STEM refers to four fields of study and occupation: science, technology, engineering, and mathematics. But STEM has taken on social and political meaning far beyond the sum of its component parts. Public and policy discussions of STEM, whether in education or employment, rest on a startling lack of clarity about what counts as STEM. Most studies of postsecondary STEM education focus on students’ programs of study as the measure of STEM education, but we find this metric leads to substantial mismeasurement. Instead, we argue that examining STEM course taking is a more accurate measure of STEM preparation among college students. This descriptive study establishes conceptual and operational definitions of STEM coursework and uses nationally representative college student transcript data to develop a more accurate measure STEM course taking. Finally, we analyze the extent of potential mismeasurement and estimate STEM course taking using this revised classification system. Among bachelor’s degree students, we find wide variation in the number of STEM courses completed by students both within and between programs of study. Moreover, we find that many students in non-STEM programs of study complete substantial amounts of STEM coursework at levels comparable to that of many STEM students.
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THE MISMEASUREMENT OF STEM: EVIDENCE FROM COLLEGE COURSE CLASSIFICATIONS
STEM acronymically refers to four areas of inquiry – Science, Technology, Engineering, and Mathematics. But as its use has become ubiquitous, STEM has taken on social and political meaning far beyond the sum of its component parts. In this paper, we take a first step in clarifying the analytic categories of STEM in education. This, we propose, is a necessary first building block for STEM analysis – to understand what constitutes STEM coursework, the constituent element of a STEM education. We first review the STEM definitional problems we have identified in the process of examining two sets of NCES nationally-representative data, provide analysis of the extent of potential mismeasurement, and estimates of impact. We then outline an approach to resolving the mismeasurement problems in nationally-representative postsecondary student surveys. DOI: https://doi.org/10.7282/00000318
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- Award ID(s):
- 1561687
- PAR ID:
- 10521112
- Publisher / Repository:
- Rutgers University
- Date Published:
- Subject(s) / Keyword(s):
- STEM workforce Economic Policy Educational Administration and Policy Higher Education STEM Education Sociology Education Standard Reference Data
- Format(s):
- Medium: X
- Institution:
- Rutgers University
- Sponsoring Org:
- National Science Foundation
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