Accession Number:

ADA207041

Title:

Rules and Principles in Cognitive Diagnosis

Descriptive Note:

Interim rept. 1 Jan-31 Dec 1988

Corporate Author:

CALIFORNIA UNIV IRVINE SCHOOL OF INFORMATION AND COMPUTER SCIENCE

Report Date:

1989-01-01

Pagination or Media Count:

37.0

Abstract:

Cognitive simulation is concerned with constructing process models of human cognitive behavior. The authors work on the ACM Automated Cognitive Modeler is an attempt to automate this process. The basic assumption is that all goal-oriented cognitive behavior involves search through some problem space. Within this framework, the task of cognitive diagnosis is to identify the problem space in which the subject is operating, identify solution paths used by the subject, and find conditions on the operators that explain those solution paths that predict the subjects behavior on new problems. The work presented in this paper uses techniques from machine learning to automate the tasks of finding solution paths and operator conditions. The authors apply this method to the domain of multi-column subtraction and present results that demonstrate ACMs ability to model incorrect subtraction strategies. Finally, they discuss the difference between procedural bugs and misconceptions, proposing that errors due to misconceptions can be viewed as violations of principles for the task domain. Keywords Heuristic search, Machine learning.

Subject Categories:

  • Psychology
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE