The PAR Framework: What We've Learned from 4 Years in the Learning Analytics Trenches

Wednesday, February 11 | 10:30AM–11:15AM | Laguna, Fourth Floor
Session Type: Professional Development
This session will present key findings, outcomes, and insights from four years of exploring the impact, efficacy, and value of predictive modeling for improving postsecondary student success. The Predictive Analytics Reporting (PAR) Framework was launched in 2011 with the receipt of the first of three Gates Foundation grants to see if predictive analytics could be used to provide new insights for mitigating student risk. We'll describe PAR's journey, from the spark of a shared idea to the establishment of an independent, nonprofit provider of "learner analytics as a service" serving more than 30 institutions and providing participants with calls to action for improving data readiness and evidence-based decision making at their institutions.

OUTCOMES: Understand the value of predictive analytics as methodologies rather than magic bullets * See and hear how predictive analytics directly affect the provision of student support at a variety of institutions * Access resources and assets for getting started on or refining your analytics efforts


  • Hae Okimoto

    Director, Academic Technologies, University of Hawaii at Manoa
  • Ellen Wagner

    Affiliate Research Professor, University of Central Florida