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An overview of usage data formats for recommendations in TEL

: Niemann, K.; Scheffel, M.; Wolpers, M.

Volltext (PDF; )

Manouselis, N.; Drachsler, H.; Verbert, K.; Santos, O.C.:
RecSysTEL 2012, Recommender Systems in Technology Enhanced Learning : Proceedings of the 2nd Workshop on Recommender Systems in Technology Enhanced Learning 2012. In conjunction with the 7th European Conference on Technology Enhanced Learning (EC-TEL 2012), Saarbrücken, Germany, September 18-19, 2012
Saarbrücken, 2012 (CEUR Workshop Proceedings 896)
URN: urn:nbn:de:0074-896-3
Workshop on Recommender Systems in Technology Enhanced Learning (RecSysTEL) <2, 2012, Saarbrücken>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer FIT ()

Recently, a number of usage data representations have emerged that enable the representation of user activities across system and application boundaries. Based on these user activity data, systems can adapt to the users and provide personalized information. A lot of usage data representation formats are already successfully used in real world applications. However, dependent on the purpose, the formats show different advantages and disadvantages one must consider when choosing a format for a system. In this paper, we will present the four most commonly used data representations, namely Contextualized Attention Metadata, Activity Streams, Learning Registry Paradata and NSDL to alleviate the selection of a suitable format.