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Title: Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning
Authors: Drachsler, Hendrik
Hummel, Hans
Koper, Rob
Keywords: information discovery
usability of digital information
technology-enhanced learning
lifelong learning
personal recommender
collaborative filtering
learner profiling
Issue Date: 3-Mar-2008
Abstract: The following article addresses open questions of the discussions in the first SIRTEL workshop at the EC-TEL conference 2007. It argues why personal recommender systems have to be adjusted to the specific characteristics of learning to support lifelong learners. Personal recommender systems 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. It further suggests an evaluation approach for recommender systems in technology-enhanced learning.
Description: Drachsler, H., Hummel, H. G. K., & Koper, R. (2009). Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning. Journal of Digital Information, 10(2), 4-24.
Appears in Collections:1. TENC: Publications and Preprints
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