The DOI matches its Crossref record.
Outcomes of a Longitudinal Administration of the Persistence in Engineering Survey
Abstract
B ackground Understanding more about student decisions to leave engineering may lead to higher retention. This study builds on the literature and focuses on the experiences of a cohort of students who aimed to complete their undergraduate work in 2007. P urpose (H ypothesis) This paper presents the outcomes of the longitudinal administration of the Persistence in Engineering survey. The goal was to identify correlates of persistence in undergraduate engineering education and professional engineering practice. D esign/M ethod The survey was administered seven times over four years to a cohort of students who had expressed interest in studying engineering. At the end of the study, the participants were categorized as persisters or non‐persisters. Repeated measures analysis of variance was used, in conjunction with other approaches, to test for differences between the groups. R esults Persisters and non‐persisters did not differ significantly according to the majority of the constructs. Nevertheless, parental and high school mentor influences as a motivation to study engineering, as well as confidence in math and science skills, were identified as correlates of persistence. Intention to complete an engineering major was also a correlate of persistence; it appears to decline sharply at least two semesters prior to students leaving engineering. The findings also suggest that there might be differences among non‐persisters when they are further grouped by when they leave engineering. C onclusions Facilitating higher levels of mentor involvement before college might increase student motivation to study engineering, and also constitute a mechanism for fostering confidence in math and science skills. Since the intention to complete an engineering degree decreases well before students act, there may be opportunities for institutions to develop targeted interventions for students, and help them make informed decisions.
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
Cited by
Leaving Engineering: A Multi‐Year Single Institution Study
Marra, R. M., Rodgers, K. A., Shen, D., & Bogue, B. (2012) · Journal of Engineering Education · doi:10.1002/j.2168-9830.2012.tb00039.x · Cited by 538
Measuring Undergraduate Students' Engineering Self‐Efficacy: A Validation Study
Mamaril, N. A., Usher, E. L., Li, C. R., Economy, D. R., & Kennedy, M. S. (2016) · Journal of Engineering Education · doi:10.1002/jee.20121 · Cited by 302
Meyer, M., & Marx, S. (2014) · Journal of Engineering Education · doi:10.1002/jee.20054 · Cited by 268
Computing Education Research Today
Fincher, S. A., Tenenberg, J., Dorn, B., Hundhausen, C., McCartney, R., & Murphy, L. (2019) · The Cambridge Handbook of Computing Education Research · doi:10.1017/9781108654555.003 · Cited by 7
Velázquez, J. S., Cavas, F., Fuentes, M. C., & García-Ros, R. (2023) · Education Sciences · doi:10.3390/educsci13070756 · Cited by 6
Metadata
- Authors
- Eris, O., Chachra, D., Chen, H. L., Sheppard, S., Ludlow, L., Rosca, C., Bailey, T., & Toye, G.
- Venue
- Journal of Engineering Education
- Publisher
- Wiley
- Published
- 2010-10
- Volume
- 99
- Issue
- 4
- Pages
- 371-395
- ISSN
- 1069-4730 (ISSN-L)
- 2168-9830
- OpenAlex
- W1998326408
- Cited by
- 188
- References
- 0
- FWCI
- 28.29
- 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: Outcomes of a Longitudinal Administration of the Persistence in Engineering Survey. https://app.cochat.ai/papers/10.1002/j.2168-9830.2010.tb01069.x
- The paper
- Eris, O., Chachra, D., Chen, H. L., Sheppard, S., Ludlow, L., Rosca, C., Bailey, T., & Toye, G. (2010). Outcomes of a Longitudinal Administration of the Persistence in Engineering Survey. Journal of Engineering Education. https://doi.org/10.1002/j.2168-9830.2010.tb01069.x
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.