Non-Bayesian noun generalization in 3- to 5-year-old children: Probing the role of prior knowledge in the suspicious coincidence effect

Gavin W Jenkins, Larissa K Samuelson (Lead Author), Jodi R Smith, John P Spencer

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)


It is unclear how children learn labels for multiple overlapping categories such as "Labrador," "dog," and "animal." Xu and Tenenbaum (2007a) suggested that learners infer correct meanings with the help of Bayesian inference. They instantiated these claims in a Bayesian model, which they tested with preschoolers and adults. Here, we report data testing a developmental prediction of the Bayesian model-that more knowledge should lead to narrower category inferences when presented with multiple subordinate exemplars. Two experiments did not support this prediction. Children with more category knowledge showed broader generalization when presented with multiple subordinate exemplars, compared to less knowledgeable children and adults. This implies a U-shaped developmental trend. The Bayesian model was not able to account for these data, even with inputs that reflected the similarity judgments of children. We discuss implications for the Bayesian model, including a combined Bayesian/morphological knowledge account that could explain the demonstrated U-shaped trend.

Original languageEnglish
Pages (from-to)268-306
Number of pages39
JournalCognitive Science
Issue number2
Publication statusPublished - Mar 2015


  • Word learning
  • Bayesian modeling
  • Categorization
  • Vocabulary development
  • Similarity judgment

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