Discussions of higher education quality almost always treat institutions monolithically. As such, we raise concerns about whether University of Phoenix students are well prepared or Clinton Hill Junior College’s student loan default rate as if every department and degree is the same. While it is easier to discuss colleges and universities as undifferentiated entities, doing so presents real information problems for consumers–especially at for-profit institutions. Fortunately, there’s a solution that requires neither setting new precedent nor adding substantial additional burdens to schools.
To understand the problem of undifferentiated default rates, consider the case of the Kaplan Career Institute ICM Campus in Pittsburgh. That school had 1,028 borrowers in its 2007 cohort and a default rate of 22 percent. But this data tells us nothing about which of the 10 different programs offerings produced the 228 defaulters. As a result, someone applying for the medical assistant program could be paying good money for a program with a default rate three times higher than the school average, while other students shy away from the electrical technician option since they have no way of knowing that it has a very low default rate. Or maybe the story is reversed. It’s impossible to tell unless the U.S. Department of Education were to start disaggregating default rates by program.
Knowing program default rates better reflects the actual decision-making process of students, who are more likely to select a school for a program, such as occupational therapy assistant, than they are for a brand or name. Someone going for accounting management training does not care how well a school’s nursing program is–it is highly unlikely they will take classes in that subject. They care about how their specific program will help them in their job search and career advancement.
Disaggregating cohort default rates would basically treat each program kind of like its own institutions. Schools would report borrowers by program for a given cohort year and the Department could then calculate the default rate. Minimum program cohort sizes–such as 30 borrowers–could be added to ensure student privacy and make sure the calculations do not reflect just a few students. The Department could then choose to enforce similar penalties–make a program ineligible for federal aid if the default rate is too high–or even just use it as a way to provide more information for consumers.
Getting institutions to break out cohort default rates by program is neither a huge departure from existing policy discussions nor as hard to do as one might think. The Department is already considering rules that would limit student borrowing based upon their program’s expected earnings, so there is already precedent for no longer looking at colleges as uniform institutions. And institutions are already capable of tracking students by program since they have to report the number of student completions by a detailed set of program types as part of their surveys for the Department’s Integrated Postsecondary Education Data System (IPEDS). Asking schools to take this information a step further and report both completers and dropouts by program would thus not be that onerous.
And even if this took a little bit of extra work, the costs are more than outweighed by the benefits to consumers. Though students at traditional four-year schools may pick their institution solely based on a name, those attending a for-profit college or university have usually chosen it for a specific program or credential. Providing them with better information about their likely experiences for that program would be a powerful decision-making tool. Just as all colleges are not the same, neither are all the units that comprise an institution of higher education. It’s time that our default rate policy reflect that.