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Preschool children learn about causal structure from conditional interventions
Author(s) -
Schulz Laura E.,
Gopnik Alison,
Glymour Clark
Publication year - 2007
Publication title -
developmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.801
H-Index - 127
eISSN - 1467-7687
pISSN - 1363-755X
DOI - 10.1111/j.1467-7687.2007.00587.x
Subject(s) - causal structure , causal model , psychology , psychological intervention , causal reasoning , intervention (counseling) , cognitive psychology , causal chain , bayes' theorem , conditional probability , developmental psychology , causal decision theory , cognition , bayesian probability , artificial intelligence , computer science , neuroscience , mathematics , statistics , physics , business decision mapping , quantum mechanics , decision support system , psychiatry , decision engineering
The conditional intervention principle is a formal principle that relates patterns of interventions and outcomes to causal structure. It is a central assumption of experimental design and the causal Bayes net formalism. Two studies suggest that preschoolers can use the conditional intervention principle to distinguish causal chains, common cause and interactive causal structures even in the absence of differential spatiotemporal cues and specific mechanism knowledge. Children were also able to use knowledge of causal structure to predict the patterns of evidence that would result from interventions. A third study suggests that children's spontaneous play can generate evidence that would support such accurate causal learning.