Data Analytics & Reporting | News
PAR Framework Releases Full Data Definitions
The Predictive Analytics Reporting (PAR) Framework project has publicly released the full definitions for the data included in the PAR database to encourage distribution of the definitions in the higher education research community.
The PAR Framework is a longitudinal, multi-institutional data-mining project managed by the WICHE Cooperative for Educational Technologies (WCET). According to information on the organization's site, "the PAR Framework makes it possible to create meaningful benchmark reports, conduct predictive analyses, and explore best practices in student retention on a massive collection of student records in a quest to better understand the variables affecting student loss."
The data includes more than 60 institutional, transcript, and student-level variables. "These variables will be used as building blocks in various strategic combinations to craft meaningful outcome measures and actionable predictors of student risk which further highlights the importance of common definitions," said Beth Davis, PAR Framework project director, in a prepared statement.
The PAR Framework has published the data definitions using the Data Cookbook, a collaborative data dictionary and data management tool built for higher education by IData. The definitions are published under a Creative Commons license with attribution, non-commerical, share-alike conditions.
Until now, the data fields and definitions used in the PAR Framework have been available only to the organization's 16 institutional partners, who have submitted more than 1.7 million anonymized and institutionally de-identified student records and 8.1 million course-level records to the dataset.
"The online Data Cookbook forum for publicly sharing our data model creates opportunities for alignment and collaboration with other projects and other datasets meaningful in higher education," said Mike Sharkey, director of academic analytics at the Apollo Group (parent company of the University of Phoenix), in a prepared statement.
The PAR Framework plans to continue to refine its data set to align with the recently released Common Education Data Standards (CEDS) version 3 and other higher education data sets.
Further information about the PAR Framework's data definitions can be found on the Data Cookbook site.
Leila Meyer is a technology writer based in British Columbia. She can be reached at firstname.lastname@example.org.