Empowering High School Students’ Self-Regulated Learning in Mathematics through Structured Reflection Lists and Generative AI

This study explores the integration of structured reflection lists and generative AI tools to enhance self-regulated learning (SRL) in high school mathematics. Through a qualitative approach involving post-exam reflection, AI interactions, and teacher feedback, the study seeks to evaluate the impact of these strategies on students’ mathematical performance and learning behaviors. The initial findings suggest that the combination of structured reflection and AI can promote active self-regulation and improve problem-solving abilities.