2019 – What Makes a Difference? Cloud Automation of Near Real Time Student Retention Prediction

Presentation Summary

In forecasting and addressing year-to-year student retention, effecting proactive measures to improve retention requires not only the prediction of the specific retention probabilities for each individual student, but also that those predictions be produced early and often in response to changing student behaviors. The analytical modelling and machine learning behind just-in-time retention prediction has historically been complex to implement. In this presentation, members of the Analytics and Institutional Research team at Ithaca College will present their solution to a fully automated, cloud-based, just-in-time student retention framework – a framework largely built on freely available open-source tools and technologies.