Page 32 - Campus Technology, March/April 2018

C-Level View
Predictive Analytics and the Transformation of Education
Ellen Wagner, former chief research and strategy officer for the Predictive Analytics Reporting Framework and now VP for research at Hobsons (which acquired PAR in 2016), talks about the future of predictive analytics for education. By Mary Grush
Education visionary Ellen Wagner has guided the development of the Predictive Analytics Reporting Framework (PAR) from its inception eight years ago as a research project of several higher education institu- tions, to its current home at Hobsons. She has seen the project move from a collegial inquiry with her peers — both before and after PAR received its initial funding — to its maturity in mainstream product integrations and accepted education methodologies.
Here, Wagner gives us an update on PAR, as well as her vision of more gen- eral directions in predictive analytics for education.
Campus Technology: PAR has been a key foundational participant in the ana- lytics movement in higher education. I’d
like to get your update and perspectives on PAR today. So much has happened — where should we begin?
Ellen Wagner: Who would have thought that a small group of us, talking about
this emerging idea of predictive analyt- ics after the 2010 WCET meeting, would have had the opportunity to take that idea from what we thought might be “fun” to try in education, to the designing, funding, developing and releasing of a commer- cial software product. Beyond that, who would have imagined our nonprofit re- search project being acquired by a com- mercial software provider? It’s been quite an experience.
PAR has literally “grown up” as a part of the analytics movement in U.S.
postsecondary education. Some might even say that we helped shape some of the expectations that education customers have of ed tech companies when working with analytical solutions.
How about if we start with an update on PAR at Hobsons, and then let’s take a look more broadly at the transformative impact that analytics are bringing to education practice — whether we, as educators, are ready or not. I’ve got a few thoughts on what those of us who care about student success need to be thinking about in 2018.
CT: As a set of methodologies and com- mon definitions for predictive analytics, how does PAR fit into Hobsons’s stu- dent success business?
Wagner: Our primary work to date has focused on integrating PAR with our Starfish platform, since that is where the most immediate opportunities for post- secondary student success improvement can be found. PAR analytics are now tied to “smarter” advising and case manage- ment, and are increasingly being used with interventions inventory and efficacy as- sessment. As we have seen from our PAR research, college fit is one of the most pre- dictive indicators of long-term student suc- cess; my colleague at Hobsons, Dr. Susan Hallenbeck, advised us that fit is a strong predictor of retention and completion. You can be sure we are spending some quality time looking beyond predictions for match- ing success, to focus on the importance of finding what has come to be known as ‘fit’:
32 CAMPUS TECHNOLOGY | March/April 2018