E-Learning: Challenges and Research Opportunities Using Machine Learning Data Analytics

Abdallah Moubayed*, Mohammadnoor Injadat, Ali Bou Nassif, Hanan Lutfiyya, Abdallah Shami

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

134 Scopus citations

Abstract

With the proliferation of technology, the field of e-learning has garnered significant attention in recent times. This is because it has allowed users from around the world to learn and access new information. This has added to the growing amount of collected data that is already being generated through different devices and sensors employed around the world. This has led to the need to analyze collected data and extract useful information from it. Machine learning (ML) and data analytics (DA) are proposed techniques that can help extract information and find valuable patterns within the collected data. In this paper, the field of e-learning is investigated in terms of definitions and characteristics. Moreover, the various challenges facing the different participants within this process are discussed. In addition, some of the works proposed in the literature to tackle these challenges are presented. Then, a brief survey about some of the most popular ML and DA techniques is given. Finally, some of the research opportunities available that employ such techniques are proposed to give insights into the areas that merit further exploration and investigation.

Original languageEnglish
Article number8417405
Pages (from-to)39117-39138
Number of pages22
JournalIEEE Access
Volume6
DOIs
StatePublished - 20 Jul 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Keywords

  • E-learning
  • data analytics
  • machine learning

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering

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