Predictive analytics–using massive amounts of historical data to predict future events–is a practice that’s making it easier and faster for colleges to decide which students to enroll and how to get them to graduation. But using data in this way may make decision-making processes harder, not easier. That’s because predictive analytics can aid in discriminatory practices, make institutional practices less transparent, and make vulnerable individuals’ data privacy and security.
In a new paper, The Promise and Peril of Predictive Analytics in Higher Education: A Landscape Analysis, authors Manuela Ekowo and Iris Palmer describe how predictive analytics are used in higher education to identify students who need extra support, steer students in courses they will do well in, and provide digital tools that can customize the learning process for individual students. The paper also outlines the ethical concerns involved in using data to make predictions and its impact on underrepresented students.