TEL as a Recommendation Context

  • Nikos Manouselis
  • Hendrik Drachsler
  • Katrien Verbert
  • Erik Duval
Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)


In this chapter, we define the TEL recommendation problem and identify TEL recommendation goals. More specifically, we reflect on user tasks that are supported in TEL settings, and how they compare to typical user tasks in other recommender systems. Then, we present an analysis of existing data sets 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.


Recommender System Resource Description Framework Knowledge Level Learning Resource Recommendation Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© The Authors 2013

Authors and Affiliations

  • Nikos Manouselis
    • 1
  • Hendrik Drachsler
    • 2
  • Katrien Verbert
    • 3
  • Erik Duval
    • 3
  1. 1.Agro-Know TechnologiesAthensGreece
  2. 2.Open University of the NetherlandsHeerlenThe Netherlands
  3. 3.KU LeuvenLeuvenBelgium

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