Abstract
This chapter explores the current state of data aggregation within higher education—in particular, the theoretical understandings of the role Big Data plays or can play in addressing the challenges currently facing institutions of higher education. It draws upon emergent literature in Big Data and discusses ways to better utilize the growing data available from various sources within an institution to help understand the complexity of influences on student-related outcomes, teaching, and the what-if questions for research experimentation. The chapter presents opportunities and challenges associated with the implementation of Big Data analytics in higher education. Academic analytics provides overall information about what is happening in a specific program and how to address performance challenges. Learning analytics is concerned with the measurement, collection, and analysis and reporting of data about learners and their contexts for purposes of understanding and optimizing learning and the environments in which it occurs.