For some, the movement towards “Big Data” and analytics has been an exciting opportunity within the higher education community. For others, the idea of collecting and interpreting data fills them with dread. Many are concerned about how the data is collected, who collects it and what is being stored. Even more have serious reservations about how the institution will use data to assess their role and effectiveness, particularly if they work in student affairs or student support services offices.
While it can be difficult to overcome the fears and preconceptions that program-level staff have about data, these strategies can lay the groundwork for promoting more data-informed practices at your institution.
Focus on Improvement, Not Assessment
In student success divisions, it is not unusual for someone to ask, “Did that initiative increase retention rates?” or “What impact did that investment have on graduation rates?” Determining which programs and services have a direct and measurable relationship with student outcomes is extremely complex at best, so many doubt the effectiveness and accuracy of analytics as a tool to measure impact. However, in recent years, predictive analytics technologies have made impressive inroads showing patterns of student choice (e.g., which class should I take?) and student behavior (e.g., I always registered for classes on the first day of the term) as well as relationships between different student success goals (e.g., the importance of completing math during the first year).
Staff that have access to this kind of information can better serve students and more efficiently use available resources. Instead of focusing on data as an assessment tool, focus on explaining ways that data can answer important questions they may have about what students need and what students decide, so they can better meet those students where they are. Data can help departments to allocate resources by revealing what services students utilize most often and when students use those services, so staff can provide those resources in ways that maximize their impact by reaching the students who want and need it the most.
See the Big Picture
There is a common saying about working with students: We spend 90 percent of our time on 10 percent of our students (or on 10 percent of the job, for those not working directly with students). Working through complex problems or those special exceptions often times gives the impression that something is a major problem that needs to be resolved. For example, over the course of two days, more than ten freshmen will visit the same Student Success Center because they were struggling to register for courses online—even though the required orientation course introduces and teaches students how to use the portal. It would be very easy to start to question if the program coordinator should update or change the orientation course’s content. However, after reviewing data showing the registration patterns of all freshmen, the data did not show consistent registration issues across large numbers of students. This added information changes this issue from a widespread, systematic problem to a limited, potentially isolated problem.
The reverse is also true. Being able to see the big picture can help reveal problems that are mistakenly perceived as unrelated or restricted to a specific student or class. For example, an advisor talks with two different students struggling with a math class. Because math is traditionally difficult for some students, the advisor direct students to utilize standard resources like tutoring. However after looking at assessments and final grades for all students who attempted the same course across three semesters, the math department found the threshold scores for the online assessments were likely too high to show progress and success for this terminal math course. Once the department chair reviewed this larger data set, it became clear there was a pattern in student performance that revealed an issue that was not found in smaller numbers of students.
Data Is Empowering
By having access to their own data and having the autonomy to interpret it, departments and the individuals that work in them can construct their own narrative. It is often difficult to move beyond talking about what you do towards finding ways to show what you do. Data can be an important part of demonstrating to others the impact that you have on students: the numbers you serve, the diversity of programs you offer, the frequency with which you provide services and much more. Assessment is not only about causation and return on investment. Consider how data can help you show relationships (e.g., on average, our professional advisors across campus had face-to-face contact with students over 1000 times during the first two weeks of the semester) or describe the scope of an office’s reach (e.g., over one-third of the students supported by one college’s Student Success Center are not following degree programs from their college). It is powerful to have the resources to celebrate and share accomplishments without relying on others to do it when and how you would like.
Bringing It All Together
By focusing on the positive, leaders can show program-level staff how to make data work for them and encourage its use as an important resource. That said, for data to really be valuable for program-level staff, it is essential that those on the frontline feel data is accessible to them. Accessibility takes on two different forms: having access to the type of information that is relevant for their role at the institution and having the skillset to work comfortably with data.
Give staff members the opportunity to discuss the types of data they need and provide strategies to make it easier to access what they need. Providing resources to support the processing and interpretation of data can be an important mechanism for removing barriers. Make sure your staff have access to offices and individuals that can help them work with data, such as institutional research and university assessment offices, or faculty and graduate students interested in program evaluation or Big Data.
It may also be necessary to develop more visual data representations, such as dashboards or infographics, to help people more easily uncover patterns or problems. After this final step, the institution has established a solid foundation for promoting and supporting data-driven management.
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