Page 33 - Campus Technology, March/April 2018

C-Level View
the feeling of belonging, of knowing that one has found a home base.
Additionally, our data analysts are bringing predictive analytics to Naviance, our college and career readiness platform. We need
to be smart about where predictions of readiness make the most sense. Clearly
if we are concerned about risk in college, of course we are also concerned about readiness in middle school and high school. Why not extend the PAR Framework to addresses college and career readiness, and college matching and fit, as well
as college progression, retention and completion?
CT: Over the years, PAR evolved far be- yond its original objectives. What are the highlights or strides PAR has made be- yond its initial concept?
Wagner: PAR’s original objectives were literally to see if we could use predictive analytics to find students at risk of drop- ping out of college, which, when you think
about it, continues to be a worthy goal. We still have a long way to go! Back when we hatched this idea in 2010, we wanted to see if we could identify differences among students at risk of dropping out of different kinds of schools and programs. We were tremendously excited when we saw that our predictive models were able to help us predict student risk in the areas of progress and retention. We didn’t have the data then — until some students at our member insti- tutions reached graduation — for comple- tion predictions, but we were excited about the trends.
Moving ahead, we created common data definitions so that all of the schools in PAR could contribute their de-identified data to our single dataset. Over time this helped us with consistency and scalability. It’s important to note that we focused on outcomes, not processes.
We saw our participants working together, learning to trust each other in a really new environment. Sounds simple now, but we had a lot of natural enemies in
the “room where the data happened.” For- profit institutions and community colleges and online schools and competency-based institutions and traditional institutions, all sharing their student data. That was huge.
As Beth Davis, who served as our CEO at PAR, and I saw our success building even during the early years, we also recognized that if we didn’t know what we were going to do about getting students out of risk, then our work was never going to be particularly meaningful. That is when our interest in interventions and motivation began, which brought us to the Student Success Matrix. We went in search of advising and early alert and watch lists. We found Russ Little and all he had done with the Student Success Plan. Some
of our members wrote Educause IPAS grants to integrate PAR and Starfish, and before you knew it — Boom! — PAR became part of Hobsons.
It seems to me that in our quest for actionability, we saw that analytics are tools we get to use to help anticipate
making better decisions to support student achievement. And really, that was clearly our goal all along. So maybe what we are seeing more than anything is the value of action research, the benefits of using evidence to test our strongly held beliefs. More than anything we have learned that we should never, ever take our eyes off the prize of keeping student success at the center of our work.
CT: Of course, once PAR was ac-
quired by Hobsons and integrated into Hobsons product lines, PAR’s impact and relevance was felt more widely. Will PAR eventually be integrated into other tools, at other education companies be- yond Hobsons?
Wagner: One of our strategies for extending the power and reach of our analytical capabilities is to actively seek partners
with whom we can develop APIs for extending functionality. While there are some companies, and perhaps even some
33
CAMPUS TECHNOLOGY | March/April 2018