Using Similarity Metrics for Matching Lifelong Learners

  • Nicolas Van Labeke
  • Alexandra Poulovassilis
  • George Magoulas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5091)


The L4All system provides an environment for the lifelong learner to access information about courses, personal development plans, recommendation of learning pathways, personalised support for planning of learning, and reflecting on learning. Designed as a web-based application, it offers lifelong learners the possibility to define and share their own timeline (a chronological record of their relevant life episodes) in order to foster collaborative elaboration of future goals and aspirations. A keystone for delivering such functionalities is the possibility for learner to search for ‘people like me’. Addressing the fact that such a definition of ‘people like me’ is ambiguous and subjective, this paper explores the use of similarity metrics as a flexible mechanism for comparing and ranking lifelong learners’ timelines.


Similarity Measure User Model Lifelong Learner Similarity Metrics Personalise Support 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Koper, R., Tattersall, C.: New directions for lifelong learning using network technologies. British Journal of Educational Technology 35(6), 689–700 (2004)CrossRefGoogle Scholar
  2. 2.
    Koper, R., Giesbers, B., van Rosmalen, P., Sloep, P., van Bruggen, J., Tattersall, C., Vogten, H., Brouns, F.: A design model for lifelong learning networks. Interactive Learning Environments 13(1–2), 71–92 (2005)CrossRefGoogle Scholar
  3. 3.
    de Freitas, S., Magoulas, G., Oliver, M., Papamarkos, G., Harrison, A.P.I., Mee, A.: L4all - a web-service based system for lifelong learners. In: Proceedings of eChallenges 2006 (Workshop on Next Generation in Technology Enhanced Learning), pp. 1477–1484 (2006)Google Scholar
  4. 4.
    de Freitas, S., Harrison, I., Magoulas, G., Mee, A., Mohamad, F., Oliver, M., Papamarkos, G., Poulovassilis, A.: The development of a system for supporting the lifelong learner. British Journal of Educational Technology 37(6), 867–880 (2006)CrossRefGoogle Scholar
  5. 5.
    Peterson, D., Levene, M.: Trail records and navigational learning. London Review of Education 1(3), 207–216 (2003)CrossRefGoogle Scholar
  6. 6.
    Baajour, H., Magoulas, G., Poulovassilis, A.: Modelling the lifelong learner in a services-based environment. In: Proceedings of ITA 2007- 2nd International Conference on Internet Technologies and Applications, pp. 181–190 (2007)Google Scholar
  7. 7.
    Gusfield, D.: Algorithms on Strings, Trees, and Sequences - Computer Science and Computational Biology. Cambridge University Press (1997)Google Scholar
  8. 8.
    Cohen, W.W., Ravikumar, P., Fienberg, S.E.: A comparison of string distance metrics for name-matching tasks. In: Proceedings of IIWeb 2003 – IJCAI Workshop on Information Integration on the Web, pp. 73–78 (2003)Google Scholar
  9. 9.
    Ainsworth, S., Clarke, D., Gaizauskas, R.J.: Using edit distance algorithms to compare alternative approaches to its authoring. In: Cerri, S.A., Gouardéres, G., Paraguaçu, F. (eds.) ITS 2002. LNCS, vol. 2363, pp. 873–882. Springer, Heidelberg (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Nicolas Van Labeke
    • 1
  • Alexandra Poulovassilis
    • 1
  • George Magoulas
    • 1
  1. 1.London Knowledge Lab, BirkbeckUniversity of LondonLondonUnited Kingdom

Personalised recommendations