The development of causal categorization

Brett K. Hayes, Bob Rehder

Research output: Contribution to journalArticlepeer-review

Abstract

Two experiments examined the impact of causal relations between features on categorization in 5- to 6-year-old children and adults. Participants learned artificial categories containing instances with causally related features and noncausal features. They then selected the most likely category member from a series of novel test pairs. Classification patterns and logistic regression were used to diagnose the presence of independent effects of causal coherence, causal status, and relational centrality. Adult classification was driven primarily by coherence when causal links were deterministic (Experiment 1) but showed additional influences of causal status when links were probabilistic (Experiment 2). Children's classification was based primarily on causal coherence in both cases. There was no effect of relational centrality in either age group. These results suggest that the generative model (Rehder, 2003a) provides a good account of causal categorization in children as well as adults.

Original languageEnglish (US)
Pages (from-to)1102-1128
Number of pages27
JournalCognitive Science
Volume36
Issue number6
DOIs
StatePublished - Aug 2012

Keywords

  • Categorization
  • Causal reasoning
  • Cognitive development

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Artificial Intelligence

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