Using Predictive Analytics to Improve Retention

Date of broadcast: Tue, 04/02/19

Predictive analytics has proven to be a crucial element for managing enrollment for many institutions. However, there is often a lack of clarity about how best to utilize these tools to boost retention.

Attend this web seminar to learn more about using predictive analytics to improve retention modeling, and how to distribute this information to end users to ensure the data created is actionable. The Director of Institutional Research & Effectiveness at Bellarmine University will discuss how the institution is using predictive analytics to identify at-risk students and boost retention. Bellarmine received the 2018 ACPA Award for Innovative Academic Support Initiative for their work and now have over 70 faculty and staff involved in the process.

Topics will include:

  • Which data points are predictive of student retention
  • How to involve other faculty and staff in the conversation
  • Best practices for utilizing the results of a predictive model
  • How Bellarmine University is using predictive analytics to identify at-risk students

Scheduled speakers:

Drew Thiemann
Director of Institutional Research & Effectiveness
Bellarmine University (Ky.)

Jon MacMillan
Senior Data Analyst
Rapid Insight

Who will benefit: Higher ed leaders interested in predictive analytics or retention. Anyone may attend.