'In higher education, no predictive analytics project has been able to use a multi-institutional sample of this size. As a researcher, having a sample size of this number changes everything.'
-- Dr. Phil Ice, American Public University System
Boulder, CO (PRWEB) October 17, 2011
WCET, the WICHE Cooperative for Educational Technologies, announces the successful federation of datasets from the six institutions participating in the PAR (Predictive Analytics Reporting) Framework proof of concept project just four months after the project’s early June launch. The goal of the PAR Framework is to identify variables that influence student retention and progression and to determine the impact of various demographic data on factors influencing loss and momentum. The data will be used to explore patterns that emerge when the datasets from considerably different institutions are analyzed as a single, unified sample.
The dataset includes over 640,000 anonymized student records and over 3 million course level records, focusing on 33 common variables. The institutions represent public/private, two-year/four-year, and publicly-funded and proprietary institutions.
“We have been using analytics as a tool for improving student retention and progression for several years,” said Dr. Phil Ice, vice president, research & development, American Public University System, and principal investigator of the PAR Framework Project. “Unifying records from multiple schools has the potential to expose generalizable patterns that can provide guidance to institutions across the board, regardless of their internal level of analytics expertise.” Ice continues, “In higher education, no predictive analytics project has been able to use a multi-institutional sample of this size. As a researcher, having a sample size of this number changes everything.”
The WCET member institutions engaged in the PAR Framework project include American Public University System (apus.edu), Colorado Community College System (cccs.edu), Rio Salado College (riosalado.edu), University of Hawaii System (hawaii.edu), University of Illinois Springfield (uis.edu) and the University of Phoenix (phoenix.edu). Each institution obtained IRB (Institutional Review Board) approval. All data was anonymized and encrypted to ensure that no data are personally identifiable.
“We had been warned that we could never find six schools willing to collaborate on something as sensitive as an institutional student and course level data federation project,” noted Ellen Wagner, WCET Executive Director. “It’s exciting to see how forward-thinking WCET member institutions are bringing the power of “big data” to post-secondary education in the US. Not only is the magnitude of the data set unprecedented, the diversity of the participating institutions will provide us granular insight into similarity and differences across higher education institutions in the for profit, public and community college segments.”
A summary of first findings are scheduled for presentations at the 23rd Annual WCET Conference in Denver, Colorado October 27th. http://wcetconference.wiche.edu/
About the PAR Framework
The Predictive Analytics Reporting (PAR) Framework is a longitudinal data-mining project centered on conducting large-scale analyses of federated data sets contributed by postsecondary institutions to extend our understanding of student loss and momentum. The PAR Framework has been designed to better inform student loss prevention efforts and to identify drivers relating to promoting student progression and completion.
The WICHE Cooperative for Educational Technologies (WCET) is a cooperative, membership-driven, non-profit provider of solutions and services that accelerate the adoption of effective practices and policies, advancing excellence in technology-enhanced teaching and learning in higher education. More information about WCET’s institutional membership resources, services and common interest groups can be found on WCET’s website, http://wcet.wiche.edu.
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