CIO uses customizable analytics engine to make data usable for the University’s specific goals.
Analytics technology, like MOOCs, soared in popularity within the last few years. But just like MOOCs, many institutions have found that the key to success is not in the technology itself, but in harnessing the capabilities of that technology to promote the university’s unique mission and goals.
The concept of analytics has become an interwoven fabric of the higher education tapestry. For years, institutions have amassed myriad data on student admission and retention, student GPA, and demographics; but, outside of data being used for budgetary consideration, or as a competitive metric against other institutions, higher education has only recently begun to harness the true power of predictive analytics and big-data mining for the purpose of improving the academic success rates of their students.
That’s because in 2010 there was excited talk of looking to data-driven predictive analytics models of large companies like Amazon and retooling them for a higher education context. The ubiquity of online courses and testing, e-textbooks, and social media meant that institutions were sitting on a mountain of capture-able digital data. At issue, though, was if it made sense to take something from businesses which, at their core, spring from a common culture and speak a similar language, and apply it to higher education—a space comprised of disparate institutional cultures that does not lend itself to a one-size fits all big data model.
Analytics are not a one-size-fits-all solution, say software experts and innovative colleges and universities. Every institution, through its missions and goals, is unique. So why aren’t metrics within analytics solutions as diverse as its users?
There is more benefit to building an analytics model from the ground up within a unique campus environment than in forcing an institution to conform to a standard model, says one innovative University CIO.
Enter LoudCloud and Grand Canyon University.
“We base our work on the philosophy that there is no one magic formula that can predict retention across all levels,” explained Greg Harp, chief marketing officer of LoudCloud. “A Harvard University student is going to have different learning characteristics than, say, a student at a community college. However, using technological and behavioral analytics, we can create a system that indicates, and helps support, unique outcomes.”
(Next page: Measuring everything and the importance of slimming it down)
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