From the Inside Sources Podcast

The big picture

Beth Akers, senior fellow at the American Enterprise Institute, discusses the critical role of data in improving higher education outcomes and decision-making.

Key takeaways

• Data transparency is crucial: Akers emphasizes the need for comprehensive data on student outcomes to help prospective students make informed decisions about their education.
• College Transparency Act: This proposed legislation aims to require colleges to collect and report detailed data on enrollment, completion rates, and post-college earnings.
• Addressing “data blind spots”: Current limitations in higher education data make it difficult to assess if institutions are serving all students equitably.
• Return on investment: Better data can help students evaluate the potential value of their college education and choose programs more likely to lead to successful outcomes.
• Balancing privacy and transparency: Akers acknowledges the need to protect student privacy while advocating for increased data availability to improve educational outcomes.

What’s next

As debates around student loan forgiveness continue, the push for greater accountability and transparency in higher education is likely to gain momentum. The implementation of data-driven policies could significantly impact how students, families, and policymakers approach higher education decisions in the future.

Why it matters

Higher education institutions need to be held accountable for student outcomes and embrace innovation to remain relevant and valuable.

The big picture

President Pulsipher emphasizes two main points:

• Increasing accountability for outcomes: Institutions should prove their value by demonstrating how they improve students’ lives.
• Encouraging innovation: Policies should incentivize new models that expand access, lower costs, and increase relevance to future work.

By the numbers

WGU measures its impact through the “Factor Graduate Return”:

• Graduates see a median 26x return on their investment
• Some programs yield over 50x return
• Even lower-return programs in education see 12-15x returns

Between the lines

President Pulsipher argues that higher education should democratize opportunity, not stratify society further.

The bottom line

President Pulsipher argues that higher education should democratize opportunity, not stratify society further.

The big picture

UMass Global Chancellor David Andrews advises the Department of Education to focus on improving student outcomes and experiences while maintaining accountability.

Key Points

• Challenge legacy metrics like seat time and Carnegie units
• Rethink “regular and substantive interaction” for the on-demand learning era
• Develop metrics that measure student growth or “lift” rather than raw outcomes
• Implement real-time predictive analytics to support struggling students
• Increase investment in innovation pilots, especially for working adult learners

The bottom line

The Department of Education should take more risks in piloting innovative approaches and work more collaboratively with accreditors to streamline processes and foster innovation.

By Stig Leschly, Postsecondary Commission

Almost all US college students – no matter who they are and no matter where or when in life they attend college – report that a higher wage, a better job and a viable career are their top motivations for going to college. A safer and brighter economic future is not the only reason students go to college, but it is the most common and fundamental one.

Policymakers are responding to this nearly unanimous ask from students that colleges improve their economic prospects. State and federal lawmakers are migrating toward accountability and funding policies based on whether institutions improve the earnings and employment trajectory of their students.

For this policy movement to thrive, it needs to address a mundane but serious problem: the inadequacy of the data systems on which it relies..

The data systems in question are mainly those run by education, labor and tax agencies in DC and in states. These data systems track and link together the vast student-level data – on students’ college costs, on their wages before and after attending college, and on their demographics – that enable policymakers to draw accurate and fair conclusions about the economic outcomes produced by institutions.

Unfortunately, these data systems are often under-resourced, siloed, or inaccessible, which stalls and distorts good policymaking.

For example, when policymakers assess institutions’ earnings outcomes, they are often left to rely, because of data limitations, on the absolute wages that students experience at some point after they enter or graduate from an institution.

This is problematic. Students’ absolute wages say almost nothing about the effect (positive or negative) that a given institution has on those wages. An institution might succeed in graduating students into high-wage jobs simply by selecting students who were already on track for high- paying careers.

Conversely, a non-selective institution that graduates students with seemingly unremarkable salaries might actually be doing extraordinary work if students’ actual wages are far above the wages they would have earned if they had never enrolled.

This sort of analysis of wage outcomes – often called value-added earnings analysis or wage gain analysis – takes into account the need-level and baseline earnings outlook of students who enroll in a given institution, and as a result, is far more accurate and fair than standard approaches to assessing earnings outcomes. And, it is possible only where underlying data systems are in good order.

An added benefit of surfacing the wage gains that institutions produce for their students is that it allows policymakers to make sense of the prices that institutions charge. Whether an institution is over- or under-priced depends on whether the institution generates wage gains for its students that are large enough to compensate students in a reasonable timeframe for their cost of attendance.

In another example of how data gaps inhibit good higher education policy, federal and state lawmakers have not done enough to monitor and regulate the economic outcomes of college entrants who never graduate, a group of students who comprise nearly half of US college-goers. This policy lapse is partly because lawmakers know so little about non-completers and their outcomes. They are typically under-tracked and sometimes completely ignored in higher education data systems. With better underlying data systems, policymakers would be able to track and set policy for the economic outcomes of all college entrants, not just those who complete.

This development would amount to a break-through. It would allow policymakers to sort out in detail – institution by institution, program by program – when dropping out is a problem for students (because it saddles them with high costs and no degree) and when it is not a problem for students (because they exit early and with few financial consequences).

A promising policy movement toward better economic outcomes in US higher education has started. For this movement to persist and for it to mature into sound accountability and funding policy, it needs to run on better student-level data systems in DC and in states.

Federal and state policy makers should immediately and aggressively fund improvements to these data systems. In its pursuit of better economic outcomes in US colleges, public policy can only be as good as the data on which it is based.