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Title: Recommendations for learners are different: Applying memory-based recommender system techniques to lifelong learning
Authors: Drachsler, Hendrik
Hummel, Hans
Koper, Rob
Keywords: technology-enhanced learning
lifelong learning
personal recommender systems
collaborative filtering
content-based recommendation
user profiling
Issue Date: 23-Jul-2007
Abstract: This article argues why personal recommender systems in technology-enhanced learning have to be adjusted to the specific character of learning. Personal recommender systems are strongly depend on the context or domain they operate in, and it is often not possible to take one recommender system from one context and transfer it to another context or domain. The article describes a number of distinct differences for personalized recommendation to consumers in contrast to recommendations to learners. Similarities and differences are translated into specific demands for learning and specific requirements for personal recommendation systems. Therefore, it analyses memory-based recommendation techniques for their usefulness to provide pedagogically reasonable recommendations to learners.
Description: Drachsler, H., Hummel, H. G. K., & Koper, R. (2007). Recommendations for learners are different: applying memory-based recommender system techniques to lifelong learning. Paper presented at the SIRTEL workshop at the EC-TEL 2007 Conference. September, 17-20, 2007, Crete, Greece.
Appears in Collections:1. TENC: Publications and Preprints
Keur der Wetenschap

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