Rule-Based Cognitive Modeling for Intelligent Tutoring Systems

  • Vincent Aleven
Part of the Studies in Computational Intelligence book series (SCI, volume 308)


Rule-based cognitive models serve many roles in intelligent tutoring systems (ITS) development. They help understand student thinking and problem solving, help guide many aspects of the design of a tutor, and can function as the “smarts” of a system. Cognitive Tutors using rule-based cognitive models have been proven to be successful in improving student learning in a range of learning domain. The chapter focuses on key practical aspects of model development for this type of tutors and describes two models in significant detail. First, a simple rule-based model built for fraction addition, created with the Cognitive Tutor Authoring Tools, illustrates the importance of a model’s flexibility and its cognitive fidelity. It also illustrates the model-tracing algorithm in greater detail than many previous publications. Second, a rule-based model used in the Geometry Cognitive Tutor illustrates how ease of engineering is a second important concern shaping a model used in a large-scale tutor. Although cognitive fidelity and ease of engineering are sometimes at odds, overall the model used in the Geometry Cognitive Tutor meets both concerns to a significant degree. On-going work in educational data mining may lead to novel techniques for improving the cognitive fidelity of models and thereby the effectiveness of tutors.


Production Rule Solution Path Rule Activation Intelligent Tutoring System Knowledge Component 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Vincent Aleven
    • 1
  1. 1.Human-Computer Interaction InstituteCarnegie Mellon UniversityPittsburghUSA

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