Bridging Self-Regulated Learning and Generative AI

Generative artificial intelligence (GenAI) offers significant potential for education by providing adaptive feedback and scaffolding, which aligns with self-regulated learning (SRL). SRL describes how learners initiate, monitor, and adapt their cognition, motivation, and behaviour to attain academic goals. This chapter reviews the literature at the intersection of GenAI and SRL to address two questions: what roles do generative tools play in supporting SRL phases, and what challenges arise during their integration? Adopting Zimmerman’s cyclical SRL model as a conceptual framework, this review synthesises empirical studies from formal education published from 2019 to 2025, encompassing quantitative and qualitative evidence across various disciplines. Findings indicate that GenAI can effectively support SRL’s forethought, performance, and reflection phases, leading to gains in content knowledge and strategic engagement, particularly when coupled with structured prompts and teacher mediation. However, challenges include potential overreliance, limited interactivity, and ethical concerns. For GenAI to realise its full potential in fostering scalable and equitable SRL, integrative designs coordinating affordances across SRL phases, explicit prompt literacy training, and robust teacher professional development are essential. Future research should prioritise longitudinal, multi-institutional studies to capture evolving strategies and address generalisability and equity.