Skip to main content
SpringerLink
Log in
Book cover

International Conference on Intelligent Tutoring Systems

ITS 1996: Intelligent Tutoring Systems pp 596–604Cite as

A belief net backbone for student modelling

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1086))

Abstract

In this paper, I present a belief-net-based approach to student modelling which assists an ITS make determinations as to the extent of the student's knowledge. This approach also has advantages for structuring and ensuring the consistency of the student model. As well, the paper shows the desirability of using dynamic belief networks for modelling the dynamic evolution of the student's state of knowledge.

This is a preview of subscription content, log in via an institution.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Collins, A., and Stevens, A.L. (1982) Goals and strategies for inquiry teachers. In Glaser, R. (ed.) Advances in Instructional Psychology (vol. II), 65–119.

    Google Scholar 

  2. Corbett, A.T., and Anderson, J.R. (1992) Student modeling and mastery learning in a computer-based programming tutor. In Frasson, C., Gauthier, C. and McCalla, G.I. (eds.) Intelligent Tutoring Systems (ITS'92), 413–420.

    Google Scholar 

  3. de Kleer, J., and Williams, B.C. (1987) Diagnosing multiple faults. Artificial Intelligence 32, 97–130.

    Article  Google Scholar 

  4. Dean, T., and Kanazawa, K. (1989) A model for reasoning about persistence and causation. Computational Intelligence 5, 142–150.

    Google Scholar 

  5. Pearl, J. (1988) Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann.

    Google Scholar 

  6. Pirolli, P., and Wilson, M. (1992) Measuring learning strategies and understanding: a research framework. In Frasson, C., Gauthier, C. and McCalla, G.I. (eds.) Intelligent Tutoring Systems (ITS'92), 539–558.

    Google Scholar 

  7. Shute, V. (1995). SMART evaluation: cognitive diagnosis, mastery learning & remediation. In Greer, J. (ed.) Artificial Intelligence in Education, 1995, 123–130.

    Google Scholar 

  8. Villano, M. (1992) Probabilistic student models: bayesian belief networks and knowledge space theory. In Frasson, C., Gauthier, C. and McCalla, G.I. (eds.) Intelligent Tutoring Systems (ITS'92), 491–498.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Queensland University of Technology, Q 4001, Brisbane, Australia

    Jim Reye

Authors
  1. Jim Reye
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Claude Frasson Gilles Gauthier Alan Lesgold

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Reye, J. (1996). A belief net backbone for student modelling. In: Frasson, C., Gauthier, G., Lesgold, A. (eds) Intelligent Tutoring Systems. ITS 1996. Lecture Notes in Computer Science, vol 1086. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61327-7_159

Download citation

  • DOI: https://doi.org/10.1007/3-540-61327-7_159

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61327-5

  • Online ISBN: 978-3-540-68460-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation