How an analytics-driven approach can help reduce student attrition
Part 2 of 3
As discussed in part one of this three part blog series, first-year college or university students are searching for an exceptional experience, but when they don’t find it, many of them leave the school in which they enrolled. For many of these students, attending college or university is the first time they have spent significant amounts of time away from friends and family. Feelings of loneliness and homesickness abound. Students also find the academic environment challenging; students who cruised through high school struggle in the college curriculum and may not feel they belong in the university.
According to Leaving Academia, a website focused on attrition, these are some of the reasons students leave college:
- Too much fun at the expense of classes and grades
- Academically unprepared; burned-out on education
- Financial constraints; low on funds
- Academic climate/fit
- Lack of advising, guidance
- Demands from part-time or full-time employment
In this second installment, we’ll focus on two areas: financial constraints and academic climate/fit. Data and analytics can address some of those issues by helping college and universities reduce the likelihood of attrition and to create an exceptional student experience.
Financial constraints; low on funds
College is expensive, and today many students rely on some type of financial aid to get a college or university degree. Identifying students who may be at financial risk of dropping out is an area where analytics can have a major impact. Finding students who are having a hard time meeting their financial obligations to the institution, whether knowingly or unknowingly, can help keep students enrolled in school. Take Teddy Boumboulis, a student at Towson State University. Teddy was featured in a John Kelly column in The Washington Post in March 2015. Teddy required financial aid and thought he had it covered; unfortunately, he was shocked when Towson State asked him not to return for the winter semester because his bills were unpaid, something he was unaware had happened. It turns out the state agency tasked with paying Teddy’s bills and Towson State failed to exchange the proper information on Teddy and he was asked to leave.
Happily, the situation was rectified and Teddy can re-enroll, but not after losing a semester. Simply sharing information would have prevented this from happening. But the question arises: Could a more rigorous process of sharing information, monitoring progress and alerting Teddy of problems before they became serious have prevented this situation? Most likely. The application of data and analytics to identify possible issues with students has helped many universities keep students like Teddy enrolled.
Fit is a key component of retention. Students need to feel a sense of belonging and to see themselves as fitting into the institution they are attending. When this doesn’t happen, students may think they’ve chosen the wrong school—and then leave. However, using analytics to understand the model of the type of student who thrives is helping colleges and universities drive more targeted recruiting efforts aimed at high school students who match this model of the successful student. That data includes information such as demographics, fields of study, geography and other factors. Ithaca College in upstate New York is applying data and analytics in innovative ways to recruit the right kinds of students, seeing applications increase by 32 percent year over year.
An analytics-driven approach can help colleges and universities build an exceptional student experience. To see how, visit us at IBM Analytics for Education.
Read part three of this three-part blog series.