT in academic and science writing education: Student dependency, creativity, and the mediating role of feedback in English as a second language and English as a foreign language contexts. ASEAN Journal for Science Education, 5(2), 155-166.

Brennan, K., and Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Proceedings of the 2012 annual meeting of the American Educational Research Association, 1(25), 13-17.

Thapa, M. B., and Shrestha, K. (2026). Empowering teachers through ChatGPT: Perceptions and experiences in English as a foreign or second language (EFL/ESL) classrooms as a form of community service. ASEAN Journal of Community Service and Education, 5(1), 21-32.

Campbell, M. K., Piaggio, G., Elbourne, D. R., and Altman, D. G. (2012). Consort 2010 statement: extension to cluster randomised trials. Bmj, 345, e5661.

Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4, 863.


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