2-030 - The answer is out there: How do children find solutions to difficult problems?

Session Type: Paper Symposium

Integrative Statement

From causal learning to categorization, children solve challenging inference problems in their daily lives with apparent ease. Yet, in all but the simplest settings, the number of possible solutions to these problems is enormous. Children cannot evaluate all of these possibilities (Griffiths et al., 2015), so they must find efficient ways to narrow the space of hypotheses that they evaluate. How do children and adults focus their search?

Paper 1 demonstrates that children rely on contextual information in deciding how variably to explore potential causes on a novel toy. Children who are primed with a "difficult" initial task engage in more variable search when exploring a subsequent toy. Paper 2 explores whether active hypothesis testing improves children’s relational learning relative to passive observation, and surprisingly discovers that this is not always the case. Paper 3 examines how adults and children search for causal hypotheses, with results suggesting that adults have difficulty when the correct causal structure is distant from their initial hypothesis, while children may explore a wider-ranging space of possibilities and be more likely to identify the correct causal structure when it is far from their initial hypothesis. The discussant will comment on children's search for hypotheses and explanations, as well as developmental differences, in a broader context that includes research on language development and neural plasticity. Together, these findings shed light on the advantages -- and pitfalls – in searching for explanations in a complex environment.

Sub Unit

• Cognitive Processes

Chair

• Daphna Buchsbaum, University of Toronto

Discussant

• Amy Finn, University of Toronto

Individual Presentations

• This puzzle is hard! Difficulty of one task affects children’s exploration on a second task - Presenting Author: Tiffany Doan, University of Waterloo; Amanda Castro, Rutgers University - Newark; Elizabeth Bonawitz, Rutgers University; Stephanie Denison, University of Waterloo

• Observational learning vs. active hypothesis testing in relational categorization - Presenting Author: Micah B Goldwater, University of Sydney

• Searching for causal explanations: Garden paths and developmental differences - Presenting Author: Christopher G Lucas, University of Edinburgh; Erik Herbst, University of Toronto; Kay Otsubo, University of Toronto; Daphna Buchsbaum, University of Toronto