The Knowledge Engineer as Student: Metacognitive Bases for Asking Good Questions

Abstract

Knowledge engineers are efficient, active learners. They systematically approach domains and acquire knowledge to solve routine, practical problems. By modeling their methods, we may develop a basis for teaching other students how to direct their own learning. In particular, a knowledge engineer is good at detecting gaps in knowledge base and asking focused questions to improve an expert system's performance. This ability stems from domain. General knowledge, about: problem-solving procedures, the categorization of routine problem-solving knowledge, and domain and task differences. This paper studies these different forms of metaknowledge, and illustrates its incorporation in an intelligent tutoring system. A model of learning is presented that describes how the knowledge engineer detects problem solving failures and tracks them back to gaps in domain knowledge, which are then reformulated as questions to ask a teacher. We describe how this model of active learning is being developed and tested in a knowledge acquisition program for an expert system. Keywords: Learning, Knowledge engineering, Knowledge acquisition, Metaknowledge.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1987
Accession Number
ADA186995

Entities

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  • William J. Clancey

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  • Stanford University

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  • Biomedical

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  • Acquisition
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Bacterial Infections
  • Cognitive Science
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  • Educational Technology
  • Expert Systems
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