How Georgia State University Plans to Use Predictive Analytics to Address the National Achievement Gap

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Here's how Georgia State University is using predictive analytics to identify at-risk students and intervene quickly - and how they're now testing the approach across other institutions.

 

SPOTLIGHT ON INNOVATION SERIES

The US Department of Education has awarded multi-million dollar "First in the World" grants to 18 colleges and universities that are innovating to solve critical challenges with access, recruitment, retention, and student success. At AI, we have interviewed each of the recipients to learn more about the projects these institutions are pursuing, how their approaches are unique, and what other colleges and universities can learn from these new efforts.

This was the second year of the First in the World grants. You can read our interviews with the 24 institutions that received 2014 grants here.


by Lisa Cook, Academic Impressions

During the past ten years, officials at Georgia State University have tracked more than 140,000 student records and 2.5 million grades in order to identify mistakes that put a student at risk of dropping out. A decade later, they’ve identified more than 800 different mistakes, and continue tracking all 30,000 of their students so they can quickly intervene. Their next challenge? Using the same approach to track students at 11 different institutions across the country to see if they can replicate those results.

Many institutions are already using predictive data, explains Tim Renick, GSU vice provost and vice president for enrollment management and student success, but no one has done a validated study to show what the impacts are, and if they’re positive impacts, how can they be maximized. Now with the help of a nearly-$9 million grant, officials at GSU will do just that in their project MAAPS: Monitoring Advising Analytics to Promote Success. We talked to Renick to learn more about how GSU is using predictive data, what the scale project will look like, and the benefits they think the data holds for the future.


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