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Article de revue:
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ID no. (ISBN etc.): 0096-3445
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Clé de citation BibTeX: Sloutsky2004
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Sloutsky, V. M., & Fisher, A. V. (2004). Induction and categorization in young children: A similarity-based model. Journal of Experimental Psychology: General, 133(2), p. p166–188.
Ajoutée par: Sterenn Audo 2008-01-08 16:57:01 Dernièrement modifiée par: Sterenn Audo 2008-01-08 16:58:14
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Catégories: Catégorisation, Full text, Raisonnement
Descripteurs: artificial labels, categorization task, Classification (Cognitive Process), Cognitive Processes, induction task, Inductive Deductive Reasoning, INFERENCE, Judgment, linguistic labels, LINGUISTICS, MEMORY, Naming, perceptual information, real labels, Recognition (Learning), recognition memory tasks, similarity judgment, similarity-based model, Stimulus Similarity, young children
Auteurs: Fisher, Sloutsky
Collection: Journal of Experimental Psychology: General
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Nombre de vues: 369
Popularité: 33.48%
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Résumé
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. (PsycINFO Database Record (c) 2006 APA, all rights reserved)(from the journal abstract)
Ajoutée par: Sterenn Audo Dernièrement modifiée par: Sterenn Audo
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Idées
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Ajoutée par: Sterenn Audo
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