The Role of Artificial Intelligence in Programming Education and Its Impact on the Learning Process

Bagas Dwiantoro, Yudianto Sujana, Puspanda Hatta

Abstract

The integration of Artificial Intelligence (AI) into programming education has rapidly expanded, offering both promising opportunities and complex challenges. This study conducts a systematic literature review (SLR) using the PRISMA framework to examine the influence of AI tools on creativity, collaboration, and technology acceptance in programming education. A total of 33 peer-reviewed studies published between 2022 and 2024 were analysed to explore the pedagogical impact of AI. The findings indicate that AI tools support creative problem-solving, enhance collaborative learning, and increase student engagement through personalized feedback and adaptive learning environments. Despite these benefits, concerns remain about the potential for over-reliance on AI, reduced critical thinking, and ethical issues such as bias and authorship. While AI encourages iterative and imaginative approaches to programming, its successful implementation depends on instructional strategies that promote reflection, responsible tool use, and alignment with real-world programming practices. This study emphasizes the importance of balancing the advantages of AI with thoughtful pedagogy to support meaningful learning. Future research is recommended to investigate the long-term effects of AI on student development and to refine frameworks for integrating AI tools into programming education.

Keywords

Artificial intelligence; learning process; programming education

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References

Alanazi, M., Soh, B., Samra, H., & Li, A. (2025). The Influence of Artificial Intelligence Tools on Learning Outcomes in Computer Programming: A Systematic Review and Meta-Analysis. Computers, 14(5), 185. https://doi.org/10.3390/computers14050185

Berrezueta-Guzman, S., Krusche, S., & Wagner, S. (2025). From Coders to Critics: Empowering Students through Peer Assessment in the Age of AI Copilots. https://arxiv.org/pdf/2505.22093

Bucea-Manea-Țoniş, R., Kuleto, V., Gudei, S. C. D., Lianu, C., Lianu, C., Ilić, M. P., & Păun, D. (2022). Artificial Intelligence Potential in Higher Education Institutions Enhanced Learning Environment in Romania and Serbia. Sustainability, 14(10), 5842. https://doi.org/10.3390/su14105842

Bull, C., & Kharrufa, A. (2024). Generative Artificial Intelligence Assistants in Software Development Education: A Vision for Integrating Generative Artificial Intelligence into Educational Practice, Not Instinctively Defending Against It. IEEE Software, 41(2), 52–59. https://doi.org/10.1109/MS.2023.3300574

Cervantes, J., & Navarro, E. (2025). Business Students’ Perceptions of AI in Higher Education: An Analysis Using the Technology Acceptance Model. Journal of Interdisciplinary Perspectives, 3(6). https://doi.org/10.69569/jip.2025.194

Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1), 38. https://doi.org/10.1186/s41239-023-00408-3

Fan, G., Liu, D., Zhang, R., & Pan, L. (2025). The impact of AI-assisted pair programming on student motivation, programming anxiety, collaborative learning, and programming performance: a comparative study with traditional pair programming and individual approaches. International Journal of STEM Education, 12(1), 1–17. https://doi.org/10.1186/S40594-025-00537-3

Kohen-Vacs, D., Usher, M., & Jansen, M. (2025). Integrating Generative AI into Programming Education: Student Perceptions and the Challenge of Correcting AI Errors. International Journal of Artificial Intelligence in Education, 1–19. https://doi.org/10.1007/s40593-025-00496-4

Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X.-H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025). Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task. https://arxiv.org/pdf/2506.08872

Lemke, C., Kirchner, K., Anandarajah, L., & Herfurth, F. (2023). Exploring the Student Perspective: Assessing Technology Readiness and Acceptance for Adopting Large Language Models in Higher Education. European Conference on E-Learning, 22(1), 156–164. https://doi.org/10.34190/ecel.22.1.1828

Lin, H., & Chen, Q. (2024). Artificial intelligence (AI) -integrated educational applications and college students’ creativity and academic emotions: students and teachers’ perceptions and attitudes. BMC Psychology, 12(1), 487. https://doi.org/10.1186/s40359-024-01979-0

Liu, N. (2025). Exploring the factors influencing the adoption of artificial intelligence technology by university teachers: the mediating role of confidence and AI readiness. BMC Psychology, 13(1), 311. https://doi.org/10.1186/s40359-025-02620-4

Lyu, W., Wang, Y., Sun, Y., & Zhang, Y. (2025). Will Your Next Pair Programming Partner Be Human? An Empirical Evaluation of Generative AI as a Collaborative Teammate in a Semester-Long Classroom Setting. Proceedings of the Twelfth ACM Conference on Learning @ Scale, 83–94. https://doi.org/10.1145/3698205.3729544

Ma, Q. C., Wu, S. T., & Koedinger, K. (2023). Is AI the better programming partner? Human-Human Pair Programming vs. Human-AI pAIr Programming. CEUR Workshop Proceedings, 3487, 64–77. https://arxiv.org/pdf/2306.05153

