Show simple item record

Career calculus: Assessing the psychological cost of pursuing an engineering career

dc.contributor.authorHenderson, Trevion S.
dc.contributor.authorShoemaker, Katie A.
dc.contributor.authorLattuca, Lisa R.
dc.date.accessioned2022-11-09T21:19:04Z
dc.date.available2023-11-09 16:19:02en
dc.date.available2022-11-09T21:19:04Z
dc.date.issued2022-10
dc.identifier.citationHenderson, Trevion S.; Shoemaker, Katie A.; Lattuca, Lisa R. (2022). "Career calculus: Assessing the psychological cost of pursuing an engineering career." Journal of Engineering Education 111(4): 770-791.
dc.identifier.issn1069-4730
dc.identifier.issn2168-9830
dc.identifier.urihttps://hdl.handle.net/2027.42/175106
dc.description.abstractBackgroundPersonal characteristics (e.g., race/ethnicity, gender, and precollege experiences) are known to shape students’ pathways to engineering, as well as persistence decisions in college. However, the role of psychological cost in postgraduation intentions has received less scholarly attention.PurposeThe purpose of this study is to examine sociocognitive factors that shape students’ postgraduation intentions in the early college years. Guided by Social Cognitive Career Theory and the concept of psychological cost, we examine the role of self-efficacy beliefs, outcome expectations, and psychological cost, as well as key background characteristics, in students’ postgraduation intentions.MethodWe analyzed survey responses from four cohorts of undergraduate engineering students at a large public university. Participants responded to items measuring self-efficacy beliefs, outcome expectations, and psychological cost after their first and second years of college. We used structural equation modeling to examine the relationships between the sociocognitive variables and students’ graduate school and career intentions.ResultsThe sociocognitive variables predicting postgraduation intentions after Year 1 differed from those predicting intentions after Year 2. After Year 1, we found no statistically significant sociocognitive variables predicting graduate school intentions or engineering career plans. After Year 2, both self-efficacy and outcome expectations were significant predictors of postgraduation intentions. The psychological cost was significantly related to both self-efficacy and outcome expectations. Finally, we found significant differences in racial/ethnic identity, sex, and first-generation status.ConclusionExamining psychological cost provides additional insights into the factors informing students’ postgraduation intentions over the course of their collegiate careers and suggests new directions for research on students’ thinking about engineering careers.
dc.publisherJohn Wiley & Sons, Inc.
dc.subject.otherundergraduate education
dc.subject.othersocial cognitive career theory
dc.subject.othercareer paths
dc.subject.otherpsychological cost
dc.subject.otherstructural equation modeling
dc.titleCareer calculus: Assessing the psychological cost of pursuing an engineering career
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelEngineering Education
dc.subject.hlbtoplevelEngineering
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/175106/1/jee20474.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/175106/2/jee20474_am.pdf
dc.identifier.doi10.1002/jee.20474
dc.identifier.sourceJournal of Engineering Education
dc.identifier.citedreferencePerez, T., Wormington, S. V., Barger, M. M., Schwartz-Bloom, R. S., Lee, Y., & Linnenbrink-Garcia, L. ( 2019 ). Science expectancy, value, and cost profiles and their proximal and distal relations to undergraduate science, technology, engineering, and math persistence. Science Education, 103 ( 2 ), 264 – 286. https://doi.org/10.1002/sce.21490
dc.identifier.citedreferenceNational Academy of Engineering. ( 2018 ). Understanding the educational and career pathways of engineers. The National Academies Press. https://doi.org/10.17226/25284
dc.identifier.citedreferenceNational Academy of Sciences, National Academy of Engineering, & Institute of Medicine. ( 2007 ). Rising above the gathering storm: Energizing and employing American for a brighter economic future. The National Academies Press. https://doi.org/10.17226/11463
dc.identifier.citedreferencePerez, T., Cromley, J. G., & Kaplan, A. ( 2014 ). The role of identity development, values, and costs in college STEM retention. Journal of Educational Psychology, 106 ( 1 ), 315 – 329. https://doi.org/10.1037/a0034027
dc.identifier.citedreferencePresident’s Council of Advisors on Science and Technology. ( 2012 ). Report to the President: Engage to excel: Producing one million additional college graduate with degrees in science, technology, engineering, and mathematics. Retrieved from: https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/pcast-engage-to-excel-final_2-25-12.pdf
dc.identifier.citedreferenceRo, H. K. ( 2011 ). An investigation of engineering students’ post-graduation plans inside or outside of engineering (Dissertation/thesis). ProQuest Dissertations Publishing.
dc.identifier.citedreferenceRo, H. K., Lattuca, L. R., & Alcott, B. ( 2017 ). Who goes to graduate school? Engineers’ math proficiency, college experience, and self-assessment of skills. Journal of Engineering Education, 106 ( 1 ), 98 – 122. https://doi.org/10.1002/jee.20154
dc.identifier.citedreferenceRobinson, K. A., Lee, Y. K., Bovee, E. A., Perez, T., Walton, S. P., Briedis, D., & Linnenbrink-Garcia, L. ( 2019 ). Motivation in transition: Development and roles of expectancy, task values, and costs in early college engineering. Journal of Educational Psychology, 111 ( 6 ), 1081 – 1102. https://doi.org/10.1037/edu0000331
dc.identifier.citedreferenceRodriguez, A., Furquim, F., & DesJardins, S. L. ( 2018 ). Categorical and limited dependent variable modeling in higher education. In M. B. Paulsen (Ed.), Higher education: Handbook of theory and research (pp. 295 – 370 ). Springer. https://doi.org/10.1007/978-3-319-72490-4_7
dc.identifier.citedreferenceRosenzweig, E. Q., Wigfield, A., & Hulleman, C. S. ( 2020 ). More useful or not so bad? Examining the effects of utility value and cost reduction interventions in college physics. Journal of Educational Psychology, 112 ( 1 ), 166 – 182. https://doi.org/10.1037/edu0000370
dc.identifier.citedreferenceSax, L. J., Kanny, M. A., Riggers-Piehl, T. A., Whang, H., & Paluson, L. N. ( 2015 ). “ But I’m not good at math”: The changing salience of mathematical self-concept in shaping women’s and men’s STEM aspirations. Research in Higher Education, 56 ( 8 ), 813 – 842. https://doi.org/10.1007/s11162-015-9375-x
dc.identifier.citedreferenceSchar, M., Gilmartin, S. K., Rieken, B., Brunhaver, S. R., Chen, H. L., & Sheppard, S. ( 2017 ). The making of an innovative engineer: Academic and life experiences that shape engineering task and innovation self-efficacy. Paper presented at the ASEE Annual Conference and Exposition, Columbus, OH. https://doi.org/10.18260/1-2--28986
dc.identifier.citedreferenceSensoy, O., & DiAngelo, R. ( 2012 ). Is everyone really equal? An introduction to key concepts in social justice education. Teachers College.
