Open Access

Educational Data Mining and Learning Analytics: differences, similarities, and time evolution

  • Laura Calvet Liñán1Email author and
  • Ángel Alejandro Juan Pérez1
International Journal of Educational Technology in Higher Education201512:12030098

https://doi.org/10.7238/rusc.v12i3.2515

Received: 15 February 2015

Accepted: 15 May 2015

Published: 15 July 2015

Abstract

Technological progress in recent decades has enabled people to learn in different ways. Universities now have more educational models to choose from, i.e., b-learning and e-learning. Despite the increasing opportunities for students and instructors, online learning also brings challenges due to the absence of direct human contact. Online environments allow the generation of large amounts of data related to learning/teaching processes, which offers the possibility of extracting valuable information that may be employed to improve students’ performance. In this paper, we aim to review the similarities and differences between Educational Data Mining and Learning Analytics, two relatively new and increasingly popular fields of research concerned with the collection, analysis, and interpretation of educational data. Their origins, goals, differences, similarities, time evolution, and challenges are addressed, as are their relationship with Big Data and MOOCs.

Keywords

Online LearningEducational Data MiningLearning AnalyticsBig Data