How Data-in-Motion and Data-at-Rest Is Driving Innovation at Universities
April 19, 2016
University faculty and administration are in a race to stay alive.
They are aware of what has happened in the music, travel and publishing industries, where once-fat margins have been cut to the bone and former giants have been reduced to rubble.
Universities, those that work in them and care about them, are looking over their shoulders to imagine their future, while simultaneously experimenting to make their courses relevant in content and method for the social media-addled generation of students today. They are turning to data-in-motion and data-at-rest to give them an edge in the race.
More than most sectors, higher education and universities suffer from the Baumol Effect.
Faculty is no more productive now than they were in 1950, but their salaries continue to increase. The sticker shock faced by many families as they look at their first college bill reflects this, as much as diminished support for higher education by cash-strapped state legislatures. The frontier of data-in-motion is beginning to shape innovation in Universities.
Universities must increase efficiency in recruiting
All this has forced university administrators to require a deep dive into data from both their applicant pool and their existing student body to become more efficient in recruiting and maintaining students. This requires best-in-class data-at-rest services. These data are stored in university-wide admissions and ERP (Enterprise Resource Planning) systems – the central software system that integrates student records, human resources, purchasing and other mission critical information.
Asking more complex questions
In their quest to become more efficient, university administrators need to move beyond simple queries: Where are our most successful applicants from?; What is their educational, socio-economic and demographic background?; To much more complex and vitally interesting questions such as: to what extent do students in the admission pool respond to marginal financial incentives?
To attract more members of this group, what incentives are most effective: single grants for tuition remission? Work-study funds which extend over multiple years? Loans against future earning? Or tuition caps for the entire college experience?
Asking the right questions and having the data to explore the answers can help recruiters and give students a more individualized experience.
Predicting success and who may be at risk
Using such data-at-rest, coupled with in-depth interviews with students, can go beyond ad-hoc impressions by admissions staff in terms of what is an attractive inducement for attendance. They are able to go beyond just predicting which students will be academically successful. Using such data creatively can help tease out the reasons for the academic success.
And they conversely suggest which students are at risk, but also reveal simple and low-cost interventions that can save a student’s college career. This may mean a student stays in school with a lighter course load, changes their major to a choice which reflects their deep love (rather than the expectations of their family), or starts on a path where they take a semester off, but will have a successful academic re-entry after their time away. But using data-at-rest is only the beginning.
The frontier in higher education is storing, analyzing and utilizing data-in-motion.
For example, many faculty who teach large, introductory courses use audience response systems— “in-class clickers” —to pose multiple-choice questions and ascertain responses from students. While faculty do get instant responses utilizing this data-in-motion, there is no way for them to store and analyze these results, compare one class with another, or refine questions so they can be used on exams.
Using data-in-motion in this way requires different technology than data-at-rest.
Streaming data provides real-time insights users can respond to immediately. Providers such as IBM, Software Ag and SAS are leading the move in business intelligence.
Now, Universities can tailor data services to exactly what their educational institution requires and discover innovative ways to attract and keep students, while giving them a richer, more individualized experience and increased success.