Higher education data are now more widely available than ever before. In addition to institution- and program-level data, nearly every state has, or is in the process of developing, a student-level longitudinal data system that can follow students from kindergarten through college.
Despite having an abundance of data, it can still be difficult to understand how well state colleges serve students. The production and dissemination of these data have focused on the needs of potential students and their families, which is less useful for state policymakers.
Further, higher education data tend to conflate institutional quality with student characteristics. Institution-level metrics fail to account for differences in students’ academic preparation before college and their families’ financial situations, both of which affect outcomes.
Researchers at the Urban Institute worked with policymakers in Virginia and Connecticut to explore how their longitudinal data systems can be used to produce more nuanced measures of institutional quality, resulting in five papers and a summary brief. These publications leverage state longitudinal datasets to explore various measurement issues in higher education: program-level graduation rates, earnings, adjusted graduation rates, equity gaps in graduation, and issues in calculating return on investment.
Measuring College Performance: Lessons for Policymakers
Measuring Program-Level Completion Rates: A Demonstration of Metrics Using Virginia Higher Education Data
Which Dollars Get Measured? Assessing Earnings Metrics Using Data from Connecticut
Comparing Colleges’ Graduation Rates: The Importance of Adjusting for Student Characteristics
Understanding Equity Gaps in College Graduation
Evaluating the Return on Investment in Higher Education