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Understandable Learner Models for a Sensorimotor Control Task

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Intelligent Tutoring Systems (ITS 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1839))

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Abstract

We discuss the implications of making learner models that can be inspected by learners within the context of a sensorimotor control task—that of balancing a pole hinged to a cart. We argue that the requirement of producing models that are comprehensible by learners limits the options of modelling strategy, constrains model structure and calls for further refinement of model contents. We discuss the issues of modularity of model contents, modality and interactivity of model presentation, and present results from a preliminary evaluation of a graphical interface to learner models for pole balancing.

Supported by CONACYT and the Instituto de Investigaciones Electricas, Mexico, under scholarship 64999/111091.

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References

  1. Anderson J.R.: Rules of the Mind. Lawrence Erlbaum Associates (1993)

    Google Scholar 

  2. Ayala G., Yano Y.: Learner models for supporting awareness and collaboration in a CSCL environment. In: Frasson C., Gauthier G. (eds.), Intelligent Tutoring Systems (ITS’96), vol. 1086 of Lecture Notes in Computer Science. Springer-Verlag (1996) 158–167

    Google Scholar 

  3. Barr A., Feigenbaum E.A. (eds.): The Handbook of Artificial Intelligence, vol. I. Pitman, London (1981)

    MATH  Google Scholar 

  4. Barto A.G., Sutton R.S., Anderson C.W.: Neuronlike adaptive elements that can solve difficult learning control problems. IEEE Transactions on Systems, Man and Cybernetics SMC-13 (1983) 834–846

    Google Scholar 

  5. de Buen P.R., Vadera S., Morales E.F.: A collaborative approach to user modeling within a multi-functional architecture. In: Kay [17] (1999) 291–293

    Google Scholar 

  6. Bull S.: See yourself write: A simple student model to make students think. In: Jameson A., Paris C., Tasso C. (eds.), User Modeling (UM’97). Springer Wien New York (1997) 315–326

    Google Scholar 

  7. Bull S., Brna P., Pain H.: Extending the scope of the student model. User Modeling and User-Adapted Interaction 5 (1995) 45–65

    Article  Google Scholar 

  8. Bull S., Pain H.: “Did I say what I think I said, and do you agree with me?” inspecting and questioning the student model. In: Greer [14] (1995) 501–508

    Google Scholar 

  9. Cohen W.W.: Fast effective rule induction. In: Prieditis A., Russell S. (eds.), Machine Learning (ML’95). Morgan Kaufmann (1995)

    Google Scholar 

  10. Conlon T.: Alternatives to rules for knowledge-based modelling. Instructional Science 27 (1999) 117–146

    Google Scholar 

  11. Cook R., Kay J.: The justified user model: A viewable, explained user model. In: Proceedings of the Fourth International Conference on User Modeling. Hyannis, MA (1994) 145–150

    Google Scholar 

  12. Cox R., Brna P.: Supporting the use of external representations in problem solving: the need for flexible learning environments. Journal of Artificial Intelligence in Education 6 (1995) 239–302

    Google Scholar 

  13. Dimitrova V., Self J., Brna P.: The interactive maintenance of open learner models. In: Lajoie S.P., Vivet M. (eds.), Artificial Intelligence in Education (AIEd’99). IOS Press (1999) 405–412

    Google Scholar 

  14. Greer J.E. (ed.): Proceedings of the Seventh World Conference on Artificial Intelligence in Education. Washington, DC (1995)

    Google Scholar 

  15. Greer J.E., Zapata-Rivera J.D., Ong-Scutchings C., Cooke J.E.: Visualization of Bayesian learner models. In: Morales R., Pain H., Bull S., Kay J. (eds.), Proceedings of the Workshop on Open, Interactive, and Other Overt Approaches to Learner Modelling. Le Mans, France (1999) 9–13

    Google Scholar 

  16. Hayes-Roth F.: Rule-based systems. Communications of ACM 28 (1985) 921–932

    Article  Google Scholar 

  17. Kay J. (ed.): User Modeling (UM’99). Springer Wien New York (1999)

    Google Scholar 

  18. Michie D., Chambers R.A.: BOXES: An experiment in adaptive control. In: Dale E., Michie D. (eds.), Machine Intelligence, vol. 2. Oliver and Boyd, Edinburgh (1968) 137–152

    Google Scholar 

  19. Mitchell T.M.: Machine Learning. McGraw-Hill (1997)

    Google Scholar 

  20. Morales R., Pain H.: Modelling of novices’ control skills with machine learning. In: Kay [17] (1999) 159–168

    Google Scholar 

  21. Paiva A., Self J.A., Hartley R.: Externalising learner models. In: Greer [14] (1995)

    Google Scholar 

  22. Pineda L., Garza G.: A model for multimodal representation and inference. In: Paton R., Neilsen I. (eds.), Visual Representations and Interpretations. Springer (1999)

    Google Scholar 

  23. Self J.A.: Bypassing the intractable problem of student modelling. In: Proceedings of ITS’88. Montreal, Canada (1988) 18–24

    Google Scholar 

  24. Sison R., Shimura M.: Student modeling and machine learning. International Journal of Artificial Intelligence in Education 9 (1998) 128–158

    Google Scholar 

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Author information

Authors and Affiliations

  1. Division of Informatics, University of Edinburgh, 80 South Bridge, Edinburgh, EH1 1HN, UK

    Rafael Morales & Helen Pain

  2. Moray House Institute of Education, University of Edinburgh, Holyrood Road, Edinburgh, EH8 8AQ, UK

    Tom Conlon

Authors
  1. Rafael Morales
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  2. Helen Pain
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  3. Tom Conlon
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Editor information

Editors and Affiliations

  1. Département d’informatique, Université du Québec á Montréal, C.P. 8888, succ. Centre-Ville, Montréal, QC, Canada, H3C 3P8

    Gilles Gauthier

  2. Département d’informatique et de recherche opérationnelle, Université de Montréal, C.P. 6128, succ. Centre-Ville, Montréal, QC, Canada, H3C 3J7

    Claude Frasson

  3. Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, 15260, USA

    Kurt VanLehn

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© 2000 Springer-Verlag Berlin Heidelberg

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Morales, R., Pain, H., Conlon, T. (2000). Understandable Learner Models for a Sensorimotor Control Task. In: Gauthier, G., Frasson, C., VanLehn, K. (eds) Intelligent Tutoring Systems. ITS 2000. Lecture Notes in Computer Science, vol 1839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45108-0_26

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  • DOI: https://doi.org/10.1007/3-540-45108-0_26

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67655-3

  • Online ISBN: 978-3-540-45108-2

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