How can the science of learning inform the design of artificial intelligence — and how can AI, in turn, advance the way we learn?
📅 Date: November 6, 2025
🕣 Time: 8:30 – 9:30 A.M. (EST)
📍 Format: Online (Zoom link TBA)
📍 Hosted by: MIT AI Alumni Group
In this MIT AI Alumni Group online session, Professor Sanjay Sarma, former Vice President for Open Learning at MIT, will draw on his influential book Grasp: The Science Transforming How We Learn — together with his ongoing research in AI and educational innovation — to explore how a “human + machine” paradigm could reimagine teaching, learning, and the delivery of education at scale.
Grounded in evidence from neuroscience, cognitive psychology, and large-scale learning systems, Professor Sarma will examine:
- How forgetting and retrieval practice are not failures but essential mechanisms of deep learning — and how AI systems can be designed to leverage them.
- The role of spacing, interleaving, and testing in optimizing retention, and how AI tutors could dynamically schedule reviews, quizzes, and challenges tailored to each learner.
- How schools and universities often operate contrary to the brain’s natural learning rhythms, and how adaptive AI environments can bridge that gap.
- The concept of “outperformance” — how humans and institutions can learn to identify and surpass AI’s mistakes rather than defer entirely to them.
- New proposals in educational design, such as the Affordable New Educational Institution (NEI) framework, which advocates modular credentials, leaner research models, and AI-infused infrastructures.
- Insights from MIT’s Open Learning initiatives — including MicroMasters, MITx, and MIT Bootcamps — and what the next frontier may hold for democratizing high-quality education worldwide.
Join us for a thought-provoking discussion on how learning science, institutional innovation, and AI can combine to create more effective, equitable, and scalable education models for the future.
