Keynote Presentation - Thursday, 8 October (0900-1000) (Virtual Presentation)
Building Minds in the Age of AI: The Neuroscience School Leaders Need Now
Neuroscience has made extraordinary advances in revealing how the brain actually learns — yet much of this science has yet to reach the educators who need it most. In this keynote, Barbara Oakley, creator of the world’s most popular course on learning, draws on her latest research to take audiences inside the learning brain, from the physical memory traces (engrams) that form when students learn, to the mental frameworks (schemata) that organize knowledge, to the dramatic shift from effortful recall to automatic intuition as the brain's declarative and procedural memory systems work in tandem.
Along the way, she reveals a paradox at the heart of modern education: in an era when AI can instantly supply any answer, the knowledge students carry in their own heads matters more than ever — because the brain's most powerful learning mechanisms, from prediction errors to schema formation, depend on internalized knowledge to function. Without it, even the best technology becomes a crutch rather than an amplifier.
Drawing on vivid examples from classrooms around the world — including dramatic case studies from Taiwan, New Zealand, and Singapore — Oakley shows what happens when education systems align with the brain's architecture, and what happens when they don't. She examines the striking reversal of the Flynn Effect in wealthy nations, explores why AI tools can paradoxically undermine the learning they aim to support, and offers practical, evidence-based strategies school leaders can use to ensure technology enhances rather than replaces deep learning.
This presentation is grounded in the latest neuroscience but designed for the decisions school leaders face every day: How should we integrate AI? What does effective teaching actually look like at the neural level? And how do we build minds that are both tech-savvy and deeply knowledgeable?
Outline:
1. Inside the learning brain — engrams, schemata, and how knowledge physically forms
2. The two memory systems — why the declarative-to-procedural shift is the key to expertise
3. Prediction errors — the brain's learning signal, and why it requires internal knowledge
4. The cognitive offloading trap — the Flynn Effect reversal and what went wrong
5. Lessons from around the world — Taiwan, New Zealand, Singapore, and beyond
6. AI in the classroom — metacognitive laziness and how to design for real learning
7. What school leaders can do — practical strategies that align with brain architecture