University System of Maryland Adopts PAR Framework to Optimize Statewide Student Success.

Share Article

System institutions take on groundbreaking student-success intervention measurement initiative, accelerating higher-education persistence and completion efforts.

News Image
We want our citizens to be well prepared and in a strong position to contribute to Maryland’s bright future, and having PAR as a common vehicle for intervention measurement across our system will help us stay focused on student success

PAR Framework, Inc., the leading independent, non-profit provider of learner analytics as a service, today announced the University System of Maryland (USM) is adopting the PAR Framework as part of a system-wide effort to optimize investments aimed at improving student success. All USM institutions will adopt the PAR Framework Student Success Matrix (SSMx) in order to inventory, categorize, and explore the returns on investment for student success programs deployed at each institution.

The intervention measurement focus of this initiative targets innovative student supports and interventions used by institutions with their students. The USM will look for unique “points of fit” between students and interventions for achieving essential academic outcomes. This effort will also look for points in the academic life cycle where interventions are most likely to drive student success, giving academic advisors an opportunity to impact struggling students at optimal points and times of need.

The USM office and four of its institutions will also become members of PAR Framework’s predictive analyses and benchmarking collaborative, building upon the successful deployment of the PAR Framework at the University of Maryland University College, an active member since 2012. New institutional members include: Coppin State University; Frostburg State University; Bowie State University; and the University of Maryland Eastern Shore. They will be using PAR predictive analyses to identify students at risk followed by the SSMx to prescribe the most appropriate interventions. “Our institutional research department is already engaged in the pursuit of exploratory insights for supporting data-driven decision-making,” observed Doug Nutter, director of institutional research at Bowie State University. “My colleagues and I are pleased we will be actively contributing to these statewide efforts to raise the bar on student success.”

According to Nutter, all USM institutions already pay close attention to the balance between institutional efficiency and academic benefits for students, when investments are being made in support structures and interventions to help students succeed. This initiative will facilitate rapid adoption and expansion of programs that are shown to achieve results so the entire system can benefit. With the expansion of PAR, the USM will be in a position to leverage predictive models that focus on the students most likely to benefit from targeted interventions, while generalizing findings between and among USM institutions for maximum impact.

“The University System of Maryland continues its active commitment to improving graduation rates in Maryland to a completion goal of 55 percent,” said USM Chancellor Robert L. Caret. “We want our citizens to be well prepared and in a strong position to contribute to Maryland’s bright future, and having PAR as a common vehicle for intervention measurement across our system will help us stay focused on student success--getting more students through the pipeline and getting them through more quickly.”

“The era of ‘boutique analytics’ is over,” noted PAR Framework’s CEO Beth Davis, “We created PAR’s predictive models and outcomes-oriented national benchmarks to find insights we could not find using traditional research methods. One of our most important findings to date is that the significance of intervention measurement cannot be overstated. We are energized by this opportunity to engage with our USM partners to accelerate this very important conversation.”

Davis believes these efforts will actively leverage PAR’s openly-published intervention measurement framework, common data definitions, data gathering, handling, and analysis resources to standardize on meanings for metrics in the U.S. higher-education ecosystem. “PAR works collaboratively with a heterogeneous set of U.S. higher-education institutions and, as a result,” added Davis, ”we have developed deep experience building normalized datasets that enable effective and meaningful outcomes comparisons in a way that reflects the changing landscape of educational models.

The Predictive Analytics Reporting (PAR) Framework is an independent, non-profit provider of learner analytics as a service. PAR offers educational stakeholders a unique multi-institutional perspective for examining dimensions of student success that will help improve retention in U.S. higher education. PAR improves student success with predictive models and collaborative benchmarks and frameworks that identify critical points of student risk, and links interventions and services for at-risk students at the points of greatest need. PAR is distinguished among 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

The University System of Maryland, the state’s public higher education system, comprises 12 institutions, two regional higher education centers, and a system office. The USM engages in research and scholarship that expand the boundaries of current knowledge, and provides knowledge-based programs and services that are responsive to the needs of the citizens of the state and nation.

PAR membership is open to all accredited institutions of postsecondary education in the United States. PAR welcomes institutional partners that want to demonstrate how its programs contribute toward student success innovation. For information about how to join PAR Framework please visit:

Share article on social media or email:

View article via:

Pdf Print

Contact Author

Ellen Wagner
Follow >
Visit website