Study on Epistemic Authority Negotiation in AI-Assisted Lesson Planning by Mathematics Preservice Teachers

A study by Yangzhou University and others in China shows that five mathematics preservice teachers demonstrated 16 instances of authority retention, 12 of sharing, and 6 of ceding during AI-assisted lesson planning. The research identified two risks: a closed verification loop and an insight-action gap. The study analyzed 34 decision episodes through screen recordings, concurrent verbalizations, and other methods.

This research provides empirical evidence for understanding professional judgment in AI-assisted lesson planning, highlighting risks of automation bias and cognitive offloading. The study identifies two issues - closed verification loops and insight-action gaps - offering specific directions for teacher training. Affects the direction of AI literacy training for teachers, emphasizing the need for enhanced professional judgment training Highlights potential risks in AI-assisted lesson planning, providing reference for educational policy-making