A predictive analytics system is being used at Georgia State University to identify students who are at risk for dropping out. This robust system tracks every student on 700 triggers, and alerts administrators when a student is in need of one-on-one intervention.
“We wanted to get rid of gaps in races, ethnicities and income levels and to even the playing field,” says Timothy Renick, VP for Enrollment Management and Student Success and vice provost.
To that end, at the same time, Georgia State doubled its number of Pell Grant recipients and raised its graduation rate 22 points. “We want to defy logic that enrolling low income students will make graduation rates go down,” says Renick. “With the right intervention at the right time, all students can succeed.”
Renick will discuss specific examples of triggers and predictive data used by the system at UBTech in his featured session, How Using Predictive Data Helps Advisors Boost Student Success at Georgia State. “I think attendees will be surprised to hear the strong ROI we have reaped by engaging in these interventions,” he says. “They have lead to more tuition and fees revenues.”
To see Renick’s presentation and learn how how this student success initiative works, be sure to register for UBTech here.