Student Success Analytics initiative

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.

Development Cycle

The development cycle to create tools for data and analysis is complex. The Student Success Analytics initiative will: 

  • Identify a problem
  • Document requirements
  • Model
  • Pilot and test
  • Scale and deploy
  • Assess lessons learned

Development of some deliverables may continue after the initial deadline as additional opportunities and needs are identified. 

Project timeline and status

Project timeline and status

Estimated project timeline

Project status updates

Definitions:

  • Prototype: An early release to test/develop concept or process.
  • Soft-launch product: A product launch with a limited audience to test functionality, data validation, and how the data is delivered before full release.
  • Minimum viable product:  Product release in a production environment with limited distribution to early adopters.
  • Version 1: Product is available in the reporting center (or as appropriate for product/dashboard type).
  • Version 1.1, 1.2., etc.: Addition of new data elements to release.
  • Version 2.0, 3.0, etc.: Restructuring of existing data and/or delivery method.

Project descriptions

Project descriptions

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.

Project governance

Project governance

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

Working groups

  • College leadership (Deans, Associate Deans, and Advisor Management/Student Services directors)
  • Advisors