Probabilistic versus heuristic accounts of explanation in children: Evidence from a latent scope bias

Like scientists, children must find ways to explain causal systems in the world. The Bayesian approach to cognitive development holds that children evaluate explanations by applying a normative set of statistical learning and hypothesis-testing mechanisms to the evidence they observe. Here, we argue for certain supplements to this approach. In particular, we demonstrate in two studies that children, like adults, have a robust latent scope bias that conflicts with the laws of probability. When faced with two explanations equally consistent with observed data, where one explanation made an unverified prediction, children consistently preferred the explanation that did not make this prediction (Experiment 1). The bias can be overridden by strong prior odds, indicating that children can integrate cues from multiple sources of evidence (Experiment 2). We argue that children, like adults, rely on heuristics for making explanatory judgments which often lead to normative responses, but can lead to systematic error.