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NetLearn: Social Network Analysis and Visualizations for Learning

by: Mohamed Amine Chatti, Matthias Jarke, Theresia Devi Indriasari, and Marcus Specht

In: Learning in the Synergy of Multiple Disciplines, Proceedings of the EC-TEL 2009, Vol. 5794 Berlin/Heidelberg: Springer (October 2009) .

Abstract

The most valuable and innovative knowledge is hard to find, and it lies within distributed communities and networks. Locating the right community or person who can provide us with exactly the knowledge that we need and who can help us solve exactly the problems that we come upon, can be an efficient way to learn forward. In this paper, we present the details of NetLearn; a service that acts as a knowledge filter for learning. The primary aim of NetLearn is to leverage social network analysis and visualization techniques to help learners mine communities and locate experts that can populate their personal learning environments.

BibTeX record

@inproceedings{chatti2009netlearn,
  abstract = {The most valuable and innovative knowledge is hard to find, and it lies within distributed communities and networks. Locating the right community or person who can provide us with exactly the knowledge that we need and who can help us solve exactly the problems that we come upon, can be an efficient way to learn forward. In this paper, we present the details of NetLearn; a service that acts as a knowledge filter for learning. The primary aim of NetLearn is to leverage social network analysis and visualization techniques to help learners mine communities and locate experts that can populate their personal learning environments.},
  added-at = {2009-09-25T10:36:23.000+0200},
  address = {Berlin/Heidelberg},
  author = {Chatti, Mohamed Amine and Jarke, Matthias and Indriasari, Theresia Devi and Specht, Marcus},
  biburl = {http://www.bibsonomy.org/bibtex/2e5a59b3fcd1b27be70f7d836b42611f5/ectel09},
  booktitle = {Learning in the Synergy of Multiple Disciplines, Proceedings of the EC-TEL 2009},
  editor = {Cress, U. and Dimitrova, V. and Specht, M.},
  interhash = {947b3f9b0ce452e054e2e0aa71e6400e},
  intrahash = {e5a59b3fcd1b27be70f7d836b42611f5},
  keywords = {analysis datamining ectel2009 fullPapers learning network social social-network social_network visualisation visualization web2.0},
  month = {October},
  paperid = {1095},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  timestamp = {2009-09-25T10:36:23.000+0200},
  title = {NetLearn: Social Network Analysis and Visualizations for Learning},
  topic = {Full Papers},
  volume = 5794,
  year = 2009
}

Endnote record

%0 Conference Paper
%1 chatti2009netlearn
%A Chatti, Mohamed Amine
%A Jarke, Matthias
%A Indriasari, Theresia Devi
%A Specht, Marcus
%B Learning in the Synergy of Multiple Disciplines, Proceedings of the EC-TEL 2009
%C Berlin/Heidelberg
%D 2009
%E Cress, U.
%E Dimitrova, V.
%E Specht, M.
%I Springer
%K 
%T NetLearn: Social Network Analysis and Visualizations for Learning
%V 5794
%X The most valuable and innovative knowledge is hard to find, and it lies within distributed communities and networks. Locating the right community or person who can provide us with exactly the knowledge that we need and who can help us solve exactly the problems that we come upon, can be an efficient way to learn forward. In this paper, we present the details of NetLearn; a service that acts as a knowledge filter for learning. The primary aim of NetLearn is to leverage social network analysis and visualization techniques to help learners mine communities and locate experts that can populate their personal learning environments.