ADL-MOOC: Adaptive learning through big data analytics and data mining algorithms for MOOCS

Abstract

Massive Open Online Courses (MOOCs) have had an impact in current higher education as an online phenomenon gathering momentum over the past couple of years. However, one of the major challenges for MOOCs is capitalizing their potential as a tremendous data source for adaptive learning, whose large datasets growing exponentially are size-wise up to what has been recently named as “Big Data”. In this paper, we present a specific proof-of-concept oriented approach for enriching adaptive learning by applying Big Data Analytics and Data Mining algorithms for MOOCs in order to facilitate subject- and context-sensitive teaching and learning experiences, which results in an innovative technologyenhanced learning solution for intuitive and personalised interactions of students and teachers with educational contents, tools and data.