Gartner Research interviewed the PAR team when the trend of Big Data first appeared on the Education Hype Cycle, and included PAR as an example of innovative emerging work in Big Data in the 2012 Report. PAR is included in this annual review of IT market evolution since that time. This is particularly notable since PAR is not a venture capital or shareholder funded venture; rather, PAR operates as an independent, member-driven 501.c.3 organization.
For background: every year, Gartner Research analysts review technology triggers and trends attracting attention in specific markets like education, financial services, manufacturing, government, and pharmaceuticals. Their Hype Cycle reports acknowledge that emerging technologies go through boom-and-bust-and-renewal cycles as companies work out the bugs in their product and service offerings and customers learn what they want. For obvious reasons, we pay attention to the Education Hype Cycle.
As described by J.M. Lowendahl, author of the 2014 Hype Cycle Report, big data in higher education has been around for decades, but has mainly focused on research in the hard sciences. However, big data for education is more recent, and has been enabled by more and more of our lives being lived and recorded online. Examples of data sources include student information systems (SISs) for grades and demographics, learning management systems (LMSs) for instruction and learning, CRM systems for student and alumni relations.
In the 2014 report, Lowendahl observed that “The Predictive Analytics Reporting (PAR) Framework is developing analytical capabilities based on proprietary big data. Already, the PAR Framework project combining data from big traditional universities, community colleges and for-profit organizations is an interesting example that keeps growing. PAR’s project’s release of the data definitions as a Creative Commons license is a major step forward and a possible competitive advantage over commercial competitors such as Civitas Learning.”
Several paragraphs hence, Lowendahl commends PAR by saying “The PAR Framework published under a Creative Commons license is a particularly good example of how collaboration can be facilitated using simple established open-source licenses. In this complex endeavor we recommend a “learning by doing” approach and joining or at least studying the PAR Framework project experience. This is the most advanced openly available information in higher education to our knowledge.” Jan-Martin Lowendahl, (2014) Education Hype Cycle. Stamford CT: Gartner Research July 23, 2014 G00263196.
The openly published PAR data definitions have been downloaded more than 2300 times since it was published in 2013. The definitions have been cited in specifications for projects including IMS Global’s Caliper specification and in Unizin’s data specifications. Thanks to PAR’s common data definitions – the Rosetta Stone of student success data – we have integrated our predictive models with Starfish Retention Solutions and with the open source Student Success Plan. Common data definitions are the foundation for apples to apples comparisons, generalizability and scale.