Literature DB >> 10946366

Category learning with minimal prior knowledge.

A S Kaplan1, G L Murphy.   

Abstract

In 6 experiments, the authors examined the use of prior knowledge in category learning. Previous studies of the effects of knowledge on category learning have used categories in which knowledge was related to all of the category's features. However, people's knowledge of real-world categories often consists of many "rote" features that are not related to their prior knowledge. Five experiments found that even minimal prior knowledge (1 knowledge-relevant feature and 5 rote features per exemplar) can facilitate category learning. Posttests revealed that although the knowledge aided learning, subjects also acquired the rote features that were not related to knowledge, contradicting predictions of an attentional explanation of the knowledge effect. The results of Experiment 6 suggested that subjects attempt to link even rote features to their knowledge.

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Year:  2000        PMID: 10946366     DOI: 10.1037//0278-7393.26.4.829

Source DB:  PubMed          Journal:  J Exp Psychol Learn Mem Cogn        ISSN: 0278-7393            Impact factor:   3.051


  13 in total

1.  Putting together prior knowledge, verbal arguments, and observations in category learning.

Authors:  E Heit
Journal:  Mem Cognit       Date:  2001-09

Review 2.  A knowledge-resonance (KRES) model of category learning.

Authors:  Bob Rehder; Gregory L Murphy
Journal:  Psychon Bull Rev       Date:  2003-12

3.  Subtyping as a knowledge preservation strategy in category learning.

Authors:  Lewis Borr; Gregory Murphy
Journal:  Mem Cognit       Date:  2007-04

4.  Blocking in category learning.

Authors:  Lewis Bott; Aaron B Hoffman; Gregory L Murphy
Journal:  J Exp Psychol Gen       Date:  2007-11

5.  Prior knowledge enhances the category dimensionality effect.

Authors:  Aaron B Hoffman; Harlan D Harris; Gregory L Murphy
Journal:  Mem Cognit       Date:  2008-03

6.  How prior knowledge affects selective attention during category learning: an eyetracking study.

Authors:  Shinwoo Kim; Bob Rehder
Journal:  Mem Cognit       Date:  2011-05

7.  Category vs. Object Knowledge in Category-based Induction.

Authors:  Gregory L Murphy; Brian H Ross
Journal:  J Mem Lang       Date:  2010-07-01       Impact factor: 3.059

8.  Observation versus classification in supervised category learning.

Authors:  Kimery R Levering; Kenneth J Kurtz
Journal:  Mem Cognit       Date:  2015-02

9.  The science of cycology: failures to understand how everyday objects work.

Authors:  Rebecca Lawson
Journal:  Mem Cognit       Date:  2006-12

10.  Searching for Category-Consistent Features: A Computational Approach to Understanding Visual Category Representation.

Authors:  Chen-Ping Yu; Justin T Maxfield; Gregory J Zelinsky
Journal:  Psychol Sci       Date:  2016-05-03
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