Helix CEO Matthew Schnittman did two things at the end of 2016: reflected on the relationship of enrollment growth and the institutional mission, and looked to the future of enrollment growth and data analytics in higher ed.
To celebrate a new year in higher education, Schnittman was one of a few education and tech leaders asked to both reflect on higher ed trends in 2016 and anticipate what the next year will bring to the industry for eCampus News. In light of his contributed reflections and projections, I recently sat down with Schnittman for further elaboration.
What is at least one trend that you believe was significant in 2016 and why; and what is one trend that you believe will gain traction in 2017 and why?
Enrollment growth firmly established itself as a bedfellow of the institutional mission.
MS: In 2016, institutions continued to discuss the tension between their ideological foundations and the economic realities they face. The 2016 Inside Higher Ed Survey of College and University Business officers revealed that “84% of CBOs say the enrollment level in a program is an extremely or very important factor in determining its future, making it nearly as important a factor as institutional mission and academic quality.” This statistic exemplifies the fact that colleges and universities are still grappling with how to pursue their missions while also operating in an era of decreasing federal funding, stagnating enrollments, and increased competition in the higher ed space. The fact of the matter is that the business realities in higher ed have closely adhered to the institutional mission, with no end in sight.
While the social and economic value of a higher education was vindicated in the Primer on the College Student Journey, published by the American Academy of Arts and Sciences in the fall of 2016, institutions were still plagued by stagnating enrollments. Yet the tension between the economic and ideological actualities in higher education is paving the way to opportunity. When institutions seek innovative ways to both grow enrollments and maintain missional integrity, they’re more poised to provide the economic and social benefits of a higher education. Institutions don’t need to abandon their missions to compete in the higher education market–they simply need to harmonize business best practices with quality, pedagogy, and ideology.
In 2017, institutions will embrace the relationship between data and human intelligence.
MS: Data analytics is a salient topic in higher education, and institutions are embracing data to enhance the student experience to varying degrees. Early adopters are now supporting analytics departments, and those who aren’t currently utilizing data are exploring new approaches and technologies to begin to do so. Yet as higher education looks to incorporate more data into their decision making processes in 2017, there is a danger in thinking that data alone can solve their challenges. Data should augment human intelligence, not replace it.
The key to striking a balance between data and human intelligence is to act on data insights with high-touch, on-the-ground strategies. Across the many systems and moving parts of the higher education institution, data can help aggregate the nuances inherent within the student experience. Yet data insights only carry weight when deployed by people who can navigate the humanistic elements of the student experience. Data sets the context, humans build the relationships. Seeing as how student-centric learning has been continually placed front and center in both structural and pedagogical conversations, institutions will find it natural to marry data intelligence and human intelligence to enhance the student experience on a holistic level.
What is one lesson you learned in 2016 from either technology use/implementation or from trying out a general ed trend or innovation? Also, how will you leverage this lesson for 2017?
MS: As institutions work to incorporate data intelligence into their organizations, their focus has largely been on single data points related to learning analytics (LMS log-ins, pre-registration behaviors, etc.). The problem with this approach is twofold: 1) single data points aren’t enough to inform interventions related to student performance, and 2) organizations that only utilize data to enhance student performance are ignoring how data can also ensure institutional health.
Decisions and interventions—regarding student performance or institutional health—will always be limited in their efficacy when they don’t incorporate enough data. If, for example, an institution finds that students who register for classes earlier perform better, then implement an intervention that requires all students to register for classes earlier, decision makers are ignoring the fact that the behavior may be indicative of a whole other subset of qualities or practices that speak more to student success than the single data point suggests. Thus, designing an intervention that moves up the registration deadline likely won’t address what’s driving successful students to register early.
And while institutions are concentrating their data efforts on student performance, 2016 proved that many organizations are struggling to ask questions that get at the health of the entire enterprise. A recent survey of 480 higher education decision makers revealed that 83% don’t know the cost-per-inquiry of their most effective marketing channels, and less than half have a formalized process for new program development. Student academic performance and institutional health are interconnected, and institutions are poised to start integrating data analytics on a more robust and holistic scale. Thus, in 2017, institutions must widen their perspective on data and leverage insights at an enterprise level instead of just focusing on student performance.