Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning

Hendrik Drachsler, Hans G. K. Hummel, Rob Koper

Abstract


This 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 in Learning Networks. Personal recommender systems strongly depend on the context or domain they operate in, and it is often not possible to take one recommender system with a specific purpose from one context and transfer it to another context or domain. The article describes a number of distinctive differences for personalised recommendation to learners when compared to recommendations for consumers. Similarities and differences for informal and formal learning are discussed and used to define the recommendation goal that recommender systems in informal learning networks have to address. The article further suggests an evaluation approach for recommender systems in Learning Networks.

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