Advertisement

Collaborative User Tracking for Community Organization on Blogosphere: A Case Study of eLearning@BlogGrid

  • Jason J. Jung
  • Inay Ha
  • Supratip Ghose
  • Geun-Sik Jo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4256)

Abstract

The aim of this study is to recommend relevant information to users by organizing user communities on electronic learning environment. In this paper, we propose a weblog-based approach to modeling users during collaborative learning process. Thereby, we formulate user behaviors on blogosphere, e.g., posting articles, linking to neighbors, and interactions between neighbors. These user models are capable of being compared with others to quantify similarities between users. We apply co-occurrence analysis methods. In this study, we deploy BlogGrid platform to support information pushing service to students. Through our experimental results, we found out that average weighting measurement scheme with co-occurrence patterns from responding (e.g., comments and trackback) activities is the most significant patterns for information pushing on collaborative learning.

Keywords

Collaborative Learning Community Organization Heuristic Function User Context Electronic Learning 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Downes, S.: E-learning 2.0. eLearn Magazine 2005(10), 1 (2005)CrossRefGoogle Scholar
  2. 2.
    Rosenbloom, A.: The blogosphere. Communications of ACM 47(12), 31–33 (2004)CrossRefGoogle Scholar
  3. 3.
    Blood, R.: How blogging software reshapes the online community. Communications of the ACM 47(12), 53–55 (2004)CrossRefGoogle Scholar
  4. 4.
    Higgins, C.J., Reeves, L., Byrd, E.: Interactive online journaling: a campus-wide implementation of blogging software. In: Proceedings of the 32nd Annual ACM SIGUCCS conference on User services (SIGUCCS 2004), pp. 139–142. ACM Press, New York (2004)CrossRefGoogle Scholar
  5. 5.
    Xu, W., Kreijns, K., Hu, J.: Designing social navigation for a virtual community of practice. In: Pan, Z., Aylett, R.S., Diener, H., Jin, X., Göbel, S., Li, L. (eds.) Edutainment 2006. LNCS, vol. 3942, pp. 27–38. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    Schmidt, A., Winterhalter, C.: User context aware delivery of e-learning material: Approach and architecture. Journal of Universal Computer Science 10(1), 28–36 (2004)Google Scholar
  7. 7.
    Nardi, B.A., Schiano, D.J., Gumbrecht, M., Swartz, L.: Why we blog. Communications of the ACM 47(12), 41–46 (2004)CrossRefGoogle Scholar
  8. 8.
    Jung, J.J.: Semantic preprocessing of web request streams for web usage mining. Journal of Universal Computer Science 11(8), 1383–1396 (2005)Google Scholar
  9. 9.
    Newman, M.E.J.: Fast algorithm for detecting community structure in networks. Physical Review E 69, 66133 (2004)CrossRefGoogle Scholar
  10. 10.
    Jung, J.J., Ha, I., Jo, G.: BlogGrid: Towards an efficient information pushing service on blogspace. In: Zhuge, H., Fox, G.C. (eds.) GCC 2005. LNCS, vol. 3795, pp. 178–183. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  11. 11.
    Jung, J.J., Lee, K.S., Park, S.B., Jo, G.S.: Efficient web browsing with semantic annotation: A case study of product images in e-commerce sites. IEICE - Trans. Inf. Syst. E88-D(5), 843–850 (2005)CrossRefGoogle Scholar
  12. 12.
    Gowda, K.C., Krishna, G.: Agglomerative clustering using the concept of mutual nearest neighbourhood. Pattern Recognition 10(2), 105–112 (1978)MATHCrossRefGoogle Scholar
  13. 13.
    Kojiri, T., Watanabe, T.: Harmony: Web-based adaptive collaborative learning environment. In: Proceedings of International Conference on Computers in Education (ICCE/SchoolNet), pp. 559–566 (2001)Google Scholar
  14. 14.
    Chen, Z., Hu, T., Yu, Y.: Analysis and research about an on-line collaborative learning teams based grids. In: Pan, Z., Aylett, R.S., Diener, H., Jin, X., Göbel, S., Li, L. (eds.) Edutainment 2006. LNCS, vol. 3942, pp. 735–744. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  15. 15.
    Tscherteu, G.: The blogosphere map visualising microcontent dissemination – inspired by maria montessori. In: Hug, T., Lindner, M., Bruck, P.A. (eds.) Proceedings of the Microlearning, pp. 109–120. Innsbruck University Press (2005)Google Scholar
  16. 16.
    Bruns, A., Humphreys, S.: Wikis in teaching and assessment: the M/Cyclopedia project. In: Proceedings of the 2005 international symposium on Wikis (WikiSym 2005), pp. 25–32. ACM Press, New York (2005)CrossRefGoogle Scholar
  17. 17.
    Reinhold, S., Abawi, D.F.: Concepts for extending wiki systems to supplement collaborative learning. In: Pan, Z., Aylett, R.S., Diener, H., Jin, X., Göbel, S., Li, L. (eds.) Edutainment 2006. LNCS, vol. 3942, pp. 755–767. Springer, Heidelberg (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jason J. Jung
    • 1
    • 2
  • Inay Ha
    • 2
  • Supratip Ghose
    • 2
  • Geun-Sik Jo
    • 2
  1. 1.INRIA Rhône-AlpesSaint IsmierFrance
  2. 2.Intelligent E-Commerce Systems Laboratory, School of Computer and Information EngineeringInha UniversityIncheonKorea

Personalised recommendations