Association for Public Policy Analysis & Management

By 2020, 65 percent of all U.S. jobs will require some postsecondary education or training (Carneval, Smith, & Strohl, 2013). However, only 40-45 percent of adults have completed a postsecondary credential (Lumina Foundation, 2017). To both meet the needs of a growing and changing economy and to improve the economic outcomes for their residents, most states have set specific goals to increase the share of adults with a postsecondary credential. These ambitious goals -- which typically call for increasing postsecondary attainment to 60 percent within the next decade -- are not attainable by increasing credential completion among traditionally-aged college students alone. As such, one of the key strategies to meet these goals is to engage with adult workers who completed some college-level credits, but left before earning a credential. Despite the importance “some college, no degree” population (SCND) to achieving states’ ambitious educational attainment goals, this population is still largely a black box. The goal of this study is to provide an in-depth descriptive analysis of the SCND population; this deep dive will allow us, as well as other policy-makers and practitioners, to more effectively design targeted interventions to increase re-enrollment and credential completion. We perform this analysis in the context of community college students in the commonwealth of Virginia. We use individual-level, linked higher education-workforce data for several cohorts of entering Virginia Community College System (VCCS) students to provide the first detailed descriptive analysis we are aware of for this population. In additional to enrollment and degree completion records, this data allows us to observe quarterly employment records for each individual in Virginia UI records before, during, and after their enrollment at VCCS, starting in 2005. Using this highly detailed data, we first characterize the magnitude of the SCND population in Virginia and compare its demographic characteristics, academic experiences, and employment and earnings trajectories to the population of graduates. Stemming from this descriptive analysis, we then work to identify the types of individuals who would likely benefit most from re-enrollment intervention efforts. For example, we estimate the SCND versus graduate “gaps” in employment and earnings outcomes for specific college by program of study combinations. We also examine whether the SCND-graduate gaps vary based on how much progress SCND students made towards a degree.