Nothing Special   »   [go: up one dir, main page]

Skip to main content

Approximate Modelling of the Multi-dimensional Learner

  • Conference paper
Intelligent Tutoring Systems (ITS 2006)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 4053))

Included in the following conference series:

Abstract

This paper describes the design of the learner modelling component of the LeActiveMath system, which was conceived to integrate modelling of learners’ competencies in a subject domain, motivational and affective dispositions and meta-cognition. This goal has been achieved by organising learner models as stacks, with the subject domain as ground layer and competency, motivation, affect and meta-cognition as upper layers. A concept map per layer defines each layer’s elements and internal structure, and beliefs are associated to the applications of elements in upper-layers to elements in lower-layers. Beliefs are represented using belief functions and organised in a network constructed as the composition of all layers’ concept maps, which is used for propagation of evidence.

This publication was generated in the context of the LeActiveMath project, funded under the 6th Framework Programm of the European Community – (Contract N° IST- 2003-507826). The authors are solely responsible for its content, it does not represent the opinion of the European Community and the Community is not responsible for any use that might be made of data appearing therein.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Advanced Distributed Learning: Sharable Content Object Reference Model Version 1.2: The SCORM Overview (2001)

    Google Scholar 

  2. LeActiveMath Consortium: Language-enhanced, user adaptive, interactive elearning for mathematics (2004), http://www.leactivemath.org

  3. National Information Standards Organization: Understanding Metadata (2004)

    Google Scholar 

  4. Institute of Electrical and Electronics Engineers: IEEE 1484.12.1 Draft Standard for Learning Object Metadata (2002)

    Google Scholar 

  5. Organisation for Economic Co-Operation and Development: The PISA 2003 Assessment Framework (2003)

    Google Scholar 

  6. Self, J.A.: Dormorbile: A vehicle for metacognition. AAI/AI-ED Technical Report 98, Computing Department, Lancaster University, Lancaster, UK (1994)

    Google Scholar 

  7. Zapata-Rivera, J.-D., Greer, J.E.: Inspecting and Visualizing Distributed Bayesian Student Models. In: Gauthier, G., VanLehn, K., Frasson, C. (eds.) ITS 2000. LNCS, vol. 1839, pp. 544–553. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  8. Smets, P., Kennes, R.: The transferable belief model. Artificial Intelligence 66(2), 191–234 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  9. Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press, Princeton (1976)

    MATH  Google Scholar 

  10. Sentz, K., Ferson, S.: Combination of evidence in dempster-shafer theory. Sandia Report SAND2002-0835, Sandia National Laboratories (2002)

    Google Scholar 

  11. Shenoy, P.P., Shafer, G.: Axioms for probability in belief-function propagation. In: Shachter, R.D., Levitt, T.S., Kanal, L.N., Lemmer, J.F. (eds.) Proceedings of the Fourth Anual Conference on Uncertainty in Artificial Intelligence, pp. 169–198. North-Holland, Amsterdam (1990)

    Google Scholar 

  12. Conati, C., Gertner, A., VanLehn, K.: Using bayesian networks to manage uncertainty in student modeling. User Modeling and User-Adapted Interaction 12(4), 371–417 (2002)

    Article  MATH  Google Scholar 

  13. Bunt, A., Conati, C.: Probabilistic student modelling to improve exploratory behaviour. User Modeling and User-Adapted Interaction 13(3), 269–309 (2003)

    Article  Google Scholar 

  14. Jameson, A.: Numerical uncertainty management in user and student modeling: An overview of systems and issues. User Modeling and User-Adapted Interaction 5(3–4), 193–251 (1996)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Morales, R., van Labeke, N., Brna, P. (2006). Approximate Modelling of the Multi-dimensional Learner. In: Ikeda, M., Ashley, K.D., Chan, TW. (eds) Intelligent Tutoring Systems. ITS 2006. Lecture Notes in Computer Science, vol 4053. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11774303_55

Download citation

  • DOI: https://doi.org/10.1007/11774303_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35159-7

  • Online ISBN: 978-3-540-35160-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics