A Probabilistic Model for Diagnosing Misconceptions by a Pattern Classification Approach.

Abstract

The purpose of this study is to introduce a probabilistic approach to classify and diagnose erroneous rules of operation resulting from a variety of misconceptions ('bugs') in a procedural domain of arithmetic. The model contrasts the deterministic approach which has commonly been used in the field of artificial intelligence and shows an advantage in treating the variability of errors in responses. Item response theory (IRT) turned out to be a useful model in integrating the theory of cognitive processes with educational practice. In this paper, erroneous rules of operation in signed-number subtraction problems are represented as points in a geometric space by utilizing IRT. We named this space 'rule space.' This approach seems promising in assessing the state of knowledge as reflected by erroneous rules and in utilizing the information obtained from behaviors of bugs into educational evaluation.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1983
Accession Number
ADA161617

Entities

People

  • Kikumi K. Tatsuoka

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Cognition
  • Computer Programs
  • Computer Science
  • Computers
  • Education
  • Information Processing
  • Information Science
  • Instructors
  • Military Research
  • Plastic Explosives
  • Probability
  • Psychology
  • Statistical Analysis
  • Students
  • Training

Readers

  • Artificial Intelligence
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space