Using Multiple Intelligence Informed Resources in an Adaptive System

  • Declan Kelly
  • Brendan Tangney
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4053)


Adaptive educational systems capture and represent, for each student, various characteristics such as knowledge and traits in an individual learner model. However, there are some unresolved issues in building adaptive educational systems that adapt to individual traits. For example it is not obvious what is the appropriate educational theory with which to develop instructional resources and model individual traits. This paper describes an experiment using the Multiple Intelligence (MI) based adaptive intelligent educational system, EDUCE, that explores how different categories of resources are used when the learner has complete control and when adaptive presentation strategies are employed. In particular it explores how Musical/Rhythmic traits and resources impact on performance. Results suggest that students prefer using Musical/ Rhythmic resources to other types of resources, however it is not clear how this preference can be best employed to enhance learning performance.


Adaptive System Presentation Strategy Prefer Strategy Educational Theory Multiple Intelligence 
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  1. 1.
    Brusilovsky, P.: Adaptive Hypermedia. User Modeling and User-Adapted Instruction 11(1-2), 87–110 (2001)MATHCrossRefGoogle Scholar
  2. 2.
    Brusilovsky, P., Peylo, C.: Adaptive and Intelligent Web-based Educational Systems. International Journal of Arificial Intelligence in Education 13(2-4), 159–172 (2003)Google Scholar
  3. 3.
    Cambpell, L., Campbell, B.: Multiple Intelligences and student achievement: Success stories from six schools. Association for Supervision and Curriculum Development (2000)Google Scholar
  4. 4.
    Carroll, K.: Sing a Song of Science. Zephyr Press (1999)Google Scholar
  5. 5.
    De Bra, P.: Adaptive Educational Hypermedia on the Web. Communications of the ACM 45(5), 60–61 (2002)Google Scholar
  6. 6.
    Gardner, H.: Frames of Mind: The theory of multiple intelligences. Basic Books, New York (1983)Google Scholar
  7. 7.
    Gilbert, J.E., Han, C.Y.: Adapting Instruction in search of a significant difference. Journal of Network and Computer Applications 22(3), 149–160 (1999)CrossRefGoogle Scholar
  8. 8.
    Kelly, D.: A Framework for using Multiple Intelligences in an ITS. In: Proceedings of EDMedia 2003, World Conference on Educational Multimedia, Hypermedia & Telecommunications, Honolulu, HI (2003)Google Scholar
  9. 9.
    Kelly, D., Tangney, B.: Predicting Learning Characteristics in a Multiple Intelligence Based Tutoring System. In: Lester, J.C., Vicari, R.M., Paraguaçu, F. (eds.) ITS 2004. LNCS, vol. 3220, pp. 678–688. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  10. 10.
    Kelly, D., Tangney, B.: Matching and Mismatching Learning Characteristics with Multiple Intelligence Based Content. In: The Twelveth International Conference on Artificial Intelligence in Education, AIED 2005, Amsterdam, Netherlands, pp. 354–361. Reigeluth, C.M. (1996); A new paradigm of ISD? Educational Technology 36(3) (1996)Google Scholar
  11. 11.
    Lazaer, D.: Eight Ways of Teaching: The Artistry of Teaching with Multiple Intelligences, SkyLight (1999)Google Scholar
  12. 12.
    Riding, R., Rayner, S.: Cognitive Styles and learning strategies, David Fulton (1997)Google Scholar
  13. 13.
    Rasmussen, K.L.: Hypermedia and learning styles: Can performance be influenced? Journal of Multimedia and Hypermedia 7(4) (1998)Google Scholar
  14. 14.
    Specht, M., Oppermann, R.: ACE: Adaptive CourseWare Environment. New Review of HyperMedia & MultiMedia 4 (1998)Google Scholar
  15. 15.
    Stern, M., Woolf, B.: Adaptive Content in an Online lecture system. In: Proceedings of the First Adpative Hypermedia Conference, AH 2000 (2000)Google Scholar
  16. 16.
    Papanikolaou, K.A., Grigoriadou, M., Kornilakis, H., Magoula, G.D.: Personalising the interaction in a Web-based educational hypermedia system: the case of INSPIRE. User-Modeling and User-Adapted Interaction 13(3), 213–267 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Declan Kelly
    • 1
  • Brendan Tangney
    • 2
  1. 1.National College of IrelandIreland
  2. 2.Trinity CollegeUniversity of DublinIreland

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