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Use Data To Drive Diversity

by Manuela Ekowo

EdSurge

Article excerpt

Colleges Need to Use Predictive Data to Enhance—Not Hinder—Diversity

Colleges have turned to predictive analytics—using past enrollment data to make predictions about future enrollment trends—to make tough decisions about who to actively recruit, admit, and support financially. In fact, a recent KPMG survey found that 41 percent of colleges are using their data to make predictions about future conditions and/or events.

Our take

Data Can Be a Diversity Driver: If Used Effectively

Using technology—specifically predictive analytics—to aid in recruiting a diverse student body seems like an idea with great potential, and it may be. Administrators, though, need to be alert to unintended consequences that may hinder, rather than help, the diverse audiences they seek. Is your profile of the “ideal student” built on data that may drive unintended bias?

Data can be a great aid, but must be fully understood to ensure the conclusions it drives are sound. As pointed out here, if the data used to profile an ideal student is based on past attendance (which it likely will be), it may not be reflective of the students who are underrepresented. Admissions officers have difficult decisions to make and data can help. At the end of the day, though, admission decisions need to balance a range of inputs and insights that align with both institutional, and individual student, goals and objectives.

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