If you were making one of the most important and expensive decisions of your life, how much of the necessary information would you want to have? About 100 percent? 75 percent? Would you settle for 50 percent?
Probably not. You would want as much information as possible. But consider what the reality is for making decisions about going to college.
Only 47 percent of students are counted in federal graduation rates and roughly one-third of postsecondary graduates are left out of data on post-college earnings.
Students—along with policymakers, businesses, and many others—want to rely on high-quality data to determine the effectiveness of institutions and the quality and outcomes of their programs. But they can’t because we lack comprehensive, accurate federal data to tell us whether America’s colleges and universities are fulfilling their mission to help students earn the degrees or other credentials they need to get good jobs.
The shortcomings and complexities of federal higher education data and reporting systems are well-documented. Consumers need program-level outcomes data to inform their decisions about where to go to college and what to study—but our current data cannot perform this vital function. We should always ask if the collected data could
- be used to help institutions understand and improve their outcomes,
- help consumers understand how specific institutions and programs are doing, and
- help policymakers steward public investments.
Data collection aimed at producing information for consumers—especially those considering a purchase as important as a college education—must help them make smart decisions. These data should be publicly accessible and understandable; ensuring that consumers have the information they need to guide their education and training toward the degree, certificate, or other credential they need to find and keep jobs. Data collection used to judge the effectiveness of institutions is equally important. Without careful examination of data, we can’t know which approaches to education yield desired results of increased affordability, completion, attainment, and equity. So, appropriate data collection on all fronts is critical.
Over the years, Lumina Foundation has supported research that shows the following principles are essential to harness the power of data for institutional improvement and consumer empowerment:
Students, policymakers, and other stakeholders should have access to key indicators of quality and measurements of the return on investment for both students and taxpayers. Quality-assurance metrics must validate that institutions provide students, especially low-income students and students of color, with adequate access to education; credentials that represent demonstrated learning; supports that help students complete their programs, and confidence that the earned credential was well-designed to help graduates gain financial stability by using what they have learned. Where appropriate, these metrics also should reflect the characteristics of different types of institutions and the students they serve.
Data and metrics must be comparable and consistent across education providers and states. Without this, it will be nearly impossible to measure outcomes and properly inform consumers, because one-third of students transfer at some point before earning a degree, and 27 percent of those who transfer do so across state lines.
Data collected and shared must reflect all types of students and the totality of their experience. When we leave students out of data systems we are effectively leaving them out of the policymaking process. And that has real implications for efforts to drive equity and enhance opportunity for the most underserved students. The growing need for more accurate and comprehensive data on why today’s students succeed or fail can most effectively be addressed through the thoughtful and deliberate development of a secure, privacy-protected student-level data network. Allowing data on students’ progress to be matched with other federal data systems to allow for the reporting of more comprehensive, higher quality program- and institutional-level data will help us all assess how we can better help students move to, among, and through providers of post-high school learning and in to the workforce.
Data collected on student outcomes must be comparable across all federal programs connected to education after high school. Today, there is no way to compare outcomes from programs at the federal departments of education, labor, veterans affairs and defense, even if these programs serve the same or similar groups of students. Each agency develops its own indicators of quality, and each interacts rarely, if at all, with other agencies and programs that serve the same or similar groups. There is nuance here to be sure—and some differences in data sources and measurement intervals are appropriate—but a more robust match on the underlying data will allow all federal programs charged with cultivating education and talent to comparatively evaluate their effectiveness.
And while we believe these principles are important, the principle that matters most is a simple one: we can do better.
We can do better than 47 percent.
We can do data better.