Data-Driven Decision-Making and Its Impacts on Education Quality in Developing Countries: A Systematic Review

Data-driven decision-making (DDDM) technologies are increasingly being utilized, aiming to enhance education quality. However, the implementation of these technologies in developing countries is at an early stage, and evidence regarding their impacts on education quality remains limited. Therefore, this paper examines articles that explore the implementation of DDDM technologies and their effects on education quality. We employed PRISMA to select relevant articles published between 2018 and 2022 from ERIC, Science Direct, IEEE Xplore, and Google Scholar databases. A total of 26 studies were identified, showcasing various DDDM technologies employed in developing countries' educational sectors, including learning management systems (LMS), learning analytics tools, massive open online course (MOOC) platforms, e-Iearning tools, e-assessment systems, recommender and guidance systems, data-driven approaches, personal response systems, collaborator tools, and educational management information systems (EMIS). The adoption of these technologies has shown positive effects such as improved academic performance, timely dissemination of information, enhanced collaboration, improved communication, better decision-making processes, enhanced ICT skills, improved monitoring, immediate feedback provision, and efficient time management. Although DDDM technologies have been more prevalent in higher education settings, their effective utilization in the educational sector of developing countries has not been fully realized. Nonetheless, the adoption and diversification of DDDM technologies in education hold substantial potential for the future. Further research should focus on quantifying the contribution of DDDM technologies to educational quality through rigorous statistical analysis. Additionally, it is essential to explore any potential adverse effects that DDDM may have on educational quality in developing countries.