My research explores how young children come to know about the world around them. The work is informed by the "theory theory" -- the idea that children develop and change intuitive theories of the world in much the way that scientists do. Most recently, we have been concentrating on young children's causal knowledge and causal learning across domains,, including physical, biological and psychological knowledge. In collaboration with computer scientists, we are using the Bayes Net formalism to help explain how children are able to learn causal structure from patterns of data, and we have demonstrated that young children have much more powerful causal learning mechanisms than was previously supposed.
Professor Gopnik's Homepage Includes a publications list of downloadable papers.