Driving Analytics to the Front Lines of Education

Charles Thornburgh & Mark David Milliron, Founder & CEO, Co-Founder & Chief Learning Officer, Civitas Learning
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Charles Thornburgh & Mark David Milliron, Founder & CEO, Co-Founder & Chief Learning Officer, Civitas Learning

As it has in many industries, technology has been a disruptive force in higher education. Indeed, the infrastructure for teaching and reaching students over the last 20 years has changed radically. From the early days of transitions to large-scale, integrated ERP systems, to the emergence of Learning Management Systems (LMS) that support traditional, blended, and online delivery, to the rise of social networks, digital textbooks, and Massively Open Online Courses (MOOCs), CIOs in our sector have been riding a technology tiger for decades now.

Even with all this change and technology adoption, however, what haven’t changed are student success rates. With the notable exception of elite institutions with selective student populations, higher education institutions are still challenged to help more of the students that start their journey through post secondary education. Today more than 37 million adults have significant college coursework and no credential to show for it. Only about half of the students that begin higher education finish. And if you’re a low-income student, you are far more likely to leave your higher education quest with debt than with a degree. A host of initiatives from the U.S. Department of Education, state agencies, foundations, associations, and non-profits are trying to address this challenge. However, we think CIOs are going to have to play an even larger role if these efforts are to bear fruit.

The 2.0 Education CIO: Using Analytics to Empower the Front Lines

In a very real sense, the focus of the first wave of technology adoption in education, and by extension the focus of most education CIOs, has been on blocking and tackling: the establishment of the core IT infrastructure necessary to support the functioning of the institution, followed by the adoption of enterprise software platforms that automated
existing business processes and made institutional operations and compliance function more efficiently and effectively. While these initial efforts were essential, it should be of little surprise that they didn’t move the needle much on higher education’s central mission—improving student outcomes. Now that these core investments have been made, institutions across the country are realizing that analytics provides an opportunity to leverage them to drive improved results for students—and the industry’s most forward-thinking CIOs are leading the charge.

Like a host of other industries that have moved quickly to adopt and leverage technology, and harvest the resulting data—e.g., retail, gaming, professional sports, healthcare—interest in analytics has become a hot topic in education. Many believe that the use of these data might lead to the realization of the technology dividend promised by the work of the last two decades. Moreover, these data initiatives will become even more useful as the digital footprints students leave behind become deeper and clearer as they engage the newly built-out technology infrastructure in their institutions. We agree. For those CIOs who are thinking strategically about using analytics to connect insight to action, the opportunity to have an impact is enormous.

The Million-More Matrix
The Million-More Matrix is a tool that has emerged in our early work with CIOs and others on the leadership teams at our member institutions. It’s based on the basic idea that if we want to help our country move toward a day where a million-more students succeed on educational pathways, then we need to help more institutions leverage their technology and data in support of their strategic goals.

If you think about Action—innovating with new policies, practices, and technology tools to help more students succeed—on the X axis, and Insight—the ability to collect, analyze, and strategically leverage data about student pathways—on the Y-axis, you end up with an interesting tool to think about a given institution’s strategic technology and data approach against their stated mission. Let’s take a look at each quadrant:

Low Insight/Low Action: Status Quo (Losing Ground)
In this quadrant, an institution is usually only doing data work because of regulations and reporting requirements. They may use some data in strategic planning, but it’s usually trumped by leaders who can weave stories about their versions of what’s happening. Moreover, these institutions are convinced that their way of doing things is working and are unlikely to be motivated to change without some kind of existential threat.

High Insight/Low Action: Intellectually Curious (Edu-Voyeurs)
In this quadrant, institutions are typically part of state systems or initiatives that are harvesting their data and have done deep analysis of student success rates and pathway patterns. However, these analyses tend to be dated (i.e., the students have already dropped out or graduated) or far removed from the front lines. Specifically, faculty, advisors, and students are not privy to data that could help them navigate their learning journeys more effectively. The worst outcome in this quadrant is rich data going into little seen reports or worse, used as fodder for blaming, shaming, bragging, or bashing.

Low Insight/High Action: Best Practicism (Risky Bets)

In this quadrant, motivated change agents are moving—and often moving quickly. To jumpstart their work, they are looking for “best practices” and assume that these strategies have been tested somewhere else. Often, however, these practices, policies, or technology tools are either taken on as pilot programs that have little impact for most students— i.e., they don’t scale—or worse, they are highly risky bets taken at scale with little to no view to likely impact. Leaders
operating in this quadrant are often well intentioned; however, they are ready and willing to change the way students, faculty, and advisors do their work, but have little to fall back on except rhetoric when challenged as to “why” these changes are taking place.

Put simply, CIOs are put in a difficult place in each of these three quadrants. Many feel either stuck in place, or constrained by inaction, or convinced they are enabling risky change. However, if CIOs can help move conversations into the upper right quadrant, their technology and data work can be a significant part of the solution.

High Insight/High Action: Student Success Scientists
In this quadrant, there are no easy answers – just tough problems, interesting data, and a team of leaders willing to learn together. Using sophisticated analytics and predictive models that unpack insights about student pathways, the institution gets a clearer view of the connection of action to course completion, year-over year persistence, and graduation for each student. Even more compelling, by coupling these insights with front-line focused technology applications that go right to those doing the work of teaching, learning, and advising, a real difference can be made. Moreover, rapid testing of user interface design and messaging in these apps can be conducted to tune them for maximum, sustainable lift.

As CIOs help institutions move into the upper right quadrant, we’ve already seen that students can make more informed choices, access better learning resources, and engage support systems earlier if there is a problem. Advisors have a clearer view of high-achievers ready to be challenged and struggling students ready for outreach. Faculty can watch for engagement changes in near real-time, and test the effectiveness of instructional strategies and outreach. Moreover, with a commitment to using the data to test and tune their technology use and intervention and engagement strategies, these dedicated and tough-minded educators have been enabled to clear the way for improved student outcomes.

Our Chief Data Scientist, David Kil, comes from the world of health care and has helped us understand the lessons of their technology and data use. Deploying and studying interventions is useful, he says, but understanding patient life cycles and getting insight into when are right times to intervene, what kinds of interventions are best, and how they can be deployed at scale with new technology tools is the game changer.

Put simply, the lesson from this technology and data work in education is this: CIOs ready and willing to help their organization build the right infrastructure to get the right data to the right people in the right way—to truly enable action driven by insight—will be indispensible to the achievement of their institution’s most important goals. In our world, that means helping millions of students succeed on the pathway to possibility that is education.

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