There is a planning problem facing colleges and universities across the United States.
While Guided pathways, highly structured educational experiences designed to help more students progress through college and graduate, have continued to show promise, a new survey from AACRAO found that few institutions think they do a good job using data that effective scheduling demands.
Of the more than 300 undergraduate institutions in the U.S. and five other countries surveyed by AACRAO, only 18% said they use data well to analyze class demand at their campuses. Just 14% said they are skilled at deploying data to analyze demand for academic programs.
More than two-thirds of classes at four-year public universities are either over-subscribed or underutilized, according to Ad Astra’s data. Too many available class sections is a waste of institutional resources. Too few class sections means bottlenecks and delays for learners. These numbers are unacceptable.
Using data to help learners isn’t a novel concept in higher education. Just three years ago, a trio of organizations — the Association for Institutional Research, EDUCAUSE and the National Association of College and University Business Officers — urged institutions to deploy data to better understand and meet the needs of their students. Their joint statement carried the provocative title: “Analytics can save higher education. Really.”
In August, U.S. Education Secretary Miguel Cardona announced a new $5 million college completion fund for institutions of higher education to use data-driven and evidence-based tools to improve student success.
But the recent AACRAO survey underscores the notion that higher education still has a long way to go to better leverage course scheduling — a proven tool for improving student success. According to the survey, the vast majority of institutions said demand analysis is crucial to ensuring that students get the classes they need to stay on track to graduate. It’s also an important tool for managing limited institutional resources and remaining within budget. But many colleges reported that they ran into barriers to using data to accurately forecast class and program demand. The top 3 issues: a lack of time, tools and staff expertise.
Failing to use data to improve scheduling often leads to academic offerings being misaligned with a rapidly changing student population. Institutions of higher education have seen the emergence of what Excelencia in Education calls post-traditional students — first-generation, working and adult students who have different needs than the more affluent 18-to-22-year-old learners that higher education was originally designed to serve. The surge in online college enrollment during the COVID-19 pandemic further complicates matters
Meeting student needs requires more than data-informed scheduling based on class and program demand. Colleges and universities must also analyze how students need to take classes.
Working learners lack the time to drive an hour to get to class or to endure long waits on campus between classes. Going to college already requires enough sacrifice. Classes should be scheduled around a learner’s busy life, not the other way around. In addition, prior and current research suggests that students on average do worse in online courses than in on-campus in-person classes. Students who take most or all of their classes virtually will need extra help, and colleges that know how to work well with data will be able to find and support these learners.
Meeting the needs of post-traditional students requires what Complete College America has labeled structured schedules. These are not flexible schedules optimized for student exploration. Instead, structured schedules lay out clear completion paths for students to start and finish an academic program in a direct and predictable way. This type of scheduling can happen only when colleges prioritize demand analyses of both classes and academic programs and pair them with data-informed planning throughout the institution.
Critics of structured schedules accuse them of being too rigid, of robbing students of the chance to discover an interest or talent they didn’t know they possessed. A few institutions have even told us that they refuse to publish pathways or degree maps because they believe students should explore the curriculum and not be so laser-focused on graduation.
Optimizing for exploration instead of predictable completion paths makes it extremely difficult for the post-traditional student to stay in college and earn a degree in a timely fashion. Well-defined degree maps and structured schedules can support a healthy amount of course choices in most academic programs. Any institution committed to improving graduation rates and closing equity gaps is obligated to provide clear and data-driven completion paths.
Colleges and universities routinely say they’re all about improving student success. But until they prioritize data-driven planning and scheduling required to improve outcomes and close equity gaps, they will fail to realize their aspirations for student success.
Tom Shaver is Founder and CEO of Ad Astra.