Nassim DENNOUNI; Zohra SLAMA; Yvan PETER; Luigi LANCIERI

Recommendation Techniques in Mobile Learning Context: A Review

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Author(s)

Nassim DENNOUNI ^1,* Zohra SLAMA ¹ Yvan PETER ² Luigi LANCIERI ²

1. ISIBA team, EEDIS Laboratory, Djilali Liabes University, Sidi Bel Abbes, Algeria

2. NOCE team, CRISTAL Laboratory, Lille1 University, Lille, France

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2017.10.05

Received: 7 Feb. 2017 / Revised: 20 May 2017 / Accepted: 28 Jun. 2017 / Published: 8 Oct. 2017

Index Terms

Mobile learning, field trip, mobile learning activities, collaborative filtering, recommendation system, Point of Interest, ACO algorithm

Abstract

The objective of this article is to make a bibliographic study on the recommendation of learning activities that can integrate user mobility. This type of recommendation makes it possible to exploit the history of previous visits in order to offer adaptive learning according to the instantaneous position of the learner and the pedagogy of the guide. To achieve this objective, we review the existing literature on the recommendation systems that integrate contexts such as geographic location and training profile. Next, we are interested in the social relationships that users can have between themselves. Finally, we focus on the work of recommending mobile learning activities in the context of scenarios of field trips.

Cite This Paper

Nassim DENNOUNI, Zohra SLAMA, Yvan PETER, Luigi LANCIERI, "Recommendation Techniques in Mobile Learning Context: A Review", International Journal of Modern Education and Computer Science(IJMECS), Vol.9, No.10, pp. 37-46, 2017. DOI:10.5815/ijmecs.2017.10.05

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