How do students regulate their learning with a genAI chatbot?

Abstract

Self-regulated learning (SRL) is essential for effective learning, yet students often struggle to regulate in digital environments, including suboptimal learning tool use. The rapid integration of generative AI (e.g., ChatGPT) into learning settings raises questions about their role in supporting or hindering SRL. This exploratory study investigated how students’ SRL in a technology-enhanced learning environment with a genAI tool was associated with learning processes and performance. Thirty university students were tasked to read texts and write an essay within 45 minutes. Learning performance was measured using knowledge and transfer tests, and the essay. SRL processes were measured using trace-based SRL event analysis and learner-genAI interaction with chatbot log events and coded queries. Most students (73%) used the chatbot voluntarily, primarily for seeking information. Chatbot users achieved higher essay scores than non-users. Chatbot interaction frequencies correlated positively with high cognitive activities; durations of chatbot use and high cognition negatively correlated with reading time. Qualitative data indicated reliance on the chatbot to summarise and extract key points, suggesting offloading of learning. Findings highlight potential performance benefits but also risks of outsourcing critical SRL processes to genAI. Implications point to instructional and tool design that align technological advances with educational fit.