Finding Appropriate Learning Objects: An Empirical Evaluation

  • Jehad Najjar
  • Joris Klerkx
  • Riina Vuorikari
  • Erik Duval
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3652)

Abstract

The challenge of finding appropriate learning objects is one of the bottlenecks for end users in Learning Object Repositories (LORs). This paper investigates usability problems of search tools for learning objects. We present findings and recommendations of an iterative usability study conducted to examine the usability of a search tool used to find learning objects in ARIADNE Knowledge Pool System [1]. Findings and recommendations of this study are generalized to other similar search tools.

Keywords

Learning Object Digital Library Search Tool Empirical Evaluation Usability Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
  2. 2.
    Blandford, A., Suzette, K., Connell, I., Edwards, H.: Analytical usability evaluation for digital libraries: a case study. In: ACM/IEEE Joint conference on Digital libraries, pp. 27–36 (2004)Google Scholar
  3. 3.
    Borgman, C.L.: Why are online catalogs hard to use? Lessons learned from information retrieval studies. Journal of the American Society for information Science 37(6), 387–400 (1986)Google Scholar
  4. 4.
    Borgman, C.L.: Why are online catalogs still hard to use? Journal of the American Society for information Science 47(7), 493–503 (1996)CrossRefGoogle Scholar
  5. 5.
    Cockburn, A., McKenzie, B.: What do web users do? An empirical Analysis of Web Use. Int’l. Journal of Human-Computer Studies 54(6), 903–922 (2001)MATHCrossRefGoogle Scholar
  6. 6.
    Courtois, M.P., Berry, M.W.: Results-ranking in Web search engines. Online 23(3), 39–40 (1999)Google Scholar
  7. 7.
    dtSearch, How to index databases with the dtSearch Engine, http://support.dtsearch.com/faq/dts0111.htm
  8. 8.
    Dublin Core, Dublin Core Metadata Element Set v1.1., http://www.dublincore.org
  9. 9.
    Duval, E., Hodgins, W.: A LOM research agenda. In: International conference on World Wide Web (2004)Google Scholar
  10. 10.
  11. 11.
    France, R.K., Nowell, T.L., Fox, A.E., Saad, A.R., Zhao, J.: Use and usability in a digital library search system. CoRR cs.DL/9902013 (1999)Google Scholar
  12. 12.
    Jones, S., Cunningham, S.J., McNab, R.: An Analysis of Usage of a Digital Library. In: Nikolaou, C., Stephanidis, C. (eds.) ECDL 1998. LNCS, vol. 1513, pp. 261–277. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  13. 13.
    IEEE Standard for Learning Object Metadata, http://ltsc.ieee.org/doc/wg12/
  14. 14.
    Klerkx, J., Duval, E., Meire, M.: Using information visualization for accessing learning object repositories. Information Visualization (IV 2004), 465–470 (2004)Google Scholar
  15. 15.
    Marchionini, G., Plaisant, C., Komlodi, A.: The people in digital libraries: Multifaceted approaches to assessing needs and impact. In: Bishop, A., Buttenfield, B., VanHouse, N. (eds.) Digital Library Use: Social Practice in Design and Evaluation, November 2003, pp. 119–160. MIT Press, Cambridge (2003)Google Scholar
  16. 16.
  17. 17.
    Najjar, J., Ternier, S., Duval, E.: The Actual Use of Metadata in ARIADNE: An Empirical Analysis. In: ARIADNE 3rd Conférence, pp. 1–6 (2003)Google Scholar
  18. 18.
    Najjar, J., Ternier, S., Duval, E.: User Behavior in Learning Objects Repositories: An Empirical Analysis. EdMedia, 4373–4378 (2004)Google Scholar
  19. 19.
    Najjar, J., Klerkx, J., Ternier, S., Verbert, K., Meire, M., Duval, E.: Usability Evaluation of Learning Object Indexation: the ARIADNE Experience. In: European Conference on e-Learning, pp. 281–290 (2004)Google Scholar
  20. 20.
    Neven, F., Duval, E., Ternier, S., Cardinaels, K., Vandepitte, P.: An Open and Flexible Indexation and Query tool for ARIADNE. In: EdMedia 2003, pp. 107–114 (2003)Google Scholar
  21. 21.
    Nielsen, J.: When Search Engines Become Answer Engines, usit.com (2004)Google Scholar
  22. 22.
    O’Neill, C., Paice, C.D.: the lancaster stemming algorithm, http://www.comp.lancs.ac.uk/computing/research/stemming/
  23. 23.
    Porter, M.: The Porter stemming algorithm, http://www.hackdiary.com/
  24. 24.

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Jehad Najjar
    • 1
  • Joris Klerkx
    • 1
  • Riina Vuorikari
    • 1
  • Erik Duval
    • 1
  1. 1.Computer Science DepartmentK.U.LeuvenLeuvenBelgium

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