Data Analytics has found its way into the US education system where data silos containing performance data of former students are being analysed to predict the outcomes of current ones.
According to a Time report approximately 125 schools around the U.S. have been collating and sifting through years of data covering millions of grades earned by thousands of former students, as part of this effort; something enterprises, retailers and businesses have been doing with available data points to glean customer behaviour in order to provide better services and upscale revenues.
“What we used to do, and what other universities do, is let the C student go along until it was too late to help them,” notes Timothy Renick, Georgia State’s vice president for enrollment management and student success. “Now we have a flag that goes off as soon as we spot a C in the first course.”
A predictive algorithm has been established to track students’ chances of dropping out or graduating and alert the academic advisors about the ones who may fall short, so as to help them before it’s late.
In the wake of the economic hitch starting in 2008, there has been a noted drop in graduation rates. Georgia State University, one of the institutes incorporating the technique, has analyzed 2.5 million grades of former students to predict outcomes with current students. Since 2012 the “early warning system” is attempting to fix the “lower-than-the-national-average graduation rate,” having flagged 34,000 students last year who might suffer a setback.
The Time article points out that apart from the graduation rates going up there is also a resource and monetary advantage: “tracking data in this way keeps tuition coming in from students who stay, and avoids the cost of recruiting new ones, which the enrollment consulting firm Noel-Levitz estimates is $2,433 per undergraduate at private and $457 at four-year public universities,” it said.
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