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The uses of multiple student inputs in modeling and lesson planning in CAI and ICAI programs

  • Joel Michael
  • Allen Rovick
  • Martha Evens
  • Leemseop Shim
  • Chong Woo
  • Nahkoon Kim
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 602)

Abstract

Responding appropriately to student errors requires some model of the student with which to determine the most likely cause of the errors. In a conventional CAI program the model is implicit and is represented by the hard-coded relationship between errors and corrective feedback. In an intelligent tutoring system (ICAI program) student modeling can be done dynamically as student responses are generated. In both cases, multiple inputs about causally related variables obtained prior to any tutoring provides a rich source of information about the cognitive state of the student. As a result it is possible to produce a more robust student model and to generate a more effective sequence of lessons to repair the student's misconceptions. Examples of such an approach used in the implementation of both a CAI and a ICAI program are presented.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Joel Michael
    • 1
  • Allen Rovick
    • 1
  • Martha Evens
    • 2
  • Leemseop Shim
    • 2
  • Chong Woo
    • 2
  • Nahkoon Kim
    • 3
  1. 1.Department of PhysiologyRush Medical CollegeChicago
  2. 2.Computer Science DepartmentIllinois Institute of TechnologyChicago
  3. 3.Dong Duck Women's UniversitySeoulKorea

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