In The News

In a university teeming with 30,000 undergraduates, where the average freshman's GPA exceeds 4.0, it would be easy for struggling students to get lost and drop out. But the University of South Florida, using sophisticated software, is making a concerted push to identify students who are having trouble and quickly intervene to help. The results are unequivocal: a narrowing achievement gap, higher retention rates and more students graduating on time.

Enter big data. Powerful software maps patterns of success, then pinpoints students veering off track so they can get the support they need. Already, the effort has lifted USF's graduation and retention rates to new highs. And with the graduation rate, at least, the achievement gap between white and black students has been erased.

Cheryl Donahue is the VP of strategic partnerships at Civitas Learning, joining the team a year and a half ago. Donahue said she recognized her passion for helping others early on.

"By evaluating the strengths and weaknesses of leading analytics offerings, this report will help institutions better understand the current market and supply a framework to determine best fit within your institution." - James Wiley, principal technology analyst at EDUVENTURES

The Student Success Report includes: a framework to help decision-makers evaluate the tools that support student success, a market map of tools that support student success, elements for decision-makers to consider as they redesign support services for all learners, and seventeen in-depth product profiles detailing how products work and what differentiates them from other players.

The hottest topics on higher ed campuses today are unequivocally student retention and student success. As college and university academics and administrators, we cannot tackle these challenges without getting deeper, much deeper, into the realm of Big Data, predictive analytics and data science. Our critical path to success in improving the student experience is to develop a laser focus on data-based decision making.

Institutional researchers at colleges and universities have been collecting and analyzing data about student recruitment, retention and graduation rates for decades. In recent years, however, these activities—under new rubrics such as “Big Data mining” and “predictive analytics”—have taken center stage in higher education thanks to the conviction that today’s technologies can allow us to base critical strategic decisions on solid data models rather than on anecdotal information or personal intuition.

Analytics! In higher education, seeking meaning in patterns only observable from a distance is changing the way we see and know our students. Blurry clusters of dots—whether in student demographics, behaviors or circumstances—can provide a broader understanding.

In 2010, the Student Success Task Force at the University of South Florida (USF) presented a comprehensive plan to improve student success at the institution, based on the concept that student success is everyone’s responsibility.

Less than half of the nation’s college students graduate in four years, and even adding two more years to get the job done only increases the graduation rate to about 60%. So, colleges try to predict which students are going to struggle and funnel them into extra coaching and support services.