Re-engineering higher education learning and teaching business processes for Big Data analytics

Big Data analytics need to be combined with higher education business processes to improve course structure and delivery to help students who have struggled to stay in the course by identifying their engagement and correlation with different variables such as access to documents; assignment submission etc. Online activity data can be used to keep students on track all the way to graduation and universities struggling to understand how to lower dropout rates and keep students on track during their study program. In this paper we discuss how Big Data analytics can be combined with higher education business processes using re-engineering for structured data, unstructured data, and external data. In order to achieve this objective, we investigate the core business processes of learning and teaching and define a re-engineered higher education business process model.