It sounds like an idea any university’s leadership can get behind: Using data to make a positive difference in the lives of students. But it can also be overwhelming. What’s the right kind of data to collect? How can it be used to make improve a student’s experience? The problem seems complex. The solution doesn’t have to be.
Many universities are finding success in analytics by keeping things simple and building from there. Here are some lessons learned from their successes, and how you can go about using data to make a difference for students at your university as well.
Find the right technology
Not every solution that works in the business world can be applied to the world of academia. You need an analytics solution that is flexible and allows you to ask the right questions.
Universities collect all kinds of data when a student enters the community—from birth date to high school performance—and then continue to gather data on the student throughout his or her time at the university. That data could be focused solely on the student, like course load or GPA, for example, but it could also be information the university uses in accreditation processes, like an evaluation or portfolio work. Your analytics solution needs to be able to work with that data to produce the results you are looking for.
That collection results in the possibility of millions of data points for a university, some of which is static—a student’s hometown, for example. But to be able to make a positive change for a student, users need to be able to identify the data points that are in a position to be changed by the student’s experience at the university.
For example, Southern Connecticut State University began a process in 2007 to promote a data-driven process of educational change at the university. In addition to collecting data, the university tracks students for seven years—whether or not they complete their academic studies at SCSU. The university uses the data to figure out the issues it needs to address, and then it begins programs to address those findings.
The programs, called campaigns, could focus on issues such as retention. If a student is showing signs of struggle in his or her chosen field, for example, the university might redirect that student to another major within that field where he or she is likelier to find success rather than leave school entirely. Or the university might use the data to identify a first-generation college student who may be likely to leave school because of a lack of support from home and put that student in a situation where he or she will stay. (One example includes having such students live in dorms with residential staff members who themselves were first-generation college students.)
Understand the data
The right data solution will allow a university to conduct analysis on more of an individual student level rather than just at a large group level. For example, the fact that someone is a first-generation college student does not alone mean that person is likely to leave school before graduation. It is a combination of that data point plus others that guides the university towards making any change or intervening in a student’s experience.
It is important to understand the nuances of the data so that changes aren’t being made arbitrarily. Sometimes the data could indicate that the biggest difference a university can make in a student’s experience is to make no change to that experience at all.
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