Abstract

The authors present a similarity-based model of induction and categorization in young children (SINC). The model suggests that (a) linguistic labels contribute to the perceived similarity of compared entities and (b) categorization and induction are a function of similarity computed over perceptual information and linguistic labels. The model also predicts young children’s similarity judgment, induction, and categorization performance under different stimuli and task conditions. Predictions of the model were tested and confirmed in 6 experiments, in which 4- to 5-year-olds performed similarity judgment, induction, and categorization tasks using artificial and real labels (Experiments 1–4) and recognition memory tasks (Experiments 5A and 5B). Results corroborate the similarity-based account of young children’s induction and categorization, and they support both qualitative and quantitative predictions of the model. Inductive inference, or extending knowledge from known to novel instances, is ubiquitous in human cognition. For example, if one learned that a particular lion has a certain neurotransmitter in its brain, one would expect another lion also to have this neurotransmitter, even if one did not have factual knowledge of the brain

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