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ReMashed – Recommendations for Mash-Up Personal Learning Environments

  • Hendrik Drachsler
  • Dries Pecceu
  • Tanja Arts
  • Edwin Hutten
  • Lloyd Rutledge
  • Peter van Rosmalen
  • Hans Hummel
  • Rob Koper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5794)

Abstract

The following article presents a Mash-Up Personal Learning Environment called ReMashed that recommends learning resources from emerging information of a Learning Network. In ReMashed learners can specify certain Web2.0 services and combine them in a Mash-Up Personal Learning Environment. Learners can rate information from an emerging amount of Web2.0 information of a Learning Network and train a recommender system for their particular needs. ReMashed therefore has three main objectives: 1. to provide a recommender system for Mash-up Personal Learning Environments to learners, 2. to offer an environment for testing new recommendation approaches and methods for researchers, and 3. to create informal user-generated content data sets that are needed to evaluate new recommendation algorithms for learners in informal Learning Networks.

Keywords

recommender system mash-up personalisation personal learning environments MUPPLE informal learning emergence learning networks 

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References

  1. 1.
    Liber, O., Johnson, M.: Personal Learning Environments. Interactive Learning Environments 16, 1–2 (2008)CrossRefGoogle Scholar
  2. 2.
    Wild, F., Kalz, M., Palmer, M. (eds.): Mash-Up Personal Learning Environments. CEUR Workshop Proceedings Maastricht, The Netherlands, vol. 388 (2008)Google Scholar
  3. 3.
    Wild, F., Moedritscher, F., Sigurdarson, S.E.: Designing for Change: Mash-Up Personal Learning Environments. eLearning Papers 9 (2008)Google Scholar
  4. 4.
    Koper, R., Tattersall, C.: New directions for lifelong learning using network technologies. British Journal of Educational Technology 35, 689–700 (2004)CrossRefGoogle Scholar
  5. 5.
    Drachsler, H., Hummel, H., Koper, R.: Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning. Journal of Digital Information 10, 4–24 (2009)Google Scholar
  6. 6.
    Wilson, S., Sharples, P., Griffith, D.: Distributing education services to personal and institutional systems using Widgets. In: Wild, F., Kalz, M., Palmer, M. (eds.) Mash-Up Personal Learning Environments, Proceedings of the 1st MUPPLE workshop. CEUR-Proceedings, Maastricht, The Netherlands,vol. 388 (2008)Google Scholar
  7. 7.
    Shepitsen, A., Gemmell, J., Mobasher, B., Burke, R.: Personalized recommendation in social tagging systems using hierarchical clustering. In: Recommender Systems 2008, pp. 259–266. ACM, New York (2008)Google Scholar
  8. 8.
    Symeonidis, P., Nanopoulos, A., Manolopoulos, Y.: Tag recommendations based on tensor dimensionality reduction. In: Recommender Systems 2008, pp. 43–50. ACM, New York (2008)Google Scholar
  9. 9.
    Garg, N., Weber, I.: Personalized, interactive tag recommendation for flickr. In: Recommender System 2009, pp. 67–74. ACM, New York (2009)Google Scholar
  10. 10.
    Sarwar, B.M., Karypis, G., Konstan, J., Riedl, J.: Recommender systems for large-scale e-commerce: Scalable neighborhood formation using clustering. In: Fifth International Conference on Computer and Information Technology (2002)Google Scholar
  11. 11.
    Herlocker, J.L., Konstan, J.A., Riedl, J.: Explaining collaborative filtering recommendations. In: Proceedings of the 2000 ACM conference on Computer supported cooperative work, pp. 241–250 (2000)Google Scholar
  12. 12.
    Drachsler, H., Hummel, H., Koper, R.: Personal recommender systems for learners in lifelong learning: requirements, techniques and model. International Journal of Learning Technology 3, 404–423 (2008)CrossRefGoogle Scholar
  13. 13.
    Van Setten, M.: Supporting people in finding information. Hybrid recommender systems and goal-based structuring. Telematica Instituut Fundamental Research Series No. 016 (TI/FRS/016) (2005) Google Scholar
  14. 14.
    Drachsler, H., Peccau, D., Arts, T., Hutten, E., Rutledge, L., Van Rosmalen, P., Hummel, H., Koper, R.: ReMashed - An Usability Study of a Recommender System for Mash-Ups for Learning. In: 1st Workshop on Mashups for Learning at the International Conference on Interactive Computer Aided Learning, Villach, Austria (submitted)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Hendrik Drachsler
    • 1
  • Dries Pecceu
    • 2
  • Tanja Arts
    • 2
  • Edwin Hutten
    • 2
  • Lloyd Rutledge
    • 2
  • Peter van Rosmalen
    • 1
  • Hans Hummel
    • 1
  • Rob Koper
    • 1
  1. 1.Centre for Learning Sciences and TechnologiesOpen University of the NetherlandsNetherlands
  2. 2.Computer Science DepartmentOpen University of the NetherlandsHeerlenThe Netherlands

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