Summer Strategies: Using AI & Institutional Change to Prevent Retention Risks
As summer approaches, enrollment and student success teams will be shifting their focus from deposit season to ensuring students—both incoming and continuing—are set up for success. One of the most effective ways to improve retention is by leveraging AI-driven predictive analytics alongside institutional change to identify and address at-risk students before they face challenges that could lead to attrition.
Six Steps to At-Risk Student Intervention
Identifying individual students who are at-risk of dropping out is often a subjective exercise in higher education. Additionally, for each student the institution intervenes with, we must answer the question of why are we intervening? And what resources will we provide this student? It is critical to increase retention and graduation rates, while remaining conscious of intervention resources, budgets and university revenues.