ABSTRACT
This chapter provides a comprehensive and unified view of data analytics and educational data mining, and how they are used to improve student learning and engagement. The chapter begins with a discussion of distinctions and similarities between Data Analytics (DA), Data Mining (DM), Educational Data Mining (EDM), Machine Learning (ML), and Learning Analytics (LA). The six functional facets of DA are also described, and an overview of machine learning and data mining approaches as a backdrop for Educational Data Mining and Learning Analytics is provided. Open source tools and resources available for developing Learning Analytics systems are also listed.
