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ERIC Number: EJ1192447
Record Type: Journal
Publication Date: 2018-Nov
Pages: 18
Abstractor: As Provided
ISSN: ISSN-1360-2357
Big Data for Online Learning Systems
Dahdouh, Karim; Dakkak, Ahmed; Oughdir, Lahcen; Messaoudi, Fayçal
Education and Information Technologies, v23 n6 p2783-2800 Nov 2018
In recent years, Online learning systems have met big challenges, especially due to rapid changes in technology, the gigantic amounts of data to be stored and manipulated, the large number of learners and the diversity of educational resources. As a result, e-learning platforms must change their mechanisms for data processing and storage to be smarter. In this context, big data is the relevant paradigm for the distributed and parallel processing of large data sets through thousands of clusters. It also offers a rich set of tools in order to improve data collection, storage, analysis, processing, optimization, and visualization. This article introduces the big data concept, its characteristics, and focuses in particular on the integration of it in a computing environment for human learning dedicated to online learning systems, and how the new methods, technologies, and tools of big data can enhance the future of online learning. Moreover, it proposes an approach for smoothly adapting the traditional e-learning systems to be suitable for big data ecosystems in cloud computing. Furthermore, it provides a methodology and architecture to incorporate the e-learning storage and computing in a Hadoop software library. Finally, the benefits and advantages associated with implementing big data in future online learning systems are discussed.
Springer. Available from: Springer Nature. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail:; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A