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Please use this identifier to cite or link to this item: http://hdl.handle.net/1820/937

Title: Personal recommender systems for learners in lifelong learning: requirements, techniques and model
Authors: Drachsler, Hendrik
Hummel, Hans
Koper, Rob
Keywords: lifelong learning networks
learning technology
personal recommender systems
collaborative filtering
content-based recommendation
user profiling
Issue Date: 12-Apr-2007
Abstract: This article argues for the need of personal recommender systems in lifelong learning networks that provide learners advice on suitable learning activities to follow. Existing recommender systems and recommendation techniques used for consumer products and other contexts are assessed on their suitability for providing navigation support in a learning network. Similarities and differences are translated into specific demands for learning and specific requirements for recommendation techniques. We propose a combination of memory-based recommendation techniques that appear suitable to realize personalized recommendation on learning activities in the context of e-learning. An initial model for the design of such systems in learning networks and a roadmap for their further development are presented.
Description: Drachsler, H., Hummel, H. G. K., & Koper, R. (2008). Personal recommender systems for learners in lifelong learning: requirements, techniques and model. International Journal of Learning Technology, 3(4), 404-423.
URI: http://hdl.handle.net/1820/937
Appears in Collections:1. TENC: Publications and Preprints
1. LN: Publications and Preprints
Keur der Wetenschap

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