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Recommendation Systems for Personalized Technology-Enhanced Learning

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Ubiquitous Learning Environments and Technologies

Part of the book series: Lecture Notes in Educational Technology ((LNET))

Abstract

From e-commerce to e-learning, recommendation systems have given birth to an important and thriving research niche and have been deployed in a variety of application areas over the last decade. In particular, in the technology-enhanced learning (TEL) field, recommendation systems have attracted increasing interest, especially with the rise of educational data mining and big data learning analytics. Generally, TEL recommendation systems are used to support learners in locating relevant educational content according to their profiles. These systems may involve several phases, such as data acquisition and preparation, modeling, and recommendation computation, phases, which together, can describe a TEL recommendation system and distinguish it from others. However, such a description needs to be expanded and generalized in order to cover most of the TEL recommendation systems, especially, in the context of anywhere and anytime learning based on various Web-based learning environments, including Learning Object Repository (LOR), Open Courseware (OCW), Open Educational Resources (OER), Learning Management Systems (LMS), Massive Open Online Courses (MOOC), Educational Widgets, Educational Mobile applications, etc. In this chapter, we provide a generic meta-level framework for a common description of TEL recommendation systems. Then, we present an analysis of several existing TEL recommendation systems with respect to our defined framework.

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Authors and Affiliations

  1. Technologies of Information and Communication Lab, University of Tunis, 5, Avenue Taha Hussein, B.P. 56, Bab Menara, 1008, Tunis, Tunisia

    Mohamed Koutheaïr Khribi & Mohamed Jemni

  2. Knowledge Discovery and Web Mining Lab, Department of Computer Engineering and Computer Science, Speed School of Engineering, University of Louisville, Louisville, KY, 40292, USA

    Olfa Nasraoui

Authors
  1. Mohamed Koutheaïr Khribi
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  2. Mohamed Jemni
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  3. Olfa Nasraoui
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Correspondence to Mohamed Koutheaïr Khribi .

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Editors and Affiliations

  1. Athabasca University, Edmonton, Alberta, Canada

    Kinshuk

  2. Faculty of Education Research, Beijing Normal University, Beijing, China

    Ronghuai Huang

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Khribi, M.K., Jemni, M., Nasraoui, O. (2015). Recommendation Systems for Personalized Technology-Enhanced Learning. In: Kinshuk, ., Huang, R. (eds) Ubiquitous Learning Environments and Technologies. Lecture Notes in Educational Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44659-1_9

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  • DOI: https://doi.org/10.1007/978-3-662-44659-1_9

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