How can data and analytics be used to make predictions about student engagement and student retention in higher education?
In Session features interviews with KPMG’s Higher Education professionals that are working with universities and colleges that are being tested by the rapid pace of change.
In this issue, Pete Irwin discusses how data and analytics can be used to make predictions about student engagement and student retention.
With over 15 years of analytics, IT, and business systems consulting experience, Pete leads teams that leverage data to develop and implement solutions in the areas of predictive analytics and decision intelligence. He recently started working with universities to design solutions that integrate large volumes of data with external signals to make predictions around student engagement, time-to-complete, grades, and retention.