STEM stereotypes predict students’ STEM career interest via self-efficacy and outcome expectations
Open accessAbstract
Background: Nurturing students’ interest in science, technology, engineering, and mathematics (STEM) careers is a major goal of STEM education. Although the relationship between students’ stereotypical beliefs regarding STEM careers and their career interest can be reasonably hypothesized, research investigating the extent to which and how students’ STEM career interest is directly or indirectly influenced by their stereotypical beliefs is lacking. This study investigated how upper primary students’ stereotypical beliefs regarding STEM careers predicted their STEM self-efficacy and STEM career-related outcome expectations and how these constructs predicted their STEM career interest. Structural equation modelling was used to analyse quantitative survey data of 824 fourth- to sixth-grade students and test the hypothesized models. Results: Students’ stereotypical beliefs regarding STEM careers negatively predicted their self-efficacy in STEM activities and career-related outcome expectations. Additionally, the students’ self-efficacy in STEM activities and career-related outcome expectations in turn predicted their STEM career interest. Conclusions: These results explain the potential indirect effect of STEM stereotypes on students’ career interest through self-efficacy and outcome expectations. The findings highlight the significant role of STEM stereotypes, self-efficacy in STEM activities, and career-related outcome expectations in students’ career development. The implications of this study for STEM education are also discussed.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Cognitive motivational constructs such as academic self-efficacy, self-regulation, effort control, and goal setting affect STEM students' academic performance and intentions to pursue and persist in STEM fields.
“such as academic self-efficacy (Chen & Zimmerman, 2007;Han et al., 2021;Luo et al., 2021;van Aalderen-Smeets et al., 2018), selfregulation (Shell & Soh, 2013;Zollman, 2012), effort control (Cromley et al., 2016), and goal setting (Shaw & Barbuti, 2010) affect STEM students' academic performance as well as their intentions to pursue and persist in STEM fields.”
From The Importance of STEM Sense of Belonging and Academic Hope in Enhancing Persistence for Low-Income, Underrepresented STEM Students (2024) · cites this paper as Luo et al., 2021
The section on relationships among self-efficacy, outcome expectations, and career interest reports that self-efficacy in STEM activities significantly predicted students’ STEM career interest. That supports the intention-to-pursue portion of the claim. The study concerns upper-elementary students and does not establish effects on academic performance or persistence in STEM fields; its discussion of persistence refers to learning, not remaining in a STEM field. The other constructs in the sentence are cited to other sources, not Luo et al. (LLM, conf=0.85)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003) · Department of Psychology - University of Koblenz-Landau · doi:10.23668/psycharchives.12784 · Cited by 8,975 · see citing works
Reporting Structural Equation Modeling and Confirmatory Factor Analysis Results: A Review
Schreiber, J. B., Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006) · The Journal of Educational Research · doi:10.3200/joer.99.6.323-338 · Cited by 6,937 · see citing works
Contextual supports and barriers to career choice: A social cognitive analysis.
Lent, R. W., Brown, S. D., & Hackett, G. (2000) · Journal of Counseling Psychology · doi:10.1037/0022-0167.47.1.36 · Cited by 2,285 · cited 1× · see citing works
“Lent et al. (2000) argued that perceived environmental factors can influence individuals’ career development by shaping the experiences that influence self-efficacy and outcome expectations.”
BackgroundArcher, L., DeWitt, J., Osborne, J., Dillon, J., Willis, B., & Wong, B. (2013) · Pedagogy, Culture & Society · doi:10.1080/14681366.2012.748676 · Cited by 308 · see citing works
Flagged first, then by citations
Research works printed but not linked: 52
- Allison, P. D. (2003). Missing data techniques for structural equation modeling. Journal of Abnormal Psychology, 112(4), 545-557. https://doi.org/10.1037/ 0021-843X.112.4.545. · DOI
- Archer, L., DeWitt, J., & Dillon, J. (2014). 'It didn't really change my opinion': exploring what works, what doesn't and why in a school science, technology, engineering and mathematics careers intervention. Research in Science & Technological Education, 32(1), 35-55. https://doi.org/10.1080/0263 5143.2013.865601. · DOI
- Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215. https://doi.org/10.1037/0033-295X.84.2.1 · DOI · Paper page
- Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs: Prentice Hall. · DOI · Paper page
- Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588-606. https:// doi.org/10.1037/0033-2909.88.3.588. · DOI
- Blotnicky, K. A., Franz-Odendaal, T., French, F., & Joy, P. (2018). A study of the correlation between STEM career knowledge, mathematics self-efficacy, career interests, and career activities on the likelihood of pursuing a STEM career among middle school students. International Journal of STEM Education, 5(1), 1-15.
- Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen, & J. S. Long (Eds.), Testing structural equation model, (pp. 136-162). Newbury Park: Sage.
- Capobianco, B. M., Diefes-Dux, H. A., Mena, I., & Weller, J. (2011). What is an engineer? Implications of elementary school student conceptions for engineering education. Journal of Engineering Education, 100(2), 304-328. https://doi.org/10.1002/j.2168-9830.2011.tb00015.x. · DOI
- Cheryan, S., Siy, J. O., Vichayapai, M., Drury, B. J., & Kim, S. (2011). Do female and male role models who embody STEM stereotypes hinder women's anticipated success in STEM? Social Psychological and Personality Science, 2(6), 656-664. https://doi.org/10.1177/1948550611405218. · DOI
- DeWitt, J., Archer, L., & Osborne, J. (2013). Nerdy, brainy and normal: children's and parents' constructions of those who are highly engaged with science. Research in Science Education, 43(4), 1455-1476. https://doi.org/10.1007/s11165-012-9315-0. · DOI
- Diekman, A. B., Brown, E. R., Johnston, A. M., & Clark, E. K. (2010). Seeking congruity between goals and roles: a new look at why women opt out of science, technology, engineering, and mathematics careers. Psychological Science, 21(8), 1051-1057. https://doi.org/10.1177/0956797610377342. · DOI · Paper page
- Fralick, B., Kearn, J., Thompson, S., & Lyons, J. (2009). How middle schoolers draw engineers and scientists. Journal of Science Education and Technology, 18(1), 60-73. https://doi.org/10.1007/s10956-008-9133-3. · DOI
- Franz-Odendaal, T. A., Blotnicky, K. A., & Joy, P. (2020). Math self-efficacy and the likelihood of pursuing a STEM-based career: a gender-based analysis. Canadian Journal of Science, Mathematics, and Technology Education, 20(3), 538-556. https://doi.org/10.1007/s42330-020-00105-7. · DOI
- Fung, Y. Y. H. (2002). A comparative study of primary and secondary school students' images of scientists. Research in Science & Technological Education, 20(2), 199-213. https://doi.org/10.1080/0263514022000030453. · DOI
- Garriott, P. O., Hultgren, K. M., & Frazier, J. (2016). STEM stereotypes and high school students' math/science career goals. Journal of Career Assessment, 25(4), 585-600.
- Garriott, P. O., Raque-Bogdan, T. L., Zoma, L., Mackie-Hernandez, D., & Lavin, K. (2017). Social cognitive predictors of Mexican American high school students' math/science career goals. Journal of Career Development, 44(1), 77-90. https://doi.org/10.1177/0894845316633860. · DOI
- Gottfredson, L. S. (1981). Circumscription and compromise: a developmental theory of occupational aspirations. Journal of Counseling Psychology, 28(6), 545-579. https://doi.org/10.1037/0022-0167.28.6.545. · DOI
- Hair, J. F. (2006). Multivariate data analysis. Pearson Education India.
- Hancock, A. J., Clarke, H. M., & Arnold, K. A. (2020). Sexual orientation occupational stereotypes. Journal of Vocational Behavior, 119, 103427. https:// doi.org/10.1016/j.jvb.2020.103427. · DOI
- Hazari, Z., Sonnert, G., Sadler, P. M., & Shanahan, M. C. (2010). Connecting high school physics experiences, outcome expectations, physics identity, and physics career choice: a gender study. Journal of Research in Science Teaching, 47(8), 978-1003.
- Holmegaard, H. T., Madsen, L. M., & Ulriksen, L. (2014). To choose or not to choose science: Constructions of desirable identities among young people considering a STEM higher education programme. International Journal of Science Education, 36(2), 186-215. https://doi.org/10.1080/09500693.2012.749362. · DOI
- Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. https://doi.org/10.1 080/10705519909540118. · DOI · Paper page
- Johnson, C. C. (2013). Conceptualizing integrated STEM education. School Science and Mathematics, 113(8), 367-368. https://doi.org/10.1111/ssm.12043. · DOI
- Kier, M. W., Blanchard, M. R., Osborne, J. W., & Albert, J. L. (2014). The development of the STEM career interest survey (STEM-CIS). Research in Science Education, 44(3), 461-481. https://doi.org/10.1007/s11165-013-9389-3. · DOI
- Kline, R. B. (2005). Methodology in the social sciences. London: Routledge.
