The Role of Probability-Based Inference in an Intelligent Tutoring System.

Abstract

Probability-based inference in complex networks of interdependent variables is an active topic in statistical research, spurred by such diverse applications as forecasting, pedigree analysis, troubleshooting, and.medical diagnosis. This paper concerns the role of Bayesian inference networks for updating student models in intelligent tutoring systems (ITSs). Basic concepts of the approach are briefly reviewed, but the emphasis is on the considerations that arise when,one attempts to operationalize the abstract framework of probability-based reasoning in a practical ITS context. The discussion revolves around HYDRIVE, an ITS for learning to trouble shoot an aircraft hydraulics system. HYDRIVE supports generalized claims about aspects of student proficiency through probability-based combination of rule-based evaluations of specific actions. The paper highlights the interplay among inferential issues, the psychology of learning in the domain, and the instructional approach upon which the ITS is based.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1995
Accession Number
ADA303584

Entities

People

  • Drew H. Gitomer
  • Robert J. Mislevy

Organizations

  • Educational Testing Service

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Aircrafts
  • Artificial Intelligence
  • Bayesian Inference
  • Bayesian Networks
  • Cognitive Science
  • Educational Psychology
  • Landing Gear
  • Military Research
  • Probability
  • Probability Distributions
  • Psychology
  • Random Variables
  • Reasoning
  • Statistical Inference
  • Statistics
  • Students
  • Theorems

Readers

  • Artificial Intelligence
  • Instructional Design and Training Evaluation.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference