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Record 1 1989-06-23

English

Subject field(s)
  • Artificial Intelligence
  • Continuing Education
CONT

For diagnosis, the system simply updates the probabilities in the student's matrix with methods from probability theory. When problem classes occur for the first time, ad hoc heuristics generate a seed probability. Kimball claims that the probabilistic approach allows precise measurements of student learning revealing its discontinuities. He suggests that the identification of these discontinuities, which are apparently associated with failures, is an important pedagogical task. Kimball goes into a lengthy technical argument to support the applicability of his probabilistic approach to modeling the student, mainly from the standpoint of independence of the probabilities associated with the various approaches. Many of his concerns actually apply to other modular representations, such as rule-based ones, used more recently for student modeling.

French

Domaine(s)
  • Intelligence artificielle
  • Éducation permanente

Spanish

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