- Lent, R., Brown, S., & Hackett, G. (1994). Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior, 45(1), 79-122. https://doi.org/10.1006/jvbe.1994.1027. · DOI · Paper page
- Lent, R., Miller, M., Smith, P., Watford, B., Hui, K., & Lim, R. (2015). Social cognitive model of adjustment to engineering majors: longitudinal test across gender and race/ethnicity. Journal of Vocational Behavior, 86, 77-85. https://doi.org/1 0.1016/j.jvb.2014.11.004. · DOI
- Lent, R. W., Sheu, H. B., Miller, M. J., Cusick, M. E., Penn, L. T., & Truong, N. N. (2018). Predictors of science, technology, engineering, and mathematics choice options: a meta-analytic path analysis of the social-cognitive choice model by gender and race/ethnicity. Journal of Counseling Psychology, 65(1), 17-35. https://doi.org/10.1037/cou0000243. · DOI
- Lin, C., & Deemer, E. D. (2019). Stereotype threat and career goals among women in STEM: Mediating and moderating roles of perfectionism. Journal of Career Development. https://doi.org/10.1177/0894845319884652. · DOI
- Luo, T., Li, J., & So, W. W. M. (2018). Analysis of students' visual presentations of STEM professionals. Hualien: Paper presented at 2018 International Conference of East-Asian Association for Science Education.
- Luo, T., So, W. W. M., Li, W. C., & Yao, J. (2020). The development and validation of a survey for evaluating primary students' self-efficacy in STEM activities. Journal of Science Education and Technology. https://doi.org/10.1007/s10956- 020-09882-0. · DOI · Paper page
- Masnick, A. M., Valenti, S. S., Cox, B. D., & Osman, C. J. (2010). A multidimensional scaling analysis of students' attitudes about science careers. International Journal of Science Education, 32(5), 653-667. https://doi.org/10.1080/ 09500690902759053. · DOI
- Matsumoto, D. E. (2009). The Cambridge dictionary of psychology. Cambridge: Cambridge University Press.
- Metcalf, H. (2010). Stuck in the pipeline: a critical review of STEM workforce literature. InterActions: UCLA Journal of Education and Information Studies, 6(2), 1-20.
- Milner, D. I., Horan, J. J., & Tracey, T. J. (2014). Development and evaluation of STEM interest and self-efficacy tests. Journal of Career Assessment, 22(4), 642- 653. https://doi.org/10.1177/1069072713515427. · DOI
- Nassar-McMillan, S. C., Wyer, M., Oliver-Hoyo, M., & Schneider, J. (2011). New tools for examining undergraduate students' STEM stereotypes: implications for women and other underrepresented groups. New Directions for Institutional Research, 2011(152), 87-98. https://doi.org/10.1002/ir.411. · DOI
- National Research Council (2014). STEM integration in K-12 education: Status, prospects, and an agenda for research. Washington, DC: National Academies Press.
