This study aims to identify the skills earned through dual enrollment and how those skills drive adult labor market outcomes. The team will use large‑scale language models to infer likely skills embedded in community college syllabi and pair them with students’ grades. The researchers will organize these skills using the Burning Glass Institute’s skills taxonomy, which can be linked to local labor markets. Texas statewide data will be used to examine students’ Unemployment Insurance earnings, parental socioeconomic status, and county‑level disadvantage. At a time when high school redesign and dual enrollment opportunities are surging, the project will examine how specific dual enrollment experiences shape postsecondary enrollment, degree attainment, and early career outcomes, with particular attention to socioeconomic disparities. Using quasi‑experimental methods and novel AI‑based measures of course content, the study will also estimate the causal effects of dual enrollment participation and of the skills acquired through these courses, providing critical evidence for designing dual enrollment pathways that meaningfully enhance later economic mobility.

Data Sources 

• Data: Texas educational administrative and test data, community college syllabi, and National Student Clearinghouse postsecondary enrollment and completion records
• Mobility Outcomes: Texas Unemployment Insurance employment and earnings through Texas State Longitudinal Data System (SLDS)