PAR Framework

An analytics collaborative taking the guesswork out of student success

The Predictive Analytics Reporting (PAR) Framework, originated at WICHE and Primarily funded by the BMGF, was acquired by Starfish by Hobsons in December, 2014 and was built for educators, by educators, with a front-line view of the points of greatest need. Participating institutions–each one committed to student success–actively engage in the collaborative process by contributing their resources and experience. In exchange, PAR offered its members a plethora of insight tools and proven best practices that measurably improve student and institution outcomes.

Often student retention and analytics initiatives are based on isolated, institutional-specific situations, or activities, making it necessary for every institution to start from scratch when trying to improve student outcomes. These efforts fail to provide the holistic perspective that PAR strives to achieve when leveraging data to improve student outcomes across multiple institutions. PAR’s multi-institutional assets and collaborative approach provide a jump-start to any institution looking to make a difference in course success, retention, and graduation rates.

To revisit the PAR Framework in action, watch An Empirical Look at Intervention Effectiveness for Improving First-Year Experiences.

The PAR Approach

Many higher-education efforts focus on an individual institution’s student records. The PAR Framework leveraged the efficacy of federating and aggregating independent institutional datasets into a single data resource. By systematically applying a variety of exploratory, inferential, and descriptive techniques, PAR looked for patterns of risk and then mitigated those risks with the appropriate interventions at points of need.

The PAR Framework was committed to:

  1. Building open collaboration between 2-year, 4-year, public, private, proprietary, traditional, and progressive institutions for sharing data, analyses, and findings. Members share what they have learned about responding to challenges as a result of data, as well as successful practices that have been validated as a result of analyses.
  2. Developing and maintaining common data definitions; Identifying and defining common variables that apply across U.S. higher-education institutions and systems are the first steps in developing valid and reliable tools and interventions that can be utilized across the U.S. post-secondary system.
  3. Creating a scalable multi-institutional database that yields meaningful benchmarks for PAR institutional members and offers common, cross-institutional metrics for accountability that consider student outcomes.
  4. Providing affordable access to sophisticated analytical resources enabling PAR member institutions to benefit from predictive analytics, outcomes benchmarks, data warehousing, “data hygiene,” intervention measurement, and a shared talent pool.
  5. Advancing the efficacy of student interventions: Measures, benchmarks, and predictive models–based on common definitions–enable members to evaluate retention strategies in a variety of institutional settings and allow for measurement of intervention practices at a national level.

The PAR Framework, now a part of Starfish Analytics, enabled analyses of 2 million de-identified student records and more than 20 million course-level records to look for patterns that can warn of risks before problems emerge. Analyses conducted on a sample size of this magnitude can offer confidence intervals in excess of 90 percent.

  1. Common Data Definitions
  2. View the Student Success Matrix
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