Educational Data Mining in Practice Literature Review

Abstract

Educational Data Mining (EDM) is an evolving field with a suite of computational and psychological methods for understanding how students learn. Applying Data Mining methods to education data help us to resolve educational investigation issues. The growth of education data offers some unique advantages as well as some new challenges for education study. Some of the challenges are an improvement of student models, identify domain structure model, pedagogical support and extend educational theories. The main objective of this paper is to present the capabilities of data mining in the context of the higher educational system and their applications and progress, through a survey of literature and the classification of articles. We observed the works on investigational situation studies showed in the EDM during the recent past, in addition, we have introduced three data models based on descriptive and predictive data mining techniques. This is oriented towards students in order to recommend learners’ activities, resources, suggest path pruning and shortening or simply links that would favor and improve their learning or to educators in order to get more objective feedback for instruction.