KDnuggets : News : 2007 : n21 : item32 < PREVIOUS | NEXT >


University of Alabama Uses SAS® to Increase Enrollment by 40 Percent

School Uses Data Analysis to Target Potential Students, Dropouts

NEW ORLEANS--(BUSINESS WIRE)--There are more new faces on the University of Alabama campus than just three years ago, thanks to recruiting and retention efforts using predictive analytics from SAS, the leader in business intelligence. The size of the university’s freshman class has grown 40 percent in that time while student retention has increased from 82 to 85 percent.

“As a result of admissions’ efforts, and with help from SAS, we’re seeing our recruitment and retention numbers improving,” said Cali Davis, Associate Director of Data Analysis and Specialized Recruitment. “We’re also seeing an increase in the quality of our students in terms of their high school grade-point averages and ACT/SAT scores.”

Alabama uses SAS predictive analytics to identify high school students most likely to attend the university. Davis shares these insights with recruiters outside of Alabama where significant numbers of prospects reside. Incorporating college choice preference, financial aid and scholarship awards, ACT and SAT scores, and metrics on in-state or out-of-state residency status into their data mining study, the university has devised new ways to market itself to different segments resulting in increases in both quality and quantity of incoming students.

Alabama is also using SAS to retain its students. A partnership of enrollment strategy and the classroom was born when data mining students taught by Mike Hardin, Professor of Statistics and Associate Dean of Research, began working with the school’s enrollment office to identify freshmen at risk of dropping out. By looking at data points such as college entrance test scores, grade-point averages and demographic features like single-parenthood, university staff can intervene early enough to prevent students from leaving.

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KDnuggets : News : 2007 : n21 : item32 < PREVIOUS | NEXT >

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