PAR Framework and Starfish Announce Partnership to Offer Seamless Integration of Predictive Analytics with the Starfish Platform

ARLINGTON, VA (December 16, 2014) – PAR Framework, Inc., a national, non-profit provider of learner analytics as a service, today announced the successful integration of its award-winning Predictions of Academic Risk services with the Starfish® Enterprise Success Platform™ from Starfish Retention Solutions.

PAR Framework predictive models generate predictive risk scores for each student in the PAR data set for member institutions. This integration takes that meaningful risk prediction from PAR’s predictive models and delivers that information into the Starfish platform.

Student success professionals from the University of North Dakota worked with PAR and Starfish to enable the secure delivery of predictive student risk scores from the PAR analytics platform into the Starfish platform to inform how counselors, coaches and advisors prioritize students and allocate staff resources to the students who will most benefit from interventions. This successful implementation means now PAR and Starfish can offer shared partner institutions an integrated experience resulting in smarter interventions to the right students, at the right time.

“We joined PAR Framework because of PAR’s strong commitment to student success. We appreciate PAR’s transparency and the responsiveness of PAR’s core professional staff when it came to meeting our needs,” said Dr. Joshua Riedy, vice provost and chief strategy officer, University of North Dakota. “PAR has already helped us transform the targeted delivery of interventions for students identified as ‘at risk’ through PAR’s predictive models. Working with PAR, and leveraging the Starfish platform, will further enhance the efforts of counselors, coaches and advisors who are actively using Starfish at UND. We are now on track to measure the effectiveness of this integration as early as the first half of 2015.”

Beth Davis, managing director of the PAR Framework, has noted that “the University of North Dakota and the North Dakota University System both have ambitious goals for improving institutional effectiveness and student success, and we are pleased to be a partner in their plans. We’ve quickly gone from discussing what’s possible to delivering a solution that our shared PAR and Starfish institutional partners are seeking. Using predictive analytics to drive student interventions represents the first phase of this integration, and we are now poised to measure how this tight data-driven approach in student services moves the needle for retention and completion within the University of North Dakota.”

“Working with the PAR Framework is part of our effort to use the Starfish platform to deliver the most insightful data about a student’s success to the people on campus who are able to engage with that student,” said David Yaskin, founder and CEO of Starfish Retention Solutions. “This partnership is a continuation of our strategy to offer institutions a holistic picture of each student, including data generated directly by the Starfish platform as well as by third-party providers like PAR, so that advisors and others on campus can better understand their students and offer support.”

About Starfish

The Starfish Enterprise Success Platform helps institutions efficiently scale their student success programs so that more students can finish what they start. Specifically, the software identifies at-risk students in real time based on their daily course-work performance and faculty concerns and then connects them to the resources designed to help (e.g., advising or tutoring), all while assessing which services and interventions are working. For more information, visit

About PAR Framework

The Predictive Analytics Reporting (PAR) Framework is an independent, national, non-profit provider of learner analytics as a service. The PAR Framework offers educational stakeholders a unique multi-institutional perspective for examining dimensions of student success that will help improve retention in US Higher Education PAR improves student success with predictive models and collaborative benchmarks and frameworks that identify critical points of student risks, and links interventions and services for at-risk students at the points of greatest need. PAR is distinguished among the many data analytics solutions emerging in the education domain by its common, openly published data definitions and student success frameworks. For more information about PAR please visit


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