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.
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Chatti, M.A., Jarke, M., Indriasari, T.D., Specht, M. (2009). NetLearn: Social Network Analysis and Visualizations for Learning. In: Cress, U., Dimitrova, V., Specht, M. (eds) Learning in the Synergy of Multiple Disciplines. EC-TEL 2009. Lecture Notes in Computer Science, vol 5794. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04636-0_30
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DOI: https://doi.org/10.1007/978-3-642-04636-0_30
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