Children in the earliest stages of life behave like intuitive scientists - observing the world, forming theories about how the world works, predicting possible consequences of their theories, and intervening to test their predictions. What is not clear is how these 'intuitive scientists' go about deciding when and which exploration opportunities to pursue. This research investigates whether children are motivated to explore when there is high expectation in 'Information Gain' i.e., 'the degree to which a learner can expect to update her beliefs' and examines whether exploration is sensitive to variation in factors that will influence information gain. Identifying the factors that influence efficient active learning in early childhood is important because it could lead to understanding broader developmental differences in drive for learning, with direct consequences for the development of informal and formal educational practices. Extending these findings to under-represented populations may help us to develop early interventions that improve the lives of these populations.Several sets of studies are planned. One set will examine whether children track probability information and are able to use expected reward to drive decisions. The second set of studies investigate whether children are motivated to explore an object longer and more variably when they believe learning about it will be more difficult (have higher information gain). The remaining experiments examine children's choices between two uncertain outcomes. One set of studies assess whether children consider the effects of evidence prior to exploring events with potential information gain. The second set of studies looks at information gain in the context of children's beliefs - specifically, whether children who are transitioning between beliefs are more motivated (as compared to children who are more confidently rooted in their current beliefs) to seek information that will help them learn.
|Effective start/end date||8/15/16 → 7/31/19|
- National Science Foundation (NSF)