Stanford Psychology Podcast 176 - Elizabeth Bonawitz: How to Have Fun While Studying How Children Learn so Much From so Little
May 30, 2026
Elizabeth Bonawitz, Professor of Learning Sciences at Harvard who studies curiosity, play, and how children learn. She discusses why children reveal how humans learn so much from so little. They cover shifts toward computational models, how prior beliefs shape classroom instruction, and the role of play, humor, and neuroscience methods in studying development.
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Young Children Hold Rich Intuitive Theories
- Children build rich intuitive theories quickly, explaining and predicting across domains like physics, biology, and mind.
- By age four they can reason about desires, beliefs, forces, growth, and intervene in principled ways, making them ideal subjects to study how humans learn so much from so little.
Bayesian View Reconciles Stubborn and Flexible Learning
- Bayesian models explain why children sometimes seem stubborn and other times rapidly update beliefs by combining priors with data likelihoods.
- Strong priors plus ambiguous data yield intransigence, while weak priors plus clear evidence yield fast revision, resolving prior debates about learning flexibility.
Adult Stubbornness Can Be Rational
- Adults' greater data history and cognitive habits make intransigence often rational, not merely stubbornness.
- Having seen extensive confirming evidence, limiting hypotheses, and using system 1 shortcuts makes adults more likely to explain away anomalies than revise core beliefs.
