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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

LASyM: A Learning Analytics System for MOOCs

Author 1: Yassine Tabaa
Author 2: Abdellatif Medouri

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2013.040516

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 5, 2013.

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Abstract: Nowadays, the Web has revolutionized our vision as to how deliver courses in a radically transformed and enhanced way. Boosted by Cloud computing, the use of the Web in education has revealed new challenges and looks forward to new aspirations such as MOOCs (Massive Open Online Courses) as a technology-led revolution ushering in a new generation of learning environments. Expected to deliver effective education strategies, pedagogies and practices, which lead to student success, the massive open online courses, considered as the “linux of education”, are increasingly developed by elite US institutions such MIT, Harvard and Stanford by supplying open/distance learning for large online community without paying any fees, MOOCs have the potential to enable free university-level education on an enormous scale. Nevertheless, a concern often is raised about MOOCs is that a very small proportion of learners complete the course while thousands enrol for courses. In this paper, we present LASyM, a learning analytics system for massive open online courses. The system is a Hadoop based one whose main objective is to assure Learning Analytics for MOOCs’ communities as a mean to help them investigate massive raw data, generated by MOOC platforms around learning outcomes and assessments, and reveal any useful information to be used in designing learning-optimized MOOCs. To evaluate the effectiveness of the proposed system we developed a method to identify, with low latency, online learners more likely to drop out

Keywords: Cloud Computing; MOOCs; Hadoop; Learning Analytics.

Yassine Tabaa and Abdellatif Medouri, “LASyM: A Learning Analytics System for MOOCs ” International Journal of Advanced Computer Science and Applications(IJACSA), 4(5), 2013. http://dx.doi.org/10.14569/IJACSA.2013.040516

@article{Tabaa2013,
title = {LASyM: A Learning Analytics System for MOOCs },
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2013.040516},
url = {http://dx.doi.org/10.14569/IJACSA.2013.040516},
year = {2013},
publisher = {The Science and Information Organization},
volume = {4},
number = {5},
author = {Yassine Tabaa and Abdellatif Medouri}
}


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