Much has been written about how Big Data and cloud computing can be used for diversifying educational learning platforms. For example, Big Data is being used to track students’ academic performance and alert them and their supervisors to falling grades, attendance or both. Even before the future students pack their bags, universities offer them possible learning paths, before and on campus–the University of Georgia, for example, predicts on which majors a student is likely to succeed based on performance on past courses.
Other universities are also quick to leverage this data analysis phenomenon–after all, they were never really short on data about their students in the first place. What’s really putting colleges on the edge now, though, is the shifting education landscape. With President Obama’s new ‘value ratings’ system to set to work next year, higher education establishments are forced to become more efficient, and soon, to qualify for government aid. Eventually, the goal is to “Hold students and colleges receiving student aid responsible for making progress toward a degree.” The stakes are thus rather high.
Universities pioneering in Big Data, like the Arizona State University, are long employing analytics tools that help both students and their supervisors. A.S.U’s eAdvisor system, in place for seven years already, has helped achieve substantial increase in lower-income students’ graduation rates–from 41 to 26 percent–over the past three years. They achieved this partly by using eAdvisor to notify the students and their advisors if the former are straying away from the path to a degree.
Similarly, Marist College in Poughkeepsie New York has implemented an early warning system that can indicate, three weeks into a course, if a student will have problems finishing. The system works by collecting online learning breadcrumbs, much like Facebook and Google do, to see how much attention a student is paying to the course. Within two to three weeks, they know with a 75% certainty whether someone will have trouble keeping up. In order to help the students, they send an email to the professor teaching a course so that the student can be helped privately. Before, the students themselves received an email, but many of them panicked and dropped the course, making the ‘social smarts’ aspect in such software rather evident.
That’s the usual caveat with data, big or otherwise. It’s as good as the people using it. A university with poor personnel can get better using Big Data, but, with the new regulations, this alone may well not warrant the survival of the institution. Notifications about failing grades can remind a student about her duties, but a heart to heart with a real human being can do much more–if both parties are equally interested, of course.
By Lauris Veips
