Title: Big data: a distributed storage and processing for online learning systems

Authors: Karim Dahdouh; Ahmed Dakkak; Lahcen Oughdir

Addresses: Engineering Sciences Laboratory, FPT, Sidi Mohamed Ben Abdellah University, Taza, Morocco ' Engineering Sciences Laboratory, FPT, Sidi Mohamed Ben Abdellah University, Taza, Morocco ' Engineering Sciences Laboratory, FPT, Sidi Mohamed Ben Abdellah University, Taza, Morocco

Abstract: The new information and communication technologies have changed the way of teaching and learning. In particular, the big data technology that has recently been developed to overcome the limitations of traditional systems of storage, processing, and analysis. It offers a rich set of new technologies and techniques to bring solutions to various educational problems such as the courses recommendation engine, the prediction of learner behaviour, etc. This article presents the big data paradigm, its components, technologies, and characteristics. It proposes an approach for incorporating big data, online learning systems, and cloud computing in order to enhance the efficiency of the distance learning environment. Also, it provides a methodology to store and process the data produced by online learning platforms using advanced big data technologies and tools. Moreover, it explores the advantages and benefits that big data offer to students, teachers and online learning professionals.

Keywords: e-learning; online learning; big data; cloud computing; learner; learning management systems; Hadoop; HDFS; Yarn; Spark.

DOI: 10.1504/IJCISTUDIES.2019.102536

International Journal of Computational Intelligence Studies, 2019 Vol.8 No.3, pp.192 - 205

Received: 19 Feb 2018
Accepted: 08 Jul 2018

Published online: 26 Sep 2019 *

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