Advertisement

Automating the Modeling of Learners’ Erroneous Behaviors in Model-Tracing Tutors

  • Luc Paquette
  • Jean-Franc̨ois Lebeau
  • André Mayers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7379)

Abstract

Modeling learners is a fundamental part of intelligent tutoring systems. It allows tutors to provide personalized feedback and to assess the learners’ mastery over a task domain. One aspect often overlooked is the modeling of erroneous behaviors that can be used to provide error specific feedback. This is especially true for model-tracing tutors that usually require erroneous procedural knowledge associated to each of the possible error. This process can be automated thanks to a task independent model describing the learners’ erroneous behaviors. The model proposed in this paper is inspired by the Sierra theory of procedural error and is developed for ASTUS, an authoring framework for model-tracing tutors.

Keywords

Erroneous behaviors learner modeling model-tracing tutors 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Aleven, V.: Rule-Based Cognitive Modeling for Intelligent Tutoring Systems. In: Nkambou, R., Bourdeau, J., Mizoguchi, R. (eds.) Advances in Intelligent Tutoring Systems. SCI, vol. 308, pp. 33–62. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  2. 2.
    Fortin, M., Lebeau, J.-F., Abdessemed, A., Courtemanche, F., Mayers, A.: A Standard Method of Developing User Interfaces for a Generic ITS Framework. In: Woolf, B.P., Aïmeur, E., Nkambou, R., Lajoie, S. (eds.) ITS 2008. LNCS, vol. 5091, pp. 312–322. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  3. 3.
    Corbett, A.T., Anderson, J.R.: Knowledge Tracing: Modeling the Acquisition of Procedural Knowledge. User Modeling and User-Adapted Interaction 4, 253–278 (1995)CrossRefGoogle Scholar
  4. 4.
    Ohlsson, S.: Deep Learning: How the Mind Overrides Experience. Cambridge University Press, New York (2011)CrossRefGoogle Scholar
  5. 5.
    Mitrovic, A.: Modeling Domains and Students with Constraint-Based Modeling. In: Nkambou, R., Bourdeau, J., Mizoguchi, R. (eds.) Advances in Intelligent Tutoring Systems. SCI, vol. 308, pp. 63–80. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  6. 6.
    Baffes, P., Mooney, R.: Refinement-Based Student Modeling and Automated Bug Library Construction. Journal of Artificial Intelligence in Education 7(1), 7–116 (1996)Google Scholar
  7. 7.
    Mitrovic, A., Koedinger, K., Martin, B.: A Comparative Analysis of Cognitive Tutoring and Constraint-Based Modeling. In: Brusilovsky, P., Corbett, A.T., de Rosis, F. (eds.) UM 2003. LNCS, vol. 2702, pp. 313–322. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  8. 8.
    VanLehn, K.: Mind Bugs: The Origin of Procedural Misconceptions. MIT Press (1990)Google Scholar
  9. 9.
    Paquette, L., Lebeau, J.-F., Mayers, A.: Authoring Problem-Solving Tutors: A Comparison between ASTUS and CTAT. In: Nkambou, R., Bourdeau, J., Mizoguchi, R. (eds.) Advances in Intelligent Tutoring Systems. SCI, vol. 308, pp. 377–405. Springer, Heidelberg (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Luc Paquette
    • 1
  • Jean-Franc̨ois Lebeau
    • 1
  • André Mayers
    • 1
  1. 1.Université de SherbrookeCanada

Personalised recommendations