Work place: University of the West of Scotland, Paisley, United Kingdom
E-mail: olugbenga.adejo@uws.ac.uk
Website:
Research Interests: Human-Computer Interaction, Computer systems and computational processes, Computational Learning Theory, Application Security, Data Mining, Data Structures and Algorithms
Biography
Olugbenga W. Adejo holds a PhD in Computing Science from University of the West of Scotland in Paisley United Kingdom. Previously he received B.Sc. in Agricultural Economics at the University of Calabar, Nigeria, Advanced/Higher Diploma in Computer Science North Glasgow College as well as MSc in Information Technology (Application Development) from University of Sunderland, United Kingdom. His research focuses on Data Mining application, Big data analytic, learning analytic, Predictive analytics, Human Computer Interaction, and Business Modelling. He has written interdisciplinary papers on application of Information technology to agriculture, e-health and commerce as well as Learning Analytic in Education.
He is a member of the Association of Computer Machinery (ACM) and he currently serves as member of program and review committee of various International conferences around the world.
By Olugbenga W. Adejo Isaiah Ewuzie Abel Usoro Thomas Connolly
DOI: https://doi.org/10.5815/ijitcs.2018.04.01, Pub. Date: 8 Apr. 2018
In recent years, the advancement in internet technologies has greatly altered the learning landscape, thus, a shift from traditional methods of learning to internet based learning platforms. E-learning, m-learning and cloud are some of the most powerful responses to these growing technological shift by the education sectors. Their impact and benefits cannot be over-emphasized with regard to making learning accessible, affordable, available and convenient. In addition, the use of cloud technology has made the world of education more integrated, networked and composite. This makes e-learning and m-learning as highly effective as the conventional method of learning delivery. However, despite these advantages, the security and the protection of learners’ data on this cloud platform have been some of the major challenges to m-learning effective implementation and use.
This paper discusses the various benefits of the using m-learning platform and cloud infrastructure in higher education. It also examines the vulnerabilities of the platform as well as other security and privacy challenges regarding the effective implementation of m-learning in cloud infrastructure environment. Finally, it proposes a detailed data protection and security framework that is needed for addressing these issues. It is expected that the proposed framework when fully implemented, will bring about necessary solution to issues relating to the security and data protection of m-learners in cloud computing environment, increase trust in the use of the system as well as enhance the m-learning platforms.
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