Comparing success of female students to their male counterparts in the STEM fields: an empirical analysis from enrollment until graduation using longitudinal register data

M. Vooren*, C. Haelermans, W. Groot, H.M. van den Brink

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Background
In this paper, we investigate the predictors for enrollment and success in Science, Technology, Engineering, and Mathematics (STEM) programs in higher education. We develop a sequential logit model in which students enroll in STEM education, may drop out from STEM higher education, or continue studying until they graduate in an STEM field. We use rich Dutch register data on student characteristics and high school exam grades to explain the differences in enrollment, success, and dropout rates.

Results
We find that females are less likely to enroll in STEM-related fields, while students with higher high school mathematics grades are more likely to enroll in STEM. Female students have lower first-year dropout rates at university of applied sciences STEM programs. With respect to study success, we find that conditional on enrollment in STEM, women are less likely to graduate than men within the nominal duration or the nominal duration plus one additional year. However, female students do perform equally well as male students in terms of graduation within 10 years.

Conclusions
We conclude that STEM programs are less popular among female students and that female students are less likely to graduate on time. However, females perform equally well in STEM higher education in the long run. For this reason, policy should be geared at increasing study success in terms of nominal graduation rates among female STEM students.
Original languageEnglish
Article number1
Number of pages17
JournalInternational Journal of STEM Education
Volume9
Issue number1
DOIs
Publication statusPublished - 3 Jan 2022

Keywords

  • STEM
  • Higher education
  • Study success
  • Sequential logit model
  • Register data
  • GENDER-GAP
  • INFORMATION-TECHNOLOGY
  • HIGH-SCHOOL
  • MINORITIES
  • EDUCATION
  • SCIENCE
  • WOMEN
  • COMPETITIVENESS
  • STEREOTYPES
  • CONFIDENCE

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