Literature DB >> 12480477

Are there representational shifts during category learning?

Mark K Johansen1, Thomas J Palmeri.   

Abstract

Early theories of categorization assumed that either rules, or prototypes, or exemplars were exclusively used to mentally represent categories of objects. More recently, hybrid theories of categorization have been proposed that variously combine these different forms of category representation. Our research addressed the question of whether there are representational shifts during category learning. We report a series of experiments that tracked how individual subjects generalized their acquired category knowledge to classifying new critical transfer items as a function of learning. Individual differences were observed in the generalization patterns exhibited by subjects, and those generalizations changed systematically with experience. Early in learning, subjects generalized on the basis of single diagnostic dimensions, consistent with the use of simple categorization rules. Later in learning, subjects generalized in a manner consistent with the use of similarity-based exemplar retrieval, attending to multiple stimulus dimensions. Theoretical modeling was used to formally corroborate these empirical observations by comparing fits of rule, prototype, and exemplar models to the observed categorization data. Although we provide strong evidence for shifts in the kind of information used to classify objects as a function of categorization experience, interpreting these results in terms of shifts in representational systems underlying perceptual categorization is a far thornier issue. We provide a discussion of the challenges of making claims about category representation, making reference to a wide body of literature suggesting different kinds of representational systems in perceptual categorization and related domains of human cognition.

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Year:  2002        PMID: 12480477     DOI: 10.1016/s0010-0285(02)00505-4

Source DB:  PubMed          Journal:  Cogn Psychol        ISSN: 0010-0285            Impact factor:   3.468


  28 in total

1.  Measures of similarity in models of categorization.

Authors:  Tom Verguts; Eef Ameel; Gert Storms
Journal:  Mem Cognit       Date:  2004-04

2.  As easy to memorize as they are to classify: the 5-4 categories and the category advantage.

Authors:  Mark Blair; Don Homa
Journal:  Mem Cognit       Date:  2003-12

3.  Temporal dynamics of generalization and representational distortion.

Authors:  Matthew G Wisniewski; Barbara A Church; Eduardo Mercado
Journal:  Psychon Bull Rev       Date:  2010-12

4.  Formation of category representations.

Authors:  A J Wills; Malia Noury; Nicholas J Moberly; Matthew Newport
Journal:  Mem Cognit       Date:  2006-01

5.  Strategy shifts in classification skill acquisition: does memory retrieval dominate rule use?

Authors:  Lyle E Bourne; Alice F Healy; James A Kole; Susan M Graham
Journal:  Mem Cognit       Date:  2006-06

6.  Modeling the word recognition data of Vitevitch and Luce (1998): is it ARTful?

Authors:  Mark A Pitt; Jay I Myung; Nicholas Altieri
Journal:  Psychon Bull Rev       Date:  2007-06

7.  Modelling individual difference in visual categorization.

Authors:  Jianhong Shen; Thomas J Palmeri
Journal:  Vis cogn       Date:  2016-11-10

8.  Use of evidence in a categorization task: analytic and holistic processing modes.

Authors:  Alberto Greco; Stefania Moretti
Journal:  Cogn Process       Date:  2017-08-14

9.  Logical-rule models of classification response times: a synthesis of mental-architecture, random-walk, and decision-bound approaches.

Authors:  Mario Fific; Daniel R Little; Robert M Nosofsky
Journal:  Psychol Rev       Date:  2010-04       Impact factor: 8.934

10.  Individual differences in category learning: memorization versus rule abstraction.

Authors:  Jeri L Little; Mark A McDaniel
Journal:  Mem Cognit       Date:  2015-02
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