Supporting Learners in Adaptive Learning Environments through the Enhancement of the Student Model

  • Luca Mazzola
  • Riccardo Mazza
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5613)

Abstract

This positional paper presents our research aimed at finding some possible research directions towards the enhancement of the use of open student models in the field of Technology Enhanced Learning and Adaptive Systems. Starting from the historical evolution of the learner model, we will describe some possible uses of learner models and propose some possible directions of enhancement. We will present 6 possible directions of research, and 11 dimensions on analysis. The 6 directions have been evaluated against the dimensions, and tentative ranking has been proposed. The result of this analysis will guide the work on open learner models which will be undertaken in the context of the European Union funded project GRAPPLE [1] aimed at building an infrastructure for adaptive learning systems that will adopt the strategy of opening learner models to the course learners and instructors.

Keywords

Technology Enhanced Learning independent Open Learner Model Human Computer Interaction adaptation 

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References

  1. 1.
    GRAPPLE project, http://grapple-project.org
  2. 2.
    Esposito, F., Licchelli, O., Semeraro, G.: Discovering Student Models in e-learning Systems. Journal of Universal Computer Science 10(1), 47–57 (2004), http://dx.doi.org/10.3217/jucs-010-01-0047 Google Scholar
  3. 3.
    Brusilovsky, P., Peylo, C. (eds.): Adaptive and intelligent Web-based educational systems. International Journal of Artificial Intelligence in Education 13(2-4)Google Scholar
  4. 4.
    Graf, S., Kinshuk: Learner Modelling Through Analyzing Cognitive Skills and Learning Styles. In: Adelsberger, H., Kinshuk, P., Pawlowski, J., Sampson, D. (eds.) Handbook on Information Technologies for Education and Training, 2nd edn., pp. 179–194. Springer Publishing Company, Incorporated, Heidelberg (2008)CrossRefGoogle Scholar
  5. 5.
    Bull, S.: A Simple Student Model to Make Students Think. In: Jameson, A., Paris, C., Tasso, C. (eds.) User Modelling Proceedings from 6th International Conference, UM, pp. 315–326 (1997)Google Scholar
  6. 6.
    Conlan, O., O’Keeffe, I., Brady, A., Wade, V.: Principles for Designing Activity-based Personalized eLearning. In: IEEE International Conference on Advanced Learning Technologies (ICALT 2007), pp. 642–644 (2007)Google Scholar
  7. 7.
    Dolog, P., Henze, N., Nejdl, W., Sintek, M.: Personalization in distributed e-learning environments. In: Proceedings of the 13th international World Wide Web Conference on Alternate Track Papers &Amp; Posters, WWW Alt. 2004, pp. 170–179. ACM, New York (2004)CrossRefGoogle Scholar
  8. 8.
    Dillenbourg, P., Fischer, F.: Basics of Computer-Supported Collaborative Learning. Zeitschrift für Berufs- und Wirtschaftspädagogik. 21, pp. 111–130 (2007)Google Scholar
  9. 9.
    Kay, J.: A scrutable user modelling shell for user-adapted interaction, PhD Thesis, Basser Department of Computer Science, University of Sydney, Australia (1999)Google Scholar
  10. 10.
    Bull, S., Nghiem, T.: Helping Learners to Understand Themselves with a Learner Model Open to Students, Peers and Instructors. In: International Conference on Intelligent Tutoring Systems 2002 - Workshop on Individual and Group Modelling Methods that Help Learners Understand Themselves (2002)Google Scholar
  11. 11.
    Bull, S., Mabbott, A., Abu-Issa, A.: UMPTEEN: Named and Anonymous Learner Model Access for Instructors and Peers. International Journal of Artificial Intelligence in Education 17(3), 227–253 (2007)Google Scholar
  12. 12.
    Vassileva, J.I., Greer, J.E., McCalla, G.I.: Opennes and Disclosure in Multi-agent Learner Models. In: Proceedings of the Workshop on Open, Interactive, and Other Overt Approaches to Learner Modelling at AIED 1999, Lemans, France (1999)Google Scholar
  13. 13.
    Vassileva, J.: Open Group Learner Modeling, Interaction Analysis and Social Visualization. In: Dimitrova, V., Tzagarakis, M., Vassileva, J. (eds.) Proceedings of Workshop on Adaptation and Personalisation in Social Systems: Groups, Teams, Communities. Held in conjunction with UM 2007, Crete (2007)Google Scholar
  14. 14.
    Glahn, C., Specht, M., Koper, R.: Reflecting on Web-readings with Tag Clouds. In: Conference Paper, Computer-based Knowledge & Skill Assessment and Feedback in Learning Settings (CAF) Special Track at the 11th International Conference on Interactive Computer aided Learning (ICL 2008), September, 24-26, 2008, Villach, Austria (2008)Google Scholar
  15. 15.
    Erickson, T., Kellogg, W.A.: Social translucence: using minimalist visualizations of social activity to support collective interaction. In: Höök, K., et al. (eds.) Designing information Spaces: the Social Navigation Approach, pp. 17–41. Springer, Berlin (2003)CrossRefGoogle Scholar
  16. 16.
    Spence, R.: Information Visualization: design for interaction, 2nd edn. Pearson Education/Prentice Hall, Harlow (2007)Google Scholar
  17. 17.
    Glahn, C., Specht, M., Koper, R.: Smart indicators to support the learning interaction cycle. International Journal of Continuing Engineering Education and Lifelong Learning 18(1), 98–117 (2008)CrossRefGoogle Scholar
  18. 18.
    Minaei-Bidgoli, B.: Data Mining for a Web-Based Educational System. Doctoral Thesis. Michigan State University (2005)Google Scholar
  19. 19.
    Mazza, R.: Introduction to Information Visualization. Springer, London (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Luca Mazzola
    • 1
  • Riccardo Mazza
    • 1
  1. 1.Faculty of Communication Sciences Institute for Communication TechnologyUniversity of LuganoLuganoSwitzerland

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