Literature DB >> 11820746

Consistent contrast aids concept learning.

D Billman1, D Dávila.   

Abstract

We suggest that coherence among concepts and correspondence between concepts and the world are important in concept learning. We identify one aspect of coherence, consistent contrast, and investigate its role in supervised concept learning. Concepts that contrast consistently carry information about the same attributes across the concepts within a contrast set. Concepts that contrast inconsistently predict and are predicted by values of different attributes. Experiment 1 revealed a large advantage for consistent contrast in learning and generalization. Experiment 2 pitted similarity against consistency and still revealed an advantage of consistency. Experiment 2 also broadened the range of tasks considered to include inductions about novel categories and subjects' category descriptions. We discuss relations to theories of concept learning, to attentional mechanism, and to alignability, and we suggest practical implications.

Mesh:

Year:  2001        PMID: 11820746     DOI: 10.3758/bf03195764

Source DB:  PubMed          Journal:  Mem Cognit        ISSN: 0090-502X


  15 in total

1.  Effect of causal structure on category construction.

Authors:  W K Ahn
Journal:  Mem Cognit       Date:  1999-11

2.  Learning categories composed of varying instances: the effect of classification, inference, and structural alignment.

Authors:  T Yamauchi; A B Markman
Journal:  Mem Cognit       Date:  2000-01

3.  ALCOVE: an exemplar-based connectionist model of category learning.

Authors:  J K Kruschke
Journal:  Psychol Rev       Date:  1992-01       Impact factor: 8.934

4.  Alignment and category learning.

Authors:  M E Lassaline; G L Murphy
Journal:  J Exp Psychol Learn Mem Cogn       Date:  1998-01       Impact factor: 3.051

5.  Unsupervised concept learning and value systematicity: a complex whole aids learning the parts.

Authors:  Dorrit Billman; James Knutson
Journal:  J Exp Psychol Learn Mem Cogn       Date:  1996-03       Impact factor: 3.051

6.  Rule-plus-exception model of classification learning.

Authors:  R M Nosofsky; T J Palmeri; S C McKinley
Journal:  Psychol Rev       Date:  1994-01       Impact factor: 8.934

7.  The locus of knowledge effects in concept learning.

Authors:  G L Murphy; P D Allopenna
Journal:  J Exp Psychol Learn Mem Cogn       Date:  1994-07       Impact factor: 3.051

8.  Correlated symptoms and simulated medical classification.

Authors:  D L Medin; M W Altom; S M Edelson; D Freko
Journal:  J Exp Psychol Learn Mem Cogn       Date:  1982-01       Impact factor: 3.051

9.  Induction from a single instance: formation of a novel category.

Authors:  J F Macario; E F Shipley; D O Billman
Journal:  J Exp Child Psychol       Date:  1990-10

10.  Rules and exemplars in category learning.

Authors:  M A Erickson; J K Kruschke
Journal:  J Exp Psychol Gen       Date:  1998-06
View more
  1 in total

1.  Category learning in the context of co-presented items.

Authors:  Janet K Andrews; Kenneth R Livingston; Kenneth J Kurtz
Journal:  Cogn Process       Date:  2010-11-14
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.