Guidelines for Integrating Generative AI Into Programming Education at The Diploma Level in Malaysian Polytechnics: Balancing Benefits and Risks

Abstract

The integration of Generative Artificial Intelligence (GAI) in programming education offers significant benefits, including personalized learning, real-time feedback, and debugging support. However, improper use may lead to over-reliance, reduced problem-solving skills, and academic integrity concerns. This study develops structured guidelines for AI integration in diploma-level programming education at Malaysian Polytechnics, ensuring AI enhances learning without replacing fundamental programming competencies. A Systematic Literature Review (SLR), Semi-Structured Interviews with Educators, and Focus Group Discussions (FGDs) were conducted to identify best practices, challenges, and ethical considerations. Findings indicate that while AI improves learning efficiency and engagement, students often misinterpret AI-generated code or rely on AI without understanding programming concepts. Educators struggle with assessing AI-assisted work and ensuring academic integrity, necessitating revised assessments and AI literacy training. This paper proposed guidelines focusing on students using AI as a support tool rather than a substitute, educators integrating AI responsibly, and institutions establishing clear AI policies on ethics, data privacy, and assessment methods. A balanced approach, combining AI with traditional teaching and active learning strategies, is essential for maintaining critical thinking and programming skills. Future research should focus on pilot implementation of these guidelines, longitudinal studies on AI’s impact, and AI-specific assessment development. By adopting these recommendations, Malaysian Polytechnics can effectively integrate AI into programming education, maximizing benefits while mitigating risks.

Keywords: generative AI, programming education, AI integration, academic integrity, AI literacy