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

• Published in: IEEE access 2018-01, Vol.6, p.39117-39138
• Main Authors: Moubayed, Abdallah, Injadat, Mohammadnoor, Nassif, Ali Bou, Lutfiyya, Hanan, Shami, Abdallah
• Format: Article
• Language: English
• Subjects: Computer aided instruction; Computers; Data analysis; data analytics; Data collection; Distance learning; E-learning; Electronic learning; Internet; Machine learning; Online instruction
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2018.2851790

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.