Accession Number : ADA258622


Title :   Probabilistic Student Modeling with Knowledge Space Theory


Descriptive Note : Interim rept. Feb 1991-Feb 1992


Corporate Author : HONEYWELL SENSOR AND SYSTEM DEVELOPMENT CENTER MINNEAPOLIS MN


Personal Author(s) : Villano, Michael ; Bloom, Charles


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a258622.pdf


Report Date : Oct 1992


Pagination or Media Count : 16


Abstract : This article presents Knowledge Space Theory (Falmagne and Doignon) as the foundation for a probabilistic student model to be imbedded in an intelligent Tutoring System (ITS). Applications to typical ITS student modeling issues such as knowledge representation, adaptive assessment, curriculum representation, advancement criteria, and student feedback are discussed. Several factors contribute to uncertainty In student modeling such as careless errors and lucky guesses, learning and forgetting, and unanticipated student response patterns. However, a probabilistic student model can represent uncertainty regarding the estimate of the student's knowledge and can be tested using empirical student data and established statistical techniques.


Descriptors :   *MATHEMATICAL MODELS , *ARTIFICIAL INTELLIGENCE , *COMPUTER AIDED INSTRUCTION , NEURAL NETS , MODELS , STUDENTS , NETWORKS , COMPUTERS , LEARNING , INSTRUCTIONS , THEORY , ESTIMATES , RESPONSE , FEEDBACK , ERRORS


Subject Categories : Computer Programming and Software
      Cybernetics


Distribution Statement : APPROVED FOR PUBLIC RELEASE