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Recommender Systems for Learning

Part of the SpringerBriefs in Electrical and Computer Engineering Book Series

DOI: 10.1007/978-1-4614-4361-2

ISBN: 978-1-4614-4360-5

Publisher: Springer New York - Springer Journals

Aug 28, 2012

Available

Introduction and Background

Manouselis, Nikos; Drachsler, Hendrik; Verbert, Katrien; Duval, Erik

Pages: 1 –20

[In this chapter, we start with a short introduction to the increase that has been witnessed in the past few years in applications of recommender systems at the TEL domain. Then we provide some background on the area of recommender systems, by defining recommender systems and outlining their...
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TEL as a Recommendation Context

Manouselis, Nikos; Drachsler, Hendrik; Verbert, Katrien; Duval, Erik

Pages: 21 –36

[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...
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Survey and Analysis of TEL Recommender Systems

Manouselis, Nikos; Drachsler, Hendrik; Verbert, Katrien; Duval, Erik

Pages: 37 –61

[In this chapter, we present a framework for the analysis of existing recommender systems. Then, we present a detailed analysis of relevant TEL recommender systems along the dimensions defined by our framework.]
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Challenges and Outlook

Manouselis, Nikos; Drachsler, Hendrik; Verbert, Katrien; Duval, Erik

Pages: 63 –76

[This chapter discusses the main challenges that we see as being highlighted from this study. It also outlines the directions of future work that relevant research could take. It concludes with the main contributions and lessons learnt of this work.]

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