By Dian Schaffhauser, Campus Technology
The productive use of predictive analytics in higher education is almost a foregone conclusion. Being able to predict whether a student will enroll in your institution, stay on track in his or her studies or need extra support to succeed seems like just the kind of data that can help colleges and universities meet their enrollment goals, better target recruiting efforts and more strategically apply their institutional help. However, the application of data in this way also cries out for a set of ethical practices to prevent its abuse. For example, the same data that can help students succeed could also be used to pinpoint which low-income students not to bother recruiting because their chances of enrollment are smaller than more affluent candidates.
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