Track: Modeling and Simulation

Abstract

Big data is a highly innovative technology that provides economic and social benefits for all segments of society. Big data analysis offers significant savings and new possibilities by moving the decision support of many critical areas of knowledge to an upper dimension in many different industries such as banks, energy companies, the pharmaceutical industry, health services, public services, etc. Even though there are few studies about big data applications in education, big data will revolutionize the learning industry in the coming years. Therefore, this study deals with big data applications in the education sector, especially in predicting student behavior. This paper investigated the existing literature for big data usage for predicting students' behavior in the education industry. Then it proposed a specific methodology for determining students who are likely to drop out early from the university. Because the increasing graduation rate is the strategic goal of any public or private educational institution, it is believed that with the proposed model, they can take the right action at the right time to reduce the drop-out rate and increase the graduation rate.