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Recommender systems provide users with content they might be interested in. Conventionally, recommender systems are evaluated mostly by using prediction accuracy metrics only. But, the ultimate goal of a recommender system is to increase user satisfaction.
Now that the “the only constant is change” in society, our capacity to engage with novel challenges is of first order importance. What are the personal dispositions that authentic learning needs to cultivate, and can we make these assessable and visible to learners and educators?
S. Wang, A. Isaac, L. der Meij, and S. Schlobach. Proceedings of the Workshop on Ontology Matching (OM2007) at ISWC/ASWC2007, Busan, South Korea, (November 2007)