Smart Learning Recommenders extend traditional Learning Management Systems
Smart Learning Recommenders extend traditional Learning Management Systems  istock/ Izabela Habur

Award for paper on Smart Learning Recommender

News from June 02, 2016

Two papers of our business unit “Future Applications and Media – FAME” on Smart Learning Recommender (SLR) were awarded and nominated at different conferences in April and May 2016. SLR extends traditional Learning Management Systems with the time value in order to respect the changing knowledge level in a continuous time interval.

The 8th IARIA International Conference on Mobile, Hybrid, and On-line Learning (eLmL) in April 2016 in Venice awarded the paper “The Smart Learning Approach – A Mobile Learning Companion Application" as best paper at the conference. Moreover, at the 29th AAAI International Flairs Conference in Florida in May 2016, the poster presentation of the paper “Smart-Learning: Time-Dependent Context-Aware Learning Object Recommendations" was nominated for the best poster award.
Learning Management Systems calculate the relevance score of learning objects to offer personalized training for students. SLR extends the traditional user-item-matrix of Learning Management Systems with the time value. Students can keep track of their individual predicted knowledge level on different learning objects at every point in time. Therefore, SLR also respects the changing knowledge level in a continuous time interval. The analysis at several points in time results in an accurate representation of the different factors and weights.

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