Quant Hub: Augmenting socially shared regulation of learning through human-AI interactions in collaborative inquiry tasks

Success in collaborative learning tasks requires socially shared regulation of learning (SSRL). SSRL involves learners working together to understand the task, set common goals, plan and implement strategies to achieve those goals, and adapt their understanding and strategies if their progress is not on track. SSRL is particularly important in collaborative inquiry tasks, where students need to discover knowledge that is new to them. However, collaborative inquiry tasks may pose various obstacles that can trigger the need for SSRL, such as difficulties in making sense of the task or understanding complex science concepts. To provide real-time support for SSRL, recent advances in artificial intelligence (AI) have enabled new approaches to detecting these SSRL triggers. In this seminar, I will introduce our metacognitive AI agent (MAI), which augments SSRL by raising students’ metacognitive awareness of these SSRL triggers in authentic secondary school science inquiry classrooms. Based on our empirical insights, I will discuss the challenges and opportunities of leveraging human-AI interactions to empower agentic students in collaborative inquiry tasks.

Teams-link: https://teams.microsoft.com/l/meetup-join/19%3ameeting_ZDYwMTY0ZmQtNjkzYS00NjFlLWEzNzgtNWYzMTkzNzQ1YmM2%40thread.v2/0?context=%7b%22Tid%22%3a%22cc95de1b-97f5-4f93-b4ba-fe68b852cf91%22%2c%22Oid%22%3a%22b33f55d8-6202-46f8-a141-737715faff88%22%7d