Institutions are increasingly turning to predictive analytics to help determine if students will enroll, and if so, whether or not they’ll need support to stay on track for graduation. But this data use begs the question–are decision-makers using the data ethically?
The pressure to recruit and retain students grows daily in higher education, where institutions strive to ensure students earn diplomas.
Predictive analytics–analyzing past student data to predict various things about current and prospective students–can help institutions meed enrollment and financial goals, according to a new policy paper from New America. Because without ethical practices, the use of student data could end up hurting students’ academic progress instead of helping it.
“For example, without a clear plan in place, an institution could use predictive analytics to justify using fewer resources to recruit low-income students because their chances of enrolling are less sure than for more affluent prospective students,” according to the report, authored by Manuela Ekowo and Iris Palmer.
(Next page: 5 guiding principles of predictive analytics)
Laura Ascione is the Editorial Director at eSchool Media. She is a graduate of the University of Maryland's prestigious Philip Merrill College of Journalism. Latest posts by Laura Ascione (see all) - Weak tech could push students, faculty to other institutions - April 13, 2026
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- Weak tech could push students, faculty to other institutions - April 13, 2026
- 13 predictions about edtech, innovation, and–yes–AI in 2026 - January 1, 2026
- 5 essential dimensions of AI literacy - December 12, 2025