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Artificial Intelligence Review
Published in: Artificial Intelligence Review 4/2015

01-12-2015

Recommender systems in e-learning environments: a survey of the state-of-the-art and possible extensions

Authors: Aleksandra Klašnja-Milićević, Mirjana Ivanović, Alexandros Nanopoulos

Published in: Artificial Intelligence Review | Issue 4/2015

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Abstract

With the development of sophisticated e-learning environments, personalization is becoming an important feature in e-learning systems due to the differences in background, goals, capabilities and personalities of the large numbers of learners. Personalization can achieve using different type of recommendation techniques. This paper presents an overview of the most important requirements and challenges for designing a recommender system in e-learning environments. The aim of this paper is to present the various limitations of the current generation of recommendation techniques and possible extensions with model for tagging activities and tag-based recommender systems, which can apply to e-learning environments in order to provide better recommendation capabilities.
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Metadata
Title
Recommender systems in e-learning environments: a survey of the state-of-the-art and possible extensions
Authors
Aleksandra Klašnja-Milićević
Mirjana Ivanović
Alexandros Nanopoulos
Publication date
01-12-2015
Publisher
Springer Netherlands
Published in
Artificial Intelligence Review / Issue 4/2015
Print ISSN: 0269-2821
Electronic ISSN: 1573-7462
DOI
https://doi.org/10.1007/s10462-015-9440-z

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