Educational Data Analytics and Fog Computing in Education 4.0

Abstract

Universities are generating massive amounts of educational data. Most universities are now focusing on how to harness that data to optimize and visualize it to provide better and more extended education services. Given this scenario, a literature review was used to conduct this study guided by the following objectives: (1) Assess suitable fog computing and educational data analytics architectures; (2) Examine the opportunities offered by fog computing and educational data analytics; (3) Investigate fog computing and educational data analytics challenges; and (4) Examine disruptions and future directions of these technologies in Education 4.0. The study concludes that institutions must use integrated data analytics techniques and distributed technology systems to make decisions about administration, resource allocation, student retention, performance, and improvement strategies. The study also identified the challenges of using fog computing and educational data analytics and concludes that education 4.0 is a learning style that is aligned with the fourth industrial revolution, requiring transformational learning readiness.