The DOI matches its Crossref record; 79 of the 79 references it cites were found in a registry or an index.
A Model of Factors Contributing to STEM Learning and Career Orientation
Abstract
The purpose of this research was to develop and test a model of factors contributing to science, technology, engineering, and mathematics (STEM) learning and career orientation, examining the complex paths and relationships among social, motivational, and instructional factors underlying these outcomes for middle school youth. Social cognitive career theory provided the foundation for the research because of its emphasis on explaining mechanisms which influence both career orientations and academic performance. Key constructs investigated were youth STEM interest, self-efficacy, and career outcome expectancy (consequences of particular actions). The study also investigated the effects of prior knowledge, use of problem-solving learning strategies, and the support and influence of informal educators, family members, and peers. A structural equation model was developed, and structural equation modeling procedures were used to test proposed relationships between these constructs. Results showed that educators, peers, and family-influenced youth STEM interest, which in turn predicted their STEM self-efficacy and career outcome expectancy. STEM career orientation was fostered by youth-expected outcomes for such careers. Results suggest that students’ pathways to STEM careers and learning can be largely explained by these constructs, and underscore the importance of youth STEM interest.
Overview
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
Verification
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.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
Self-efficacy: The exercise of control
Bandura, A., Freeman, W. H., & Lightsey, R. (1999) · Journal of Cognitive Psychotherapy · doi:10.1891/0889-8391.13.2.158 · Cited by 46,835
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941
(1998) · Cited by 36,049
Power analysis and determination of sample size for covariance structure modeling.
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996) · Psychological Methods · doi:10.1037/1082-989x.1.2.130 · Cited by 10,418
Cohen, J. (1992) · Psychological Bulletin · doi:10.1037//0033-2909.112.1.155 · Cited by 8,771
Motivational and self-regulated learning components of classroom academic performance.
Pintrich, P. R., & De Groot, E. V. (1990) · Journal of Educational Psychology · doi:10.1037/0022-0663.82.1.33 · Cited by 8,332
Toward a Unifying Social Cognitive Theory of Career and Academic Interest, Choice, and Performance.
Lent, R. W., Brown, S. D., & Hackett, G. (1994) · Journal of Vocational Behavior · doi:10.1006/jvbe.1994.1027 · Cited by 7,715
Motivational beliefs, values, and goals
Eccles, J. S., & Wigfield, A. (2002) · Annual Review of Psychology · doi:10.1146/annurev.psych.53.100901.135153 · Cited by 7,587
Analysis of Incomplete Multivariate Data
Schafer, J. L. (1997) · doi:10.1201/9781439821862 · Cited by 6,012
Cited by
Reviewing assessment of student learning in interdisciplinary STEM education
Gao, X., Li, P., Shen, J., & Sun, H. (2020) · International Journal of STEM Education · doi:10.1186/s40594-020-00225-4 · Cited by 297
STEM stereotypes predict students’ STEM career interest via self-efficacy and outcome expectations
Luo, T., So, W. W. M., Wan, Z. H., & Li, W. C. (2021) · International Journal of STEM Education · doi:10.1186/s40594-021-00295-y · Cited by 195
Han, J., Kelley, T., & Knowles, J. G. (2021) · Journal for STEM Education Research · doi:10.1007/s41979-021-00053-3 · Cited by 192
Reinhold, S., Holzberger, D., & Seidel, T. (2018) · Studies in Science Education · doi:10.1080/03057267.2018.1442900 · Cited by 86
Shwartz, G., Shav-Artza, O., & Dori, Y. J. (2021) · Journal of Science Education and Technology · doi:10.1007/s10956-021-09912-5 · Cited by 38
Metadata
- Authors
- Nugent, G., Barker, B., Welch, G., Grandgenett, N., Wu, C., & Nelson, C.
- Venue
- International Journal of Science Education
- Publisher
- Informa UK Limited
- Published
- 2015-03-09
- Volume
- 37
- Issue
- 7
- Pages
- 1067-1088
- ISSN
- 0950-0693 (ISSN-L)
- 1464-5289
- OpenAlex
- W2006583081
- Cited by
- 338
- References
- 79
- FWCI
- 35.29
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Model of Factors Contributing to STEM Learning and Career Orientation. https://app.cochat.ai/papers/10.1080/09500693.2015.1017863
- The paper
- Nugent, G., Barker, B., Welch, G., Grandgenett, N., Wu, C., & Nelson, C. (2015). A Model of Factors Contributing to STEM Learning and Career Orientation. International Journal of Science Education. https://doi.org/10.1080/09500693.2015.1017863
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.