Using Predictive Modeling to Drive Early Alert and Intrusive Advising

This project includes two phases. The first phase evaluates the ability of a predictive model to identify students at-risk of leaving college early, and examines the extent to which there are patterns of advising participation rates and retention rates associated with a student’s risk-level classification. The second phase of the project develops and tests the effectiveness of an academic advising intervention compared to the risk categories created by data from the predictive model. ​​

Materials and Outcomes

Throughout the course of this project, updates and final reports will be posted here.​​​

Using Predictive Modelling to Inform Early Alert and Intrusive Advising Interventions and Improve Retention

Researchers develop a model to forecast dropout rates, better support students Can a mathematical equation predict which students are most likely to drop out? Yes, according to the findings of a new report published by the Higher Education Quality Council of Ontario (HEQCO). Researchers at Mohawk College and the Education Policy Research Initiative (EPRI) developed […]

Academic Advising: Measuring the Effects of “Proactive” Interventions on Student Outcomes

More Robust Student Outreach Could Reduce Drop-out Rates First-year students who received repeated emails encouraging them to participate in advising services — particularly in group advising sessions — were less likely to drop out, finds a new report published by the Higher Education Quality Council of Ontario (HEQCO). The study was conducted by researchers at […]