The Student Success Analytics (SSA) initiative will positively affect and support student success throughout the University of Minnesota by understanding and utilizing data and analytics. The goals of this initiative include:
- Increase student retention and timely graduation
- Improve curricular design, delivery, and transparency
- Lower average student debt upon graduation
- Enhance the student academic experience
The SSA initiative will continue to build on the progress of existing University best practices like degree-planning resources and dashboards for students and advisors (APAS, APLUS), promoting financial wellness, career bridging, risk segmentation, peer mentoring, and campus engagement.
The work will initially focus on undergraduate students; opportunities for the University's graduate and professional students are being assessed.
Project timeline and status
Project timeline and status
Project work and deliverables generally flow through the following phases, including the iterative nature of the work as new features are requested.
Identify a problem. Gather and analyze information to understand the stakeholders’ and end users’ goals and needs to solve that problem.
Identifying and documenting requested requirements from stakeholders.
Proof of Concept/Prototype
Determines if an idea can be turned into a reality that will function as envisioned. Generally delivered as prototyping or wireframing samples demonstrating the design concept feasibility. Used to gain stakeholders feedback and insights in product iterations.
Minimum Viable Product
The MVP is released in a production environment to attract early-adopters with enough features to satisfy customer needs. Typically MVP involves a soft launch to test the functionality allowing adjustments to be made before a wider release.
The production release of a new product communicated to the designated audience with training and job aids provided.
The transition of a product to operations support to encompass continual improvement.
Deliverable and tool descriptions
Retention risk predictive analysis: Effort to model and analyze whether an individual student is at risk of leaving.
Curriculum analysis: Effort to analyze historical course-taking patterns to make curricular recommendations.
Degree progress reports: Ability for data authors to independently answer student degree-progress questions.
Degree progress dashboard: Dashboard will aggregate and provide summary-level degree progress data and information.
Graduation proximity report: Report provide student-level progress toward completion information.
Retention rate dashboard: Dashboard to provide summary- and student-level retention rate information.
Graduation rate dashboard: Dashboard to provide summary- and student-level graduation rate information.
Student retention risk dashboard: Dashboard to provide summary- and student level retention risk information.
Major-change analysis: Effort to understand impact of major changes, outcomes, and pathways to success.
Executive sponsor: Bob McMaster, OUE
Business sponsor: Sue Van Voorhis, ASR
Project lead: John Vlk, Student Data and Analytics, ASR, OUE
Steering committee members:
- Sue Van Voorhis, Associate Vice Provost and University Registrar, ASR, OUE
- Peter Radcliffe, Director of Undergraduate Analytics, OUE
- LeeAnn Melin, Assistant Dean for Undergraduate Student Initiatives, OUE
- Brian Krupski, Enterprise Data & Analytics Service Owner, OIT
- Linc Kallsen, Director, Institutional Analysis, OBF
- Beth Lingren Clark, Associate Vice Provost of Strategic Enrollment Initiatives
- College leadership (Deans, Associate Deans, and Advisor Management/Student Services directors)