2001 · 80 citations · 8 references
EducationEducational TechnologyInstructionE-learningIntelligent Tutoring SystemsKnowledge RepresentationBayesian LearningLearner ModelingOnline TutoringOnline Tutoring SystemsStudent ModelingUser ModelingBayesian NetworksDomain Knowledge IntegrationIntelligent Tutoring DialoguesKnowledge Base ArchitectureKnowledge State RepresentationPedagogical ModelsTutor RecommendationTutoring Dialogue Systems
The paper proposes a Bayesian‑network‑based model and architecture for designing intelligent tutoring systems. The architecture separates domain knowledge from the tutor shell and comprises a user model, knowledge base, adaptation, pedagogical, and presentation modules; Bayesian networks assess user knowledge and preferences to recommend pedagogical options, and the system is implemented as an Internet e‑learning tool with an illustrative example.
This paper proposes a model and an architecture for designing intelligent tutoring system using Bayesian Networks. The design model of an intelligent tutoring system is directed towards the separation between the domain knowledge and the tutor shell. The architecture is composed by a user model, a knowledge base, an adaptation module, a pedagogical module and a presentation module. Bayesian Networks are used to assess user’s state of knowledge and preferences, in order to suggest pedagogical options and recommend future steps in the tutor. The proposed architecture is implemented in the Internet, enabling its use as an e-learning tool. An example of an intelligent tutoring system is shown for illustration purposes.
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Artificial intelligence: a modern approach
Choice Reviews Online · 1995 · 22.2K citations · Full text
Ingo Lehmann, Richard W. Weber, H.-J. Zimmermann · OR Spectrum · 1992 · 150 citations