To read all the articles in this series, click here.

Graduation and retention rates will need to be prioritized by higher education as it looks to the future. Providing access without accounting for associated outcomes will no longer be possible for any institution in America. Colleges and universities must develop strategies to not only recruit, but also to retain and carry, as many students as possible to the graduation stage. Improving success rates will not only prepare students for meaningful careers and opportunities, but it will also increase enrollment rates, and cement the university’s place as a valuable and vital institution.

Retention and graduation rates have historically presented a persistent challenge for less selective institutions. This is partially because they cater to those who may be unprepared for college as a result of their primary and post-primary experience, or who are first-generation, low-income students. These populations are most at risk of dropping out. A complex range of factors influence student success at each college, and they must be understood in more detail.

Using Data Analytics to Retain and Graduate Students

To pull apart these issues, your university must have a solid understanding of the demographic it serves. One method many schools are trying? Using data analytics to improve retention and graduation rates.

Data analytics can be used in a variety of ways. First, they can help colleges find patterns among students who are failing courses. Colleges can figure out whether there’s a particular subset of students that are more likely to fail. First generation college students, minorities, or female students may all be more likely to struggle in college. By determining if these groups are falling behind, colleges can figure out their next steps to help these students.

Colleges can also use data analytics to find courses that are the most challenging for students. It may be a particular department, professor, or type of course that is causing a disproportionate number of students to fail and ultimately drop out.

Keeping data on individual students can also help target struggling students. Data analytics can reveal exactly what students struggle with. This can be accomplished by tagging assignment types or course types and measuring where a student performs the worst.

Sharing this data with students and professors can also be a powerful tool for improving outcomes. Once it’s clear what a student, or a group of students, is struggling with, interventions can be used. Professors who find that many students fail a particular course may offer more tutoring or additional resources. Students who learn that they struggle with a particular skill, such as writing, can seek out help with that specific skill.

Higher education must thoroughly examine its own practices in terms of the strategies faculty and administration are employing to ensure students persevere with their studies and ultimately graduate. A coordinated effort will be required as the landscape changes and adapts to meet future challenges.