#438: GenAI Chatbot for Socially Shared Regulation of Learning in CSCL: Impact on University Students' Learning Engagement and Outcome

Supporting socially shared regulation of learning (SSRL) is crucial for successful collaborative learning but is challenging due to its multidimensional and context-sensitive nature. While generative AI (GenAI) chatbots have shown promise in addressing these challenges, research has largely treated SSRL and GenAI chatbots separately, with limited empirical exploration of their integration. Furthermore, existing studies on GenAI chatbots supporting SSRL are mainly conceptual or design-focused, lacking empirical evaluation. Addressing these gaps, we developed SSRLBot, a GenAI chatbot designed to identify SSRL challenges and offer contextual strategies. We conducted a six-week experimental study with 55 Chinese university students, dividing them into two classes: one using SSRLBot (N = 27) and the other without chatbot support (N = 28). Learning engagement and outcomes were assessed through questionnaires, platform log data and products. Results showed that SSRLBot significantly improved students’ learning engagement and outcomes, extending the application of GenAI chatbots from content tutor to group moderators in CSCL.