Just Enough Fidelity in Student and Expert Modeling for ITS

Making the Practice Practical
  • Brandt Dargue
  • Elizabeth Biddle
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8534)


Intelligent Tutoring Systems (ITSs) are usually comprised of three primary models – an expert model, a domain or system model, and a student model. Many of these models are quite complex to enable just about any learner to get the optimum tailored experience possible. These systems have shown great results, typically at least one standard deviation (a letter grade) better than traditional training (e.g. [1] [2]). This complexity not only ensured that ITSs were successful, it also prohibited their widespread use (e.g. [3]). Results of studies in which the expert and system models were simplified show similar gains in effectiveness (e.g. [4] [5]), suggesting that lower-cost ITSs can be just as effective as those developed at higher costs. This paper compares the results of effectiveness studies in which the ITSs had various levels of fidelity and presents some recommended guidelines in determining the level of fidelity for student, expert, and system models of the ITS.


Cognitive Modeling Perception Emotion and Interaction Machine Learning Neural Networks Techniques for Data Processing Adaptive User Interfaces Human performance improvement Intelligent Tutoring Adaptive training 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Brandt Dargue
    • 1
  • Elizabeth Biddle
    • 2
  1. 1.Boeing Research & Technologies (BR&T)St. LouisUSA
  2. 2.Boeing Research & Technologies (BR&T)OrlandoUSA

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