When students arrive on campus they have every intention of graduating with a degree that will help them pursue their goals. Unfortunately, many will not finish their degree, and in the US a staggering 40% will fail to complete their four-year degree in the next six years.
Retention matters for many reasons. For students, graduating successfully can have a transformational impact on their lifetime earnings and career satisfaction. For institutions, increasing retention rates improves rankings, reputations, and financials. But above all, I think there’s a more fundamental reason to address retention: it’s simply the right thing to do. Enrollment is only the first step we must ensure students are supported the entire time.
Students who choose not to continue their studies make that decision for a wide variety of reasons. Perhaps family obligations or financial constraints, which cannot be affected by institutional changes however, student engagement both in and out of the classroom is addressable. Universities can use new analytical techniques with the vast amounts of data they have about students to identify when someone is at risk of dropping out – before it happens – triggering targeted interventions from professors or advisors when that person needs it most.
Let’s look at a major source of student discontent – the ability to register for classes with few conflicts. This is one of the top five most important determinants of student satisfaction. Rather than spending hours/days trying to put together the right course options by hand, administrators can use analytics and AI to determine schedules based on the historical success of previous students. This allows them to quickly determine the best combination of classes for each student to take. We’ve been working with the University of Oklahoma to create a way for students to easily visualize and arrange their course schedules, freeing up advisors to focus their time on advising rather than scheduling.
AI can play many roles in improving retention. Considerable research shows that time spent with academic advisors is a key driver of retention. In one study of first-generation college students, researchers found that each additional meeting with an advisor increased the odds of retention by 13%. A study at the University of Washington found that 33% of students who dropped out said their inability to decide on a major was a significant factor in the decision to leave. As university advisors have limited time, implementing a chatbot with AI to handle routine administrative questions can free-up time to focus on complex questions, including degree-planning discussions and student satisfaction assessments.
Most institutions have adopted their own programs to improve retention, but for results to be fully realized, they need to be prepared to think innovatively, act quickly, and leverage these new technologies.
With so many transformational changes on the horizon, a well-educated future workforce has never been more important. By combining predictive analytics and AI through digital channels, universities can positively impact the student experience and drive higher rates of retention. I am keen to hear your view on the points I’ve raised and what they might imply for your university’s retention strategies.
Please leave a comment below or explore more at www.accenture.com/digitalstudent.