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Research Article Open access CC BY 4.0

The Use of Generative Artificial Intelligence Tools in Programming Education: Opportunities and Challenges

Mariya P. Hristova

Asian Journal of Research in Computer Science · pp. 93–108 · Published 27 May 2026

10.9734/ajrcos/2026/v19i5863

Abstract

Background: Generative AI is increasingly transforming programming education by enhancing learning support and efficiency while also raising challenges related to academic integrity, critical thinking, and pedagogical adaptation. Aims: The aim of this study is to analyze the opportunities and challenges associated with the use of generative artificial intelligence tools in programming education. The paper also examines the impact of AI technologies on teaching practices, student learning experiences, and the future development of computer science education. Study Design:  This study is designed as a review paper based on analysis of recent scientific publications related to generative artificial intelligence and programming education. Study Context: The study examines contemporary educational trends related to generative artificial intelligence and programming education in higher education environments. Methodology: The research methodology includes a literature review and comparative analysis of contemporary studies, scientific articles, educational reports, and technological resources related to generative AI tools such as ChatGPT, GitHub Copilot, Gemini, and Claude. The study examines their educational applications, advantages, limitations, and influence on programming learning environments. Results: The analysis shows that generative AI tools provide significant opportunities for personalized learning, immediate feedback, increased student engagement, and improved accessibility to educational resources. These technologies support students in code generation, debugging, and understanding programming concepts. At the same time, several challenges were identified, including academic integrity issues, overreliance on AI-generated solutions, reduced critical thinking, ethical concerns, and potential inaccuracies in generated code. The study also highlights the changing role of teachers as facilitators and mentors in AI-supported educational environments. Conclusion: Generative artificial intelligence technologies have strong potential to improve programming education and enhance learning experiences when integrated responsibly and effectively. However, educational institutions and educators should establish appropriate pedagogical strategies and ethical guidelines to ensure balanced and meaningful use of AI tools in computer science education.

Generative AI programming education artificial intelligence higher education ChatGPT computer science education AI-assisted learning educational technologies

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