Big Data 101: Colleges Are Hoping Predictive Analytics Can Fix Their Dismal Graduation Rates
Decades ago, colleges would start off freshmen orientation by pointing out how many students wouldn’t succeed. The practice has gone out of style. But the graduation rate has barely budged: less than two-thirds of students who start college ever finish. So the central mystery of higher education remains the same: who will graduate? Who won’t? What separates the successes from the dropouts? And how can colleges turn the latter into the former before it’s too late?
Ellen Wagner’s job is to answer those questions. The longtime education technology expert directs the Predictive Analytics Reporting Framework, one of the biggest data sets of higher education’s nascent era of Big Data. Once colleges know the students who are most likely to drop out, the hope is that they can help them avoid that fate.
Using data on 1.8 million students from the past, Wagner can see the future. Give her the bare bones of a college freshman’s biography — age, major, whether he is the first in his family to go to college, whether she has served in the military — and she can predict whether that student is likely to graduate. “It sounds almost like science fiction,” Wagner says. “But the reality is there’s a lot that every one of us can be doing right now by simply looking at patterns of information.”