Report Number: CS-TR-82-910
Institution: Stanford University, Department of Computer Science
Title: Exploration of Teaching and Problem-Solving Strategies, 1979-1982
Author: Clancey, William J.
Author: Buchanan, Bruce
Date: May 1982
Abstract: This is the final report for Contract N-00014-79-C-0302, covering the period of 15 March 1979 through 14 March 1982. The goal of the project was to develop methods for representing teaching and problem-solving knowledge in computer-based tutorial systems. One focus of the work was formulation of principles for managing a case method tutorial dialogue; the other major focus was investigation of the use of a production rule representation for the subject material of a tutorial program. The main theme pursued by this research is that representing teaching and problem-solving knowledge separately and explicitly enhances the ability to build, modify and test complex tutorial programs. Two major computer programs were constructed. One was the tutorial program, GUIDON, which uses a set of explicit "discourse procedures" for carrying on a case method dialogue with a student. GUIDON uses the original MYCIN knowledge base as subject material, and as such, was an experiment in exploring the ways in which production rules can be used in tutoring. GUlDON's teaching knowledge is separate from and compatible with any knowledge base that is encoded in MYClN's rule language. Demonstrations of GUIDON were given for two medical and one engineering application. Thus, the generality of this kind of system goes beyond being able to teach about any problem in a "case library"--it also allows teaching expertise to be transferred and tested in multiple problem domains. The second major program is the consultation program, NEOMYCIN. This is a second generation system in which MYClN's knowledge has been reconfigured to make explicit distinctions that are important for teaching. Unlike MYCIN, the program uses the hypothesis-oriented approach and predominantly forward-directed reasoning. As such, NEOMYCIN is consistent with and extends psychological models of diagnostic problem-solving. The program differs from other knowledge-based Al systems in that reasoning is completely controlled by a set of explicit meta-rules. These meta-rules are domain independent and constitute the diagnostic procedure to be taught to students: the tasks of diagnosis and heuristics for attending to and confirming relevant diagnostic hypotheses.