  Higher education plays a critical role in driving an innovative economy by
equipping students with knowledge and skills demanded by the workforce. While
researchers and practitioners have developed data systems to track detailed
occupational skills, such as those established by the U.S. Department of Labor
(DOL), much less effort has been made to document skill development in higher
education at a similar granularity. Here, we fill this gap by presenting a
longitudinal dataset of skills inferred from over three million course syllabi
taught at nearly three thousand U.S. higher education institutions. To
construct this dataset, we apply natural language processing to extract from
course descriptions detailed workplace activities (DWAs) used by the DOL to
describe occupations. We then aggregate these DWAs to create skill profiles for
institutions and academic majors. Our dataset offers a large-scale
representation of college-educated workers and their role in the economy. To
showcase the utility of this dataset, we use it to 1) compare the similarity of
skills taught and skills in the workforce according to the US Bureau of Labor
Statistics, 2) estimate gender differences in acquired skills based on
enrollment data, 3) depict temporal trends in the skills taught in social
science curricula, and 4) connect college majors' skill distinctiveness to
salary differences of graduates. Overall, this dataset can enable new research
on the source of skills in the context of workforce development and provide
actionable insights for shaping the future of higher education to meet evolving
labor demands especially in the face of new technologies.
