Predictive Analytics Reporting (PAR) Framework Wins 2014 Campus Technology Innovator Award
Boulder, CO (PRWEB) June 16, 2014 -- The WICHE Cooperative for Educational Technologies (WCET) has announced that the Predictive Analytics Reporting (PAR) Framework has been named a Campus Technology Innovator for 2014. Campus Technology editors and judging committee of higher educational IT leaders selected the PAR Framework as an innovator in the Student Systems & Services category from among hundreds of nominations for this coveted recognition. This award was made public by Campus Technology just days after the PAR Framework announced its plans to emerge from WICHE as an independent non-profit organization before the end of 2014.
Recognition in the Student Systems & Services category is notable since the PAR Framework is a national non-profit collaborative venture of U.S. 2 year, 4 year, public, proprietary, traditional, and progressive postsecondary institutions working together to solve their student success challenges using predictive analytics. PAR Framework institutions contribute anonymized student and course data based on a common data model to a common hosted dataset. The data are used to produce comparative benchmark reports with deep insight into student attributes and outcomes. PAR Framework data scientists create localized predictive models based upon each partner institution’s own data and use techniques from standard statistical methods to advanced data mining techniques to identify points of academic loss. Institutions classify their student success interventions using the Student Success Matrix (SSMx), for gap analysis and evaluation of intervention effectiveness with target populations. Partner workgroups lead development and decision-making for all PAR tools and products.
“The PAR Framework team is honored by Campus Technology’s recognition of the work our member-driven collaborative has produced thus far,” said Beth Davis, co-founder and managing director, PAR Framework. “PAR emerged based on models developed within individual member institutions to see if cutting-edge predictive analytics could be delivered in a timely, cost-effective, broadly scalable way. We quickly learned that being able to effectively predict students at risk with high confidence levels is only part of the solution; the true value of predictive analytics is unlocked when people have tools that help them address and respond to risk. We are making the PAR Framework predictions of academic risk actionable by inventorying, mapping and measuring the impact of student success interventions.”
The PAR Framework was selected as an innovator in part because of their creative deployment of commercially available technologies used in research and ongoing operations. PAR depends upon a number of commercial service providers to accommodate distributed collaboration, data collection, analysis, reporting, and visualization requirements. PAR chose Huddle for its ease of use sharing project information, uses iData Cookbook for documenting and publishing the data definitions, and depends on web conferencing from Zoom and Blackboard Collaborate. PAR identified SAS Visual Analytics as a key component when building its core technology stack.
“PAR brings to institutions three key elements that hold great potential for increasing student persistence and completion: analytics, to identify risk factors at the individual student level; interventions aimed at timely outreach to individual students at the moment of need; and collaboration and benchmarking among participating institutions,” noted Joel Hartman, University of Central Florida. “Together, these elements are poised to give institutions tools and techniques they can use to truly ‘move the needle’ on improving student outcomes.”
The Predictive Analytics Reporting (PAR) Framework is a national, non-profit, data services collaborative focused on institutional effectiveness and student success. Membership in PAR is open to any accredited higher education institution with the desire and ability to provide undergraduate data along and the willingness of senior level leadership to contribute energy and insight to the collaborative. To learn more about the Predictive Analytics Reporting (PAR) Framework, visit the website at http://parframework.org.
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.
Ellen Wagner, PAR Framework, http://wcet.wiche.edu/par, +1 (415) 613-2690, [email protected]
Share this article