Analytics to Action: Predictive Model Outcomes and a Communication Strategy for Student Persistence

Abstract

Increased federal attention to student completion metrics and uncertain financial forecasts have heightened the tenor of student retention conversations. Improved institutional retention rates will lead to higher completion rates and relieve some funding concerns. To accomplish these improvements, institutions have invested in analytics to better understand student persistence and completion factors. However, few studies outline how analytics are employed to positively influence student success and persistence. This article outlines the creation of a predictive model for student persistence, and details the use of the model outcomes to create a communication strategy intended to increase student persistence. The methodology used to develop the persistence model and the results of the communication strategy are included.

Keywords:

• nontraditional student retention
• predictive model
• communication strategy
• analytics
• persistence
• accelerated programs

Additional information

Notes on contributors

Nathan Brad Miller

Nathan Brad Miller is the Director for the Department of Student Success, Columbia College.

Bryan Bell

Bryan Bell is Chief Analytics Officer, Aviso Coaching.