New development could help colleges improve student retention

The PAR Framework project has released full data definitions in hopes of streamlining research to improve student retention.

A project that aims to identify common factors for why college students transfer, drop out, or fail to complete courses has released full definitions for the more than 60 data fields collected from its 16 institutional partners—a move that could help other schools improve student retention.

For the first time in the Predictive Analytics Reporting (PAR) Framework project’s history, it has publicly released full data definitions for the institutional, transcript, and student-level data in the PAR database. This is the first time the data fields and definitions used in PAR Framework modeling and analysis have been available beyond the project’s institutional partners.

PAR data definitions have been published using a Creative Commons license to encourage their distribution among the higher-education research community. Moving forward, PAR will continue to refine its data set to align, where appropriate, with the recently released Common Education Data Standards (CEDS) version 3 and other pertinent higher-ed data sets, the project says.

The PAR Framework is managed by WCET and unites a cohort of universities in a data mining project to identify effective practices for improving student retention in higher education. Currently, the project’s member universities are focusing on removing barriers to student success in online and blended-learning programs.

“PAR offers educational stakeholders a unique, multi-institutional lens for examining dimensions of student success from both unified and contextual perspectives,” the WCET press release explains.

“Common data definitions are at the core of the work we are doing with PAR,” said Beth Davis, PAR Framework project director. “Our goal in working with these varied institutional partners was to define common variables to ensure that comparisons and [data] aggregation are valid, reliable, and repeatable.”

Davis believes these simplified data definitions will enable the PAR Framework project to streamline research, achieve conclusive answers, and foster a better understanding of how to improve student retention.

(Next page: How the data definitions can be used to boost retention)

“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 Davis. “The more than 60 contributed variables submitted by our institutional partners and the new variables constructed from them will be used to yield meaningful benchmarks and predictive models against which partner institutions can evaluate retention strategies.”

The simplified definitions established by the cohort of project partners were a labor worth undertaking, said Mike Sharkey, director of academic analytics at the Apollo Group, the parent company of the University of Phoenix.

“The focus on common data definitions within the PAR Framework has been a challenging yet rewarding part of this process,” said Sharkey. “Working collaboratively with representatives from a heterogeneous group of institutions takes time, but the benefits of common data definitions are tremendous. “

The data definitions were published using the Data Cookbook, a collaborative data dictionary and data management tool for higher education built by iData Inc.

Using the online Data Cookbook “was a very beneficial way to develop the overall parameters of the individual data variables,” said Vincent Maruggi, director of institutional research at Broward College. “The iterative, cooperative process unearthed a number of variables that had multiple interpretation options that needed rational and consistent consideration, especially considering their application across the diverse set of institutions involved in PAR.”

Maruggi attested that working with the other institutions within the project was a positive experience.

“The dialogue was highly productive and forced me to investigate deeper into Broward College’s student data system for elements that were not previously utilized in a like manner, while also giving us a new conceptual structure for future reporting.”

Follow Assistant Editor Sarah Langmead on Twitter at @eCN_Sarah.

For more news about improving student retention, see:

How to manage barriers to online education programs

Learning analytics tools aim to boost student retention, outcomes

Predictive analytics driving university practices

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