As generative AI tools increasingly influence how students write, problem-solve, and reflect, educators are facing urgent questions about the future of thinking and cognition in the classroom. What does it mean to learn when AI can do so much of the thinking for us (or appear to)?
This presentation explores the cognitive implications of AI-assisted learning, drawing on examples from the speaker as a Harvard educator training learning professionals globally. We’ll unpack the difference between how humans and large language models "understand", and why generative AI often appears deceptively humanlike in conversation. We’ll also examine the allure and risks of cognitive offloading—why students (and educators) gravitate toward AI support, and what happens when that reliance affects deeper learning and metacognition.
Real classroom examples will illustrate both the benefits and limitations of generative AI in supporting thinking: from AI-powered reflection tools to simulated peer tutors. The presentation will also introduce current research debates—such as "cognitive debt" and "co-intelligence"—and how these shape evolving views on AI’s role in learning.
This session invites educators to rethink what kinds of cognition we want to preserve, cultivate, or challenge in a world where AI is an increasingly ubiquitous thinking partner.

Authors:
Gloria Tam, Harvard University & Minerva University, United States

About the Presenter(s)
Dr. Gloria Tam is a Harvard Extension School faculty member and Professor at Minerva University. She focuses on generative AI in education and cognition and learning, and is developing frameworks for future-ready, AI-enhanced pedagogy.

Connect on Linkedin
https://www.linkedin.com/in/gloria-tam/

See this presentation on the full schedule – Wednesday Schedule

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