The Role of Artificial Intelligence in Instructional Skills Workshop: A Review of Applications, Challenges, and a Proposed Framework for Integration

The Instructional Skills Workshop (ISW) is a highly effective, peer-based faculty development model for enhancing teaching effectiveness. Concurrently, Artificial Intelligence (AI) presents transformative opportunities for personalized learning and feedback in education. This paper addresses the challenge of integrating AI into a human-centric, collaborative program like the ISW, which introduces significant risks, including algorithmic bias, over-reliance on automation, and the potential erosion of its core pedagogical values. There is a notable absence of frameworks to guide this integration effectively. We propose the AI-Augmented Reflective Practice (AI-ARP) framework, a model designed to strategically integrate AI into the ISW. The framework positions AI as a supplemental tool that provides data-driven insights to enrich, rather than replace, the essential processes of peer feedback and facilitated reflection. The AI-ARP framework comprises four stages: (1) AI-assisted feedback generation, (2) reflective journaling support, (3) peer-AI co-reflection sessions, and (4) facilitator-guided synthesis. Grounded in a synthesis of educational technology literature and learning theories, this human-in-the-loop approach aims to enhance the richness of feedback and promote deeper self-reflection while mitigating risks and preserving the invaluable human-centric nature of the ISW.