Monib, W. K., Qazi, A., Apong, R. A., Azizan, M. T., De Silva, L., & Yassin, H. (2024). Generative AI and future education: a review, theoretical validation, and authors’ perspective on challenges and solutions. PeerJ Computer Science, 10, e2105. https://doi.org/10.7717/peerj-cs.2105

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, 372, n71. https://doi.org/10.1136/bmj.n71

Pan, Z., Xie, Z., Liu, T., & Xia, T. (2024). Exploring the Key Factors Influencing College Students’ Willingness to Use AI Coding Assistant Tools: An Expanded Technology Acceptance Model. Systems, 12(5), 176. https://doi.org/10.3390/systems12050176

Qian, Y. (2025). Pedagogical Applications of Generative AI in Higher Education: A Systematic Review of the Field. TechTrends, 1–16. https://doi.org/10.1007/s11528-025-01100-1

Qureshi, B. (2023). ChatGPT in Computer Science Curriculum Assessment: An analysis of Its Successes and Shortcomings. 2023 9th International Conference on E-Society, e-Learning and e-Technologies, 7–13. https://doi.org/10.1145/3613944.3613946

Rahe, C., & Maalej, W. (2025). How Do Programming Students Use Generative AI? Proceedings of the ACM on Software Engineering, 2(FSE), 978–1000. https://doi.org/10.1145/3715762

Shrivastava, P. (2025). Understanding acceptance and resistance toward generative AI technologies: a multi-theoretical framework integrating functional, risk, and sociolegal factors. Frontiers in Artificial Intelligence, 8, 1565927. https://doi.org/10.3389/frai.2025.1565927

Song, F., Agarwal, A., & Wen, W. (2024). The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4856935

Stamer, T., Steinhäuser, J., & Flägel, K. (2023). Artificial Intelligence Supporting the Training of Communication Skills in the Education of Health Care Professions: Scoping Review. Journal of Medical Internet Research, 25(1), e43311. https://doi.org/10.2196/43311

Takerngsaksiri, W., Warusavitarne, C., Yaacoub, C., Keng Hou, M. H., & Tantithamthavorn, C. (2024). Students’ Perspectives on AI Code Completion: Benefits and Challenges. 2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC), 1606–1611. https://doi.org/10.1109/COMPSAC61105.2024.00252

Ursavaş, Ö. F., Yalçın, Y., İslamoğlu, H., Bakır-Yalçın, E., & Cukurova, M. (2025). Rethinking the importance of social norms in generative AI adoption: investigating the acceptance and use of generative AI among higher education students. International Journal of Educational Technology in Higher Education, 22(1), 38. https://doi.org/10.1186/s41239-025-00535-z

Wang, Y., Hanafi Zaid, Y., Li, J., & Pan, Y. (2024). Opportunities and Challenges of Using ChatGPT as a Teaching Assistant in English Language Teaching: A Systematic Literature Review. Proceedings of the 2024 International Symposium on Artificial Intelligence for Education, 375–382. https://doi.org/10.1145/3700297.3700362

Welter, A., Schneider, N., Dick, T., Weis, K., Tinnes, C., Wyrich, M., & Apel, S. (2025). From Developer Pairs to AI Copilots: A Comparative Study on Knowledge Transfer. https://arxiv.org/pdf/2506.04785

Xu, Z. (2024). AI in education: Enhancing learning experiences and student outcomes. Applied and Computational Engineering, 51(1), 104–111. https://doi.org/10.54254/2755-2721/51/20241187

Yan, W., Nakajima, T., & Sawada, R. (2024). Benefits and Challenges of Collaboration between Students and Conversational Generative Artificial Intelligence in Programming Learning: An Empirical Case Study. Education Sciences, 14(4), 433. https://doi.org/10.3390/educsci14040433

Zastudil, C., Rogalska, M., Kapp, C., Vaughn, J., & MacNeil, S. (2023). Generative AI in Computing Education: Perspectives of Students and Instructors. 2023 IEEE Frontiers in Education Conference (FIE), 1–9. https://doi.org/10.1109/FIE58773.2023.10343467

Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: a systematic review. Smart Learning Environments, 11(1), 28. https://doi.org/10.1186/s40561-024-00316-7

Zhong, T., Zhu, G., You Lim, K., Soon Ong, Y., Zhong Candidate, T., & Zhu Assistant Professor, G. (2024). Generative AI as a Tool or Leader? Exploring AI-Augmented Thinking in Student Programming Tasks. https://arxiv.org/pdf/2411.19490

Zhou, M., & Peng, S. (2025). The Usage of AI in Teaching and Students’ Creativity: The Mediating Role of Learning Engagement and the Moderating Role of AI Literacy. Behavioral Sciences, 15(5), 587. https://doi.org/10.3390/bs15050587

DOI: https://doi.org/10.20961/ijie.v9i1.103884