Sinopsis:
Knowledge-Based Tutoring describes the advantages and difficulties of adapting an expert system for use in teaching and problem solving. In this case the well-known rule-based expert system, MYCIN, which has been widely used in medical artificial intelligence to do infectious disease diagnosis and therapy selection, is used as a base for the instructional program GUIDON. MYCIN's rules are interpreted by GUIDON in order to evaluate a student's problem solving and provide assistance as the student gathers information about a patient and makes a diagnosis. The book describes what GUIDON does, how it is constructed, and the benefits and limitations of its design.
This is the first attempt to adapt a rule base for tutoring and opens the door to what will most likely be a dramatic growth in interest in the use of expert systems for teaching. Clancey points out that it is easy to build an expert system that "works," but difficult to build one that makes knowledge explicit so that it can be taught. His dramatic demonstration of the separation of tutoring from subject matter knowledge will be of particular interest to researchers who are developing traditional computer-aided instruction programs.
Clancey's program will also prove useful to cognitive science researchers in psychology and education who are interested in learning about AI techniques for explanation and student modeling, and to the many people who are currently developing computer-aided instruction programs. The book contains enough technical details for the work to be replicated, but has been generalized so the methods and lessons can be applied to other knowledge representations.
William J. Clancey is a Senior Research Associate, at the Knowledge Systems Laboratory, Computer Science Department, Stanford University. Knowledge-Based Tutoring is included in The MIT Press Series in Artificial Intelligence, edited by Patrick Henry Winston and Michael Brady.
Reseña del editor:
"Knowledge-Based Tutoring" describes the advantages and difficulties of adapting an expert system for use in teaching and problem solving. In this case the well-known rule-based expert system, MYCIN, which has been widely used in medical artificial intelligence to do infectious disease diagnosis and therapy selection, is used as a base for the instructional program GUIDON. MYCIN's rules are interpreted by GUIDON in order to evaluate a student's problem solving and provide assistance as the student gathers information about a patient and makes a diagnosis. The book describes what GUIDON does, how it is constructed, and the benefits and limitations of its design.This is the first attempt to adapt a rule base for tutoring and opens the door to what will most likely be a dramatic growth in interest in the use of expert systems for teaching. Clancey points out that it is easy to build an expert system that "works," but difficult to build one that makes knowledge explicit so that it can be taught. His dramatic demonstration of the separation of tutoring from subject matter knowledge will be of particular interest to researchers who are developing traditional computer-aided instruction programs.Clancey's program will also prove useful to cognitive science researchers in psychology and education who are interested in learning about AI techniques for explanation and student modeling, and to the many people who are currently developing computer-aided instruction programs. The book contains enough technical details for the work to be replicated, but has been generalized so the methods and lessons can be applied to other knowledge representations.William J. Clancey is a Senior Research Associate, at the Knowledge Systems Laboratory, Computer Science Department, Stanford University. "Knowledge-Based Tutoring" is included in The MIT Press Series in Artificial Intelligence, edited by Patrick Henry Winston and Michael Brady.
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