THE IMPACT OF INTEGRATING ARTIFICIAL INTELLIGENCE IN TEACHING ON PROGRAMMING PEDAGOGY: A SCOPING REVIEW

Abstract

Background: Artificial Intelligence (AI) has emerged as a transformative force in higher education, particularly in programming instruction where students often struggle with computational thinking and problem-solving.  Advancements in AI technologies such as adaptive learning platforms, generative assistants, and automated feedback systems show strong potential to enhance student engagement and improve learning outcomes. However, research on AI integration in programming education remains fragmented with limited consolidated evidence on its pedagogical implications. This scoping review aims to integrate current studies to identify AI’s pedagogical functions within programming education and highlight the key challenges and opportunities in this evolving field.  Method: A scoping review was systematically conducted using the Scopus and Web of Science databases to identify the nature of existing research on AI in programming education and to determine the pedagogical roles reported across studies. Guided by Arksey and O’Malley’s framework and the PRISMA-ScR guidelines, the search process identified 598 records, of which 15 met the inclusion criteria for thematic analysis.  Result: The review identified five pedagogical roles of AI in programming education: (i) enhancer of adaptive learning and engagement, (ii) facilitator of personalized learning pathways, (iii) assessor providing automated feedback and evaluation, (iv) scaffolder supporting problem-solving and computational thinking, and (v) personalizer tailoring content to learner needs. While AI was found to improve student confidence, creativity, and instructional design, critical concerns were also highlighted, including over-reliance on AI tools, ethical risks such as plagiarism and bias, and the lack of structured pedagogical frameworks.  Conclusion: This scoping review consolidates emerging evidence and emphasizes the dual role of AI as both a pedagogical partner and a source of challenges. The findings call for structured professional development, clear ethical guidelines, and competency-based pedagogical frameworks to ensure sustainable and responsible AI integration in programming education.