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The CATALPA Lecture Series is back for another round. Our guest, Yizhou Fan, is a long-time collaborator of Lyn Lim, head of the CATALPA junior research group ATLaS (Adaptive Teaching, Learning, and Support). His subject:

A Metacognitive Approach to Learning and Performance in Human-AI Interaction

Abstract for the talk:

Generative AI has made it easier than ever for human to perform well – but not necessarily to learn well. Learners can now outsource drafting, reasoning, feedback, and even evaluation to AI, producing fluent and high-quality outputs with less effort. This creates a critical tension for education and human-AI interaction: when does AI-supported performance become durable human learning, and when does it become a performance illusion? In this talk, Yizhou Fan addresses this question through a metacognitive lens. He connects the FLoRA project’s work on measuring and scaffolding self-regulated learning with empirical evidence on metacognitive laziness in GenAI-supported learning, where improved task performance does not necessarily translate into knowledge gain or transfer. He then introduces a broader theoretical account of metacognitive offloading and onloading, formalised in the newly proposed model of human-AI interaction. By distinguishing autopilot performance from synergetic mastery, this talk outlines how AI can support not only what learners produce, but also what they become capable of doing.

Afterwards, Yizhou Fan and his colleague Qiong Wang, Professor of Educational Technology at Peking University, look forward to an open exchange with researchers and students from Hagen.