Explaining Influences Children's Reliance on Evidence and Prior Knowledge in Causal Induction

Explaining Influences Children’s Reliance on Evidence and Prior Knowledge in Causal Induction Caren M. Walker, Joseph Jay Williams, Tania Lombrozo, & Alison Gopnik (caren.walker@berkeley.edu, joseph_williams@berkeley.edu, lombrozo@berkeley.edu, gopnik@berkeley.edu) Department of Psychology, University of California, Berkeley, 3210 Tolman Hall, Berkeley, CA 94720 Abstract In two studies, we examine how prompting 5- and 6-year-olds to explain observed outcomes influences causal learning. In Study 1, children were presented with data consistent with two causal regularities. Explainers outperformed controls in generalizing the regularity that accounted for more observations. In Study 2, this regularity was pitted against an alternative that accounted for fewer observations but was consistent with prior knowledge. Explainers were less likely than controls to generalize the regularity that accounted for more observations. These findings suggest that explaining drives children to favor causal regularities that they expect to generalize, where current observations and prior knowledge both provide cues. Keywords: Explanation; cognitive development; causal reasoning; prior knowledge; generalization; abduction. Since Piaget, researchers have regarded children’s explanations as a window into cognitive development, revealing children’s understanding of the world (e.g., Keil, 2006). More recently, however, the very process of seeking, generating, and evaluating explanations has additionally been proposed as a powerful mechanism for learning and generalization, scaffolding knowledge acquisition and contributing to theory change (e.g., Chi, DeLeeuw, Chiu, & LaVancher, 1994; Lombrozo, 2006; Wellman, 2011). Here we investigate the role of explanation in young children’s causal learning, focusing on whether and how explaining influences the relative contributions of observed evidence and currently-held theories (“prior knowledge”). Discovering the underlying causal structure in the world is one of the major inductive problems that young learners face during development. By 5 years of age, children have already developed abstract, coherent representations of causal relationships in a variety of domains (e.g., Carey, 1985; Gelman & Wellman, 1991). The acquisition of this causal knowledge is supported by powerful learning mechanisms that allow children (and adults) to infer novel causal relationships from patterns of evidence and prior beliefs (e.g., Gopnik, Glymour, Sobel, Schulz, Kushnir, & Danks, 2004; Griffiths, Sobel, Tenenbaum, & Gopnik, 2011). For example, 5-year-old children can effectively track covariational evidence to identify a novel cause, but require stronger evidence to endorse a cause that conflicts with their prior beliefs than one consistent with those beliefs (Schulz, Bonawitz, & Griffiths, 2007). These findings reveal that children integrate current observations with prior beliefs in the process of learning and revising their causal knowledge. Here we propose that explaining may play a role in this integration, by influencing the relative contributions of evidence and prior knowledge – that is, the extent to which learners revise their beliefs in light of their observations and prior commitments. A first possibility, which we call the evidence hypothesis, is that explaining a set of observations directs learners to update their beliefs in light of those observations. As a result, explaining will lead learners to change their beliefs more than they would have in the absence of explaining. This might be expected, for example, if explanation boosts children’s engagement with a task (Siegler, 2002), thereby making them more responsive to feedback and less likely to disregard relevant observations. Consistent with this possibility, a variety of studies have found that presenting young children with feedback is less effective as a means to changing their beliefs than having them explain as well (e.g., Wellman, 2011). More indirect support comes from the fact that explaining can direct children towards anomalous data, which conflicts with their prior beliefs and may therefore signal a need for belief revision (e.g., Legare, 2010; Legare, Gelman, & Wellman, 2010). In sum, the evidence hypothesis predicts that explaining should make children more responsive to observed data, leading to greater revision in current beliefs. A second possibility, which we call the prior knowledge hypothesis, is that engaging in explanation invokes learners’ currently-held theories, leading them to revise their beliefs less than they might have in the absence of explanation. In line with this hypothesis, several researchers have proposed that explaining encourages learners to accommodate what they are trying to explain in the context of what they already know (e.g., Chi et al., 1994; Lombrozo, 2006). Explaining could thus lead children to favor hypotheses consistent with prior knowledge, even when those hypotheses might not have been entertained or preferred on the basis of evidence alone. Kuhn and Katz (2009) further suggest that by encouraging learners to consider why something is the case, explaining can lead them to discount observed evidence altogether. From this perspective, learners who explain could be less inclined towards hypotheses that simply match current evidence, either because they weight prior beliefs more heavily or because they underweight current evidence. A final possibility is that explaining does not affect the role of evidence or prior knowledge uniformly across contexts. Instead, explaining could change the criteria employed in evaluating evidence and prior knowledge in the course of learning, resulting in greater belief revision under some conditions and less belief revision under others. The version of this possibility that we explore here is the