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Knowledge acquisition as a constructive modeling activity
Author(s) -
Ford Kenneth M.,
Bradshaw Jeffrey M.,
AdamsWebber Jack R.,
Agnew Neil M.
Publication year - 1993
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
ISBN - 0-471-59368-0
DOI - 10.1002/int.4550080103
Subject(s) - constructive , knowledge acquisition , computer science , knowledge management , domain knowledge , subject matter expert , bridge (graph theory) , construct (python library) , exploit , knowledge engineering , process (computing) , bridging (networking) , perspective (graphical) , body of knowledge , knowledge integration , domain (mathematical analysis) , artificial intelligence , expert system , medicine , computer network , mathematical analysis , computer security , mathematics , programming language , operating system
Knowledge acquisition is a constructive modeling process, not simply a matter of “expertise transfer.” Consistent with this perspective, we advocate knowledge acquisition practices and tools that facilitate active collaboration between expert and knowledge engineer, that exploit a serviceable theory in their application, and that support knowledge‐based system development from a life‐cycle perspective. A constructivist theory of knowledge is offered as a plausible theoretical foundation for knowledge acquisition and as an effective practical approach to the dynamics of modeling. In this view, human experts construct knowledge from their own personal experiences while interacting with their social constituencies (e.g., supervisors, colleagues, clients patients) in their niche of expertise. Knowledge acquisition is presented as a cooperative enterprise in which the knowledge engineer and expert collaborate in constructing an explicit model of problem solving in a specific domain. From this perspective, the agenda for the knowledge acquisition research community includes developing tools and methods to aid experts in their efforts to express, elaborate, and improve their models of the domain. This functional view of expertise helps account for several problems that typically arise in practical knowledge acquisition projects, many of which stem directly from the inadequacies of representations used at various stages of system development. to counter these problems, we emphasize the use of mediating representations as a means of communication between expert and knowledge engineer, and intermediate representations to help bridge the gap between the mediating representations themselves, as well as between the mediating representations and a particular implementation formalism. © 1993 John Wiley & Sons, Inc.