Causal Learning in Children

University Of California-Berkeley, Berkeley CA

Investigators

Abstract

In the first few years of life, children learn a great deal about the causal structure of the world around them; they learn how some events make other events happen. This knowledge is reflected in children's everyday "theories" of the world. How does this learning take place? This research program will investigate the underlying mechanisms for causal learning in children. In particular, the research will explore how children use information about contingencies between events, such as the fact that one event always follows another event, to draw conclusions about causal relationships. It will investigate how children learn about inhibitory causes, interactive causes and hidden, unobserved causes. This work is informed by recent work in computer science and statistics that shows how computers can make accurate causal inferences. This work should have significant broader impact for educational practice. Causal relationships play a crucial role in scientific knowledge. If we understand children's basic natural causal learning mechanisms, we can use this understanding to help teach science more effectively. Similarly, this research has impact for studies of developmental disabilities such as autism and mental retardation. There is reason to think that children with these syndromes may have particular difficulty with causal learning, and understanding natural causal learning may help us understand and remedy these difficulties.