Titlebook: Recommender Systems for Learning; Nikos Manouselis,Hendrik Drachsler,Erik Duval Book 2013 The Author(s) 2013 Recommender systems.TEL datas

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Nikos Manouselis,Hendrik Drachsler,Erik DuvalIncludes supplementary material:

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Introduction and Background,pes. A comparison with relevant work in TEL is tried, particularly focusing on adaptive educational hypermedia, learning networks, educational data mining, and learning analytics. A discussion on their similarities and differences is also made, so that relevant work can be better positioned in the TEL research landscape.

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TEL as a Recommendation Context, that capture contextual learner interactions with tools and resources in TEL settings. These data sets can be used for a wide variety of research purposes, including experimental comparison of the performance of recommendation algorithms for learning.

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Book 2013ity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.

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Introduction and Background,ms at the TEL domain. Then we provide some background on the area of recommender systems, by defining recommender systems and outlining their basic types. A comparison with relevant work in TEL is tried, particularly focusing on adaptive educational hypermedia, learning networks, educational data mi

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