Predicting Social Media Classrooms Efficiency using Educational Data Mining

Abstract—In several fields, including higher education and scholarly practices, social media has a critical role to play. Over the years, exploring the facilities available for emerging technology for universities, educators, and students has increasingly become important for all of us employed in higher education. The Educational Data Mining (EDM) is considered as one of the new fields that is concerned with the expansion of the different techniques aiming to discover information from educational environments either over the traditional or distance learning. Over the last decade, increasing research interests in the use of data mining in education have been reported with a focus on various aspects of the educational process. Therefore, this review aims to construct a system to predict the efficacy of social media classrooms by applying input from students with Data Mining Techniques (DMT). The system consists of three main phases to test the developed prediction model, which are the pre-processing phase, the data mining phase, and the evaluation phase. Reasonable results are shown by the proposed model statistics.
Keywords — Classroom; Social Media; Data Mining Techniques; Decision Tree; Prediction Model