Predict Higher Education Student Retention Risk

The college’s student retention rate over 6 years was below 50 percent. They knew they needed to find proactive ways of identifying at-risk students, but weren’t sure how to best leverage their data to do it. The college’s Institutional Research team brought in Ironside to test predictive modeling techniques, evaluate and select a set of predictor variables on which to base student risk scores, segment students into groups based on GPA attainment and retention likelihood, integrate with the college’s student services model, data warehouse, and BI platform, and output individualized student risk scores and intervention/retention strategies for at-risk students.