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The quality of expertise: implications of expert-novice differences for knowledge acquisition

Author:

Marianne LaFranceAuthors Info & Claims

ACM SIGART Bulletin, Issue 108

Pages 6 - 14

https://doi.org/10.1145/63266.63267

Published: 01 April 1989 Publication History

Abstract

Recognizing that the knowledge of experts is qualitatively and not just quantitatively different from the knowledge of novices is an important pre-requisite to conducting effective knowledge acquisition. This article reviews the current cognitive research on expertise and proposes seven ways in which the knowledge of experts is different from the knowledge of novices, including such aspects as underlying schema, goal-orientation, practical focus, categorical chunking, cognitive complexity, automaticity of expert problem solving, and finally, the episodic nature of expert memory. The paper concludes with an outline of several implications that follow from this research including showing why knowledge acquisition will remain problematic without knowledge of experts' knowledge, as well as making a number of specific suggestions for those who need to elicit expert knowledge for knowledge-based systems.

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Index Terms

The quality of expertise: implications of expert-novice differences for knowledge acquisition
1. Computing methodologies
  1. Machine learning
    1. Learning settings
2. Information systems
  1. Information systems applications
    1. Decision support systems
      1. Expert systems

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Published In

cover image ACM SIGART Bulletin

ACM SIGART Bulletin Just Accepted

Special issue on knowledge acquisition

April 1989

205 pages

ISSN:0163-5719

DOI:10.1145/63266

Editor:
Chris Westphal
Univ. of Southern California, Los Angeles

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Copyright © 1989 Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 01 April 1989

Published in SIGAI , Issue 108

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