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Causal learning from probabilistic events in 24‐month‐olds: an action measure
Author(s) -
Waismeyer Anna,
Meltzoff Andrew N.,
Gopnik Alison
Publication year - 2015
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/desc.12208
Subject(s) - psychology , measure (data warehouse) , probabilistic logic , cognitive psychology , action (physics) , statistical learning , developmental psychology , artificial intelligence , computer science , physics , quantum mechanics , database
How do young children learn about causal structure in an uncertain and variable world? We tested whether they can use observed probabilistic information to solve causal learning problems. In two experiments, 24‐month‐olds observed an adult produce a probabilistic pattern of causal evidence. The toddlers then were given an opportunity to design their own intervention. In Experiment 1, toddlers saw one object bring about an effect with a higher probability than a second object. In Experiment 2, the frequency of the effect was held constant, though its probability differed. After observing the probabilistic evidence, toddlers in both experiments chose to act on the object that was more likely to produce the effect. The results demonstrate that toddlers can learn about cause and effect without trial‐and‐error or linguistic instruction on the task, simply by observing the probabilistic patterns of evidence resulting from the imperfect actions of other social agents. Such observational causal learning from probabilistic displays supports human children's rapid cultural learning.