eBook: Supporting Student Success: First Year Retention Modeling

Colleges and universities are under intense pressure to boost retention and completion rates, and national research has shown that students who are highly engaged on campus are more apt to graduate. By using predictive analytics effectively, institutions can improve retention rates by identifying students needing early intervention and proactively helping them succeed. Read this eBook to learn what is needed to get started with predictive modeling and how it can be applied for first year retention modeling.

UNC-Greensboro: Looking Beyond First Year Student Success

Learn how UNC-Greensboro wanted to take a broader approach to retention and looked beyond just the first years. Watch this video to learn how Jeffrey Collis, Data Manager at UNC-Greensboro, and Jon MacMillan, Senior Data Analyst at Rapid Insight, collaborated in this multi-year retention project.

Ball State: Boosting Student Retention with Predictive Analytics

Dr. Kay Bales, Vice President of Student Affairs and Dean of Students, bring their predictive modeling and analytics efforts in-house to work faster and smarter to reach the right students. Their proactive approach led to a 6 point improvement in their retention rate.

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Decentralize analytics. Harness the power of many.