The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
College Major Choice in STEM: Revisiting Confidence and Demographic Factors
Abstract
Using national freshman survey data, the authors examined confidence and background variables (e.g., gender, minority status, parental occupation) as predictors of science, technology, engineering, and mathematics (STEM) major choice. Logistic regression analyses revealed that students were more likely to choose STEM majors if they had strong confidence in mathematics and academic areas and had parents with STEM occupations. Although female students were unlikely to choose a STEM major, African American and Latina/o students were equally as likely to choose a STEM major as were White or Asian American students. Findings suggest that students' confidence level in their academic and mathematics abilities makes a significant difference in their initial STEM major choice. Study findings could assist educators, counselors, and policy makers in their efforts to promote student choice of STEM‐related majors and careers.
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Relation of self-efficacy expectations to academic achievement and persistence.
Lent, R. W., Brown, S. D., & Larkin, K. C. (1984) · Journal of Counseling Psychology · doi:10.1037//0022-0167.31.3.356 · Cited by 820
An Exploration of the Mathematics Self-Efficacy/Mathematics Performance Correspondence
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Educational Expectations of Asian American Youths: Determinants and Ethnic Differences
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Cited by
Anatomy of an Enduring Gender Gap: The Evolution of Women’s Participation in Computer Science
Sax, L. J., Lehman, K. J., Jacobs, J. A., Kanny, M. A., Lim, G., Monje-Paulson, L., & Zimmerman, H. B. (2017) · The Journal of Higher Education · doi:10.1080/00221546.2016.1257306 · Cited by 261
Trajectories in quantitative and humanities self-efficacy during the first year of college
Han, J., Usher, E. L., & Brown, C. S. (2021) · Learning and Individual Differences · doi:10.1016/j.lindif.2021.102054 · Cited by 15
Metadata
- Authors
- Moakler, M. W., & Kim, M. M.
- Venue
- The Career Development Quarterly
- Publisher
- Wiley
- Published
- 2014-06
- Volume
- 62
- Issue
- 2
- Pages
- 128-142
- ISSN
- 0889-4019 (ISSN-L)
- 2161-0045
- OpenAlex
- W2001798045
- Cited by
- 277
- References
- 23
- FWCI
- 41.57
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
