A Comparison of Data-Driven and Data-Centric Architectures using E-Learning Solutions

ABSTRACT

To minimize the pace of transmission of the novel Covid-19 virus, institutions have shifted to e-learning to substitute lectures and assessments in the classroom without being fully ready and technologically equipped. As a result, institutions must identify and employ the most suitable data architecture for their universities. For this purpose, this study first identifies 109 e-learning solution use cases, collects their 983 user reviews from the e-learning industry, and categorizes them according to their data architectures for appropriate comparison using the developed conceptual framework. The finding shows that data-driven and data-centric were the only architectures used by e-learning solutions, it further recommends data-centric as the best suited for e-learning. © 2022 IEEE.