Computer-based tutors for explaining and managing the process of diagnostic reasoning. Final report, March 1985-December 1988
AI(Artificial intelligence)-based instructional programs, often called intelligent tutoring systems (ITS), use qualitative modeling techniques to represent: (1) processes in the subject domain (e.g., a steam propulsion plant, an electronic circuit), (2) problem-solving processes (e.g., diagnostic strategy, programming methods), and (3) communication processes (e.g., the Socratic method, case-method discourse, and rhetorical principles in explanation) ('Qualitative student models'). Typically, instructional programs may represent only one or two kinds of these processes. When a simulation model of problem-solving processes is incorporated in the program, a basis is provided for evaluating and assisting the student in a very general way. Such programs, which can solve the same problems given to a student, are called knowledge-based tutors (Knowledge-based Tutoring). Early in this research, the author identified the importance of representing problem-solving processes in a well-structured procedural language. In a sequence of programs, we demonstrated basic AL techniques for achieving the separation of domain facts from a diagnostic procedure (NEOMYCIN), and the advantages of this separation for explanation and student modeling (IMAGE, ODYSSEUS). The generalization of the work has had a significant impact on expert systems and tutoring research.
- Research Organization:
- Stanford Univ., CA (USA). Inst. for Research on Learning
- OSTI ID:
- 5173202
- Report Number(s):
- AD-A-211738/0/XAB
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
ARTIFICIAL INTELLIGENCE
COMPUTER-AIDED INSTRUCTION
EXPERT SYSTEMS
COMMUNICATIONS
MAINTENANCE
PROGRAMMING
PROGRESS REPORT
PROPULSION SYSTEMS
SIMULATION
THERMAL POWER PLANTS
DOCUMENT TYPES
POWER PLANTS
TRAINING
990200* - Mathematics & Computers