What is it about?

Using millions of university/college course syllabi from the Open Syllabus Project, we infer the skills taught in individual courses and characterize the taught skills of various colleges and fields of study (i.e., majors). Using post-graduation earnings data from the US Department of Education, we show that taught skills predict graduate earnings better than field of study or alma mater alone.

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Why is it important?

Skills have become increasingly useful for modeling workforce trends (e.g., ability to work from home or benefit from ChatGPT) and so similar data on the sources of skilled workers can improve our understanding of workforce development, upward mobility, and our adaptability to the future of work.


Labor economists and policy makers commonly use skills to distinguish workers (e.g., white collar or blue collar), but disruptions, like work-from-home during the COVID pandemic and new technologies including ChatGPT, demonstrate a need to refine our characterization of workers even further. Understanding workers’ specific skills will improve our understanding of their adaptability to future labor disruptions. This project contributes to this goal by creating new data reflecting the sources of “white collar” skills. As we improve our understanding of specific skills in the workforce, it is a natural extension to consider how education and policies can promote those skills during workforce development.

Morgan Frank
University of Pittsburgh

Read the Original

This page is a summary of: Connecting higher education to workplace activities and earnings, PLoS ONE, March 2023, PLOS, DOI: 10.1371/journal.pone.0282323.
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