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Please use this identifier to cite or link to this item: http://hdl.handle.net/1820/3182

Title: PLEM: a Web 2.0 driven Long Tail aggregator and filter for e-learning
Authors: Chatti, Amine Mohamed
Anggraeni
Jarke, Matthias
Specht, Marcus
Maillet, Katherine
Keywords: Personalization
Personal Learning Environment
PLE
social media
Web 2.0
e-Learning 2.0
The
Collective Intelligence
Wisdom of Crowds
Social Filtering
Issue Date: 2-Feb-2011
Abstract: The Personal Learning Environment (PLE) driven approach to learning suggests a shift in emphasis from a teacher driven knowledge-push to a learner driven knowledge-pull learning model. One concern with knowledge-pull approaches is knowledge overload. The concepts of collective intelligence and the Long Tail provide a potential solution to help learners cope with the problem of knowledge overload. Based on these concepts, the paper proposes a filtering mechanism that taps the collective intelligence to help learners find quality in the Long Tail, thus overcoming the problem of knowledge overload. We present theoretical, design, and implementation details of PLEM, a Web 2.0 driven service for personal learning management, which acts as a Long Tail aggregator and filter for learning. The primary aim of PLEM is to harness the collective intelligence and leverage social filtering methods to rank and recommend learning entities.
Description: Chatti, M. A., Anggraeni, Jarke, M., Specht, M., & Maillet, K. (2010). PLEM: a Web 2.0 driven Long Tail aggregator and filter for e-learning. International Journal of Web Information Systems, 6(1), 5–23.
URI: http://hdl.handle.net/1820/3182
Appears in Collections:1. LMedia: Publications and Preprints

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