The Knowledge Engineer as Student: Metacognitive bases for asking good questions

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Citation: William J. Clancey. (1987) The Knowledge Engineer as Student: Metacognitive bases for asking good questions. In KSL-87-12, 1987.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author William J. Clancey
title The Knowledge Engineer as Student: Metacognitive bases for asking good questions
number KSL-87-12
institution Knowledge Systems, AI Laboratory
address New York
year 1987
Bibtex more
note STAN-CS-87-1183.
publisher Springer-Verlag
Access Paper
abstract Knowledge engineers are efficient, active learners. By modeling their methods for approaching new domains and acquiring the knowledge to solve routine, practical problems, 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 a knowledge base and asking focused questions to improve an expert system's performance. This ability stems from domain-general knowledge about problem-solving procedures, how routine problem-solving knowledge is categorized, and domain and task differences. This paper studies different forms of this metaknowledge, and illustrates how it can be incorporated in an intelligent tutoring system. A model of learning is presented which 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.

KSL Technical Report ID: KSL-87-12
Facts about The Knowledge Engineer as Student: Metacognitive bases for asking good questionsRDF feed
Abstract Knowledge engineers are efficient, active … Knowledge engineers are efficient, active learners. By modeling their methods for approaching new domains and acquiring the knowledge to solve routine, practical problems, 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 a knowledge base and asking focused questions to improve an expert system's performance. This ability stems from domain-general knowledge about problem-solving procedures, how routine problem-solving knowledge is categorized, and domain and task differences. This paper studies different forms of this metaknowledge, and illustrates how it can be incorporated in an intelligent tutoring system. A model of learning is presented which 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. acquisition program for an expert system.
Address New York  +
Author William J. Clancey  +
Bibtype techreport  +
Has author William J. Clancey  +
Has identifier KSL-87-12  +
Has publishing details 1987  +
Has title The Knowledge Engineer as Student: Metacognitive bases for asking good questions  +
Has where published KSL-87-12  +
Has year 1987  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-87-12  +
Note STAN-CS-87-1183.
Number KSL-87-12  +
Process note GOOGLE  +
Publisher Springer-Verlag  +
Title The Knowledge Engineer as Student: Metacognitive bases for asking good questions  +
Year 1987  +
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