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Towards a recommender strategy for personal learning environments

Personal learning environments (PLEs) aim at putting the learner central stage and comprise a technological approach towards learning tools, services, and artifacts gathered from various usage contexts and to be used by learners. Due to the varying technical skills and competences of PLE users, recommendations appear to be useful for empowering learners to set up their environments so that they can connect to learner networks and collaborate on shared artifacts by using the tools available. In this paper we examine different recommender strategies on their applicability in PLE settings. After reviewing different techniques given by literature and experimenting with our prototypic PLE solution we come to the conclusion to start with an item-based strategy and extend it with model-based and iterative techniques for generating recommendations for PLEs. (author's abstract)

Identiferoai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:5119
Date07 September 2010
CreatorsMödritscher, Felix
PublisherElsevier B.V.
Source SetsWirtschaftsuniversität Wien
LanguageEnglish
Detected LanguageEnglish
TypeArticle, PeerReviewed
Formatapplication/pdf
RightsCreative Commons: Attribution-Noncommercial-No Derivative Works 3.0 Austria
Relationhttp://dx.doi.org/10.1016/j.procs.2010.08.002, http://epub.wu.ac.at/5119/

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