We propose a new version of the “theory theory” grounded in the computational framework
of probabilistic causal models and Bayesian learning. Probabilistic models allow a …

Few phenomena in childhood are as compelling—and mystifying—as play. We review five
proposals about the relationship between play and development. We believe each captures …

We study GPT-3, a recent large language model, using tools from cognitive psychology.
More specifically, we assess GPT-3's decision-making, information search, deliberation, and …

Recent work has argued that curiosity can improve learning. However, these studies also
leave open the possibility that being on the verge of knowing can itself induce curiosity. We …

Probabilistic models of expected information gain require integrating prior knowledge about
causal hypotheses with knowledge about possible actions that might generate data relevant …

It is widely recognized that language plays a key role in the transmission of human culture,
but relatively little is known about the mechanisms by which language simultaneously …

Children's causal learning has been characterized as a rational process, in which children
appropriately evaluate evidence from their observations and actions in light of their existing …

We look at the effect of evidence and prior beliefs on exploration, explanation and learning.
In Experiment 1, we tested children both with and without differential prior beliefs about …

Analogies between scientific theories and children's folk theories have been central to the
study of cognitive development for decades. In support of the comparison, numerous studies …

Two studies examined the specificity of effects of explanation on learning by prompting 3-to
6-year-old children to explain a mechanical toy and comparing what they learned about the …