Fading and Deepening: The Next Steps for Andes and Other Model-Tracing Tutors

  • Kurt VanLehn
  • Reva Freedman
  • Pamela Jordan
  • Charles Murray
  • Remus Osan
  • Michael Ringenberg
  • Carolyn Rosé
  • Kay Schulze
  • Robert Shelby
  • Donald Treacy
  • Anders Weinstein
  • Mary Wintersgill
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1839)


Model tracing tutors have been quite successful in teaching cognitive skills; however, they still are not as competent as expert human tutors. We propose two ways to improve model tracing tutors and in particular the Andes physics tutor. First, tutors should fade their scaffolding. Although most model tracing tutors have scaffolding that needs to be gradually removed (faded), Andes’ scaffolding is already “faded,” and that causes student modeling difficulties that adversely impact its tutoring. A proposed solution to this problem is presented. Second, tutors should integrate the knowledge they currently teach with other important knowledge in the task domain in order to promote deeper learning. Several types of deep learning are discussed, and it is argued that natural language processing is necessary for encouraging such learning. A new project, Atlas, is developing natural language based enhancements to model tracing tutors that are intended to encourage deeper learning.


Graphical User Interface Deep Learning Intelligent Tutor System Expert Model Cognitive Science Society 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Kurt VanLehn
    • 1
  • Reva Freedman
    • 1
  • Pamela Jordan
    • 1
  • Charles Murray
    • 1
  • Remus Osan
    • 1
  • Michael Ringenberg
    • 1
  • Carolyn Rosé
    • 1
  • Kay Schulze
    • 3
  • Robert Shelby
    • 2
  • Donald Treacy
    • 2
  • Anders Weinstein
    • 1
  • Mary Wintersgill
    • 2
  1. 1.Learning Research and Development CenterUniversity of PittsburghPittsburgh
  2. 2.Department of PhysicsUnited States Naval AcademyUSA
  3. 3.Computer Science DepartmentUnited States Naval AcademyUSA

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