Educational Data Mining and Learning Analytics: Past, Present and Future

Abstract

Educational data mining and learning analytics have recently emerged as two important fields aimed at rendering e-learning environments more effective. Aim of this study seeks first to reveal the differences between these two fields and then to discuss the future of these concepts by evaluating how they changed throughout history. Educational data mining refers to uncovering the patterns hidden in the big data whilst learning analytics is the use of these patterns to optimize e-learning environments. One of the purposes of the study is to add to the literature on the future trends regarding these concepts. In the very near future, it seems that studies will be performed on EDM and the Industry 4.0 and one of its application areas, “(Internet of Things-IoT)” and EDM has the potential to substantially help researchers in discovering the patterns in the interaction data in the Learning Management Systems and in designing more effective learning environments. The studies on the future of learning analytics are categorized in five main headings: personalization of learning processes, learning design, learning experience design, dashboard design and the Industry 4.0 applications.