- Navarro, R. L., Flores, L. Y., & Worthington, R. L. (2007). Mexican American middle school students' goal intentions in mathematics and science: a test of social cognitive career theory. Journal of Counseling Psychology, 54(3), 320-335. https://doi.org/10.1037/0022-0167.54.3.320. · DOI
- Nugent, G., Barker, B., Grandgenett, N., & Adamchuk, V. I. (2010). Impact of robotics and geospatial technology interventions on youth STEM learning and attitudes. Journal of Research on Technology in Education, 42(4), 391-408. https://doi.org/10.1080/15391523.2010.10782557. · DOI · Paper page
- Nugent, G., Barker, B., Welch, G., Grandgenett, N., Wu, C. R., & Nelson, C. (2015). A model of factors contributing to STEM learning and career orientation. International Journal of Science Education, 37(7), 1067-1088. https://doi.org/1 0.1080/09500693.2015.1017863. · DOI
- O'Brien, V., Martinez-Pons, M., & Kopala, M. (1999). Mathematics self-efficacy, ethnic identity, gender, and career interests related to mathematics and science. The Journal of Educational Research, 92(4), 231-235. https://doi.org/1 0.1080/00220679909597600. · DOI
- Oh, Y. J., Jia, Y., Lorentson, M., & LaBanca, F. (2013). Development of the educational and career interest scale in science, technology, and mathematics for high school students. Journal of Science Education and Technology, 22(5), 780-790. https://doi.org/10.1007/s10956-012-9430-8. · DOI
- Sadler, P. M., Sonnert, G., Hazari, Z., & Tai, R. (2012). Stability and volatility of STEM career interest in high school: a gender study. Science Education, 96(3), 411- 427. https://doi.org/10.1002/sce.21007. · DOI · Paper page
- Sahin, A., Ekmekci, A., & Waxman, H. C. (2017). Collective effects of individual, behavioral, and contextual factors on high school students' future STEM career plans. International Journal of Science and Mathematics Education, 16, 1-21. https://doi.org/10.1007/s10763-017-9847-x. · DOI
- Sasson, I., & Cohen, D. (2013). Assessment for effective intervention: enrichment science academic program. Journal of Science Education and Technology, 22(5), 718-728. https://doi.org/10.1007/s10956-012-9425-5. · DOI
- Shen, F. C., Liao, K. Y., Abraham, W. T., & Weng, C. (2014). Parental pressure and support toward Asian Americans' self-efficacy, outcome expectations, and interests in stereotypical occupations: living up to parental expectations and internalized stereotyping as mediators. Journal of Counseling Psychology, 61(2), 241-252. https://doi.org/10.1037/a0036219. · DOI
- So, W. W. M., Zhan, Y., Chow, S. C. F., & Leung, C. F. (2018). Analysis of STEM activities in primary students' science projects in an informal learning environment. International Journal of Science and Mathematics Education, 16(6), 1003-1023. https://doi.org/10.1007/s10763-017-9828-0. · DOI
- van Aalderen-Smeets, S. I., Walma van der Molen, J. H., & Xenidou-Dervou, I. (2018). Implicit STEM ability beliefs predict secondary school students' STEM self-efficacy beliefs and their intention to opt for a STEM field career. Journal of Research in Science Teaching, 56(4), 465-485.
- van Tuijl, C., & van der Molen, J. H. W. (2016). Study choice and career development in STEM fields: an overview and integration of the research. International Journal of Technology and Design Education, 26(2), 159-183. https://doi.org/10.1007/s10798-015-9308-1. · DOI
- Wang, X. (2013). Why students choose STEM majors. American Educational Research Journal, 50(5), 1081-1121. https://doi.org/10.3102/00028312134 88622. · DOI · Paper page
- Wheaton, B. (1987). Assessment of fit in overidentified models with latent variables. Sociological Methods & Research, 16(1), 118-154. https://doi.org/1 0.1177/0049124187016001005. · DOI · Paper page
- Zimmerman, B. J. (2000). Self-efficacy: an essential motive to learn. Contemporary Educational Psychology, 25(1), 82-91. https://doi.org/10.1006/ceps.1999.1016. · DOI · Paper page
Cited by
Sorted by citations
Acceptance of artificial intelligence among pre-service teachers: A multigroup analysis
Zhang, C., Schießl, J., Plößl, L., Hofmann, F., & Gläser-Zikuda, M. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00420-7 · Cited by 413 · see citing works
Hansen, M. J., Palakal, M. J., & White, L. (2024) · Journal for STEM Education Research · doi:10.1007/s41979-023-00096-8 · Cited by 138 · see citing works
- Authors
- Luo, T., So, W. W. M., Wan, Z. H., & Li, W. C.
- Affiliations
- Education University of Hong Kong (HK)
- Venue
- International Journal of STEM Education
- Published
- 2021-05-17
- Volume
- 8
- Issue
- 1
- ISSN
- 2196-7822 (ISSN-L)
- OpenAlex
- W3162063495
- Cited by
- 195
- References
- 4
- Citations by year
- 2026: 45 · 2025: 57 · 2024: 47 · 2023: 28 · 2022: 16 · 2021: 2
- FWCI
- 26.81
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- International Journal of STEM Education (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Safety Research › Career Development and Diversity
- Social Sciences › Psychology › Developmental and Educational Psychology › Science Education and Perceptions
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Education, Achievement, and Giftedness
- Keywords
- STEM career interest, STEM self-efficacy, outcome expectations, career development, upper elementary students, gender stereotypes, indirect effects, STEM education
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review