dc.identifier.citedreferenceSeron, C., Silbey, S. S., Cech, E., & Rubineau, B. ( 2016 ). Persistence is cultural: Professional socialization and the reproduction of sex segregation. Work & Occupations, 43 ( 2 ), 178 – 214. https://doi.org/10.1177/0730888415618728
dc.identifier.citedreferenceSeymour, E., & Hewitt, N. M. ( 1997 ). Talking about leaving: Why undergraduates leave the sciences. Westview Press, Boulder. https://doi.org/10.2307/2655673
dc.identifier.citedreferenceSimmons, D. R., Ye, Y., Ohland, M. W., & Garahan, K. ( 2018 ). Understanding students’ incentives for and barriers to our-of-class participation: Profile of civil engineering student engagement. Journal of Professional Issues in Engineering Education and Practice, 144 ( 2 ), 04017015-1 – 04017015-13. https://doi.org/10.1061/(asce)ei.1943-5541.0000353
dc.identifier.citedreferenceSmith, J. L., Cech, E., Metz, A., Huntoon, M., & Moyer, C. ( 2014 ). Giving back or giving up: Native American student experiences in science and engineering. Cultural Diversity & Ethnic Minority Psychology, 20 ( 3 ), 413 – 429. https://doi.org/10.1037/a0036945
dc.identifier.citedreferenceSmith, K. N., & Gayles, J. G. ( 2017 ). “ Setting up for the next big thing”: Undergraduate women engineering students’ postbaccalaureate career decisions. Journal of College Student Development, 58 ( 8 ), 1201 – 1217. https://doi.org/10.1353/csd.2017.0094
dc.identifier.citedreferenceStewart, D. L., & Nicolazzo, Z. ( 2018 ). High impact of [whiteness] on trans* students in postsecondary education. Equity & Excellence in Education, 51 ( 2 ), 132 – 145. https://doi.org/10.1080/10665684.2018.1496046
dc.identifier.citedreferenceStrenta, A. C., Elliott, R., Adair, R., Matier, M., & Scott, J. ( 1994 ). Choosing and leaving science in highly selective institutions. Research in Higher Education, 35 ( 5 ), 513 – 547. https://doi.org/10.1007/bf02497086
dc.identifier.citedreferenceThoman, D. B., Brown, E. R., Mason, A. Z., Harmsen, A. G., & Smith, J. L. ( 2015 ). The role of altruistic values in motivating underrepresented minority students for biomedicine. Bioscience, 65 ( 2 ), 183 – 188. https://doi.org/10.1093/biosci/biu199
dc.identifier.citedreferenceTonso, K. L. ( 2006 ). Student engineers and engineer identity: Campus engineer identities as figured world. Cultural Studies of Science Education, 1 ( 2 ), 273 – 307. https://doi.org/10.1007/s11422-005-9009-2
dc.identifier.citedreferenceWatt, H. M. G., Shapka, J. D., Morris, Z. A., Durik, A. M., Keating, D. P., & Eccles, J. S. ( 2012 ). Gendered motivational processes affecting high school mathematics participation, educational aspirations, and career plans: A comparison of samples from Australia, Canada, and the United States. Developmental Psychology, 48 ( 6 ), 1594 – 1611. https://doi.org/10.1037/a0027838
dc.identifier.citedreferenceAbele, A. E., & Spurk, D. ( 2011 ). The dual impact of gender and the influence of timing of parenthood on men’s and women’s career development: Longitudinal findings. International Journal of Behavioral Development, 35 ( 3 ), 225 – 232. https://doi.org/10.1177/0165025411398181
dc.identifier.citedreferenceAlexander, Q. R., & Hermann, M. A. ( 2016 ). African-American women’s experiences in graduate science, technology, engineering, and mathematics education at a predominantly white university: A qualitative investigations. Journal of Diversity in Higher Education, 9 ( 4 ), 307 – 322. https://doi.org/10.1037/a0039705
dc.identifier.citedreferenceAtman, C., Sheppard, S., Fleming, L., Miller, R., Smith, K., Stevens, R., Streveler, R., Loucks-Jaret, C., & Lund, D. ( 2008 ). Moving from pipeline thinking to understanding pathways: Findings from the academic pathways study of engineering undergraduates. Paper presented at the ASEE Annual Conference and Exposition, Pittsburgh, PA. https://doi.org/10.18260/1-2--3786
dc.identifier.citedreferenceBandura, A. ( 1986 ). Social foundations of thought and action: A social cognitive theory. Prentice Hall. https://doi.org/10.5465/amr.1987.4306538
dc.identifier.citedreferenceBarron, K. E., & Hulleman, C. S. ( 2015 ). Expectancy-value-cost model of motivation. In J. D. Wright (Ed.), International encyclopedia of the social & behavioral sciences (2nd ed., pp. 503–509). Oxford: Elsevier Ltd. https://doi.org/10.1016/B978-0-08-097086-8.26099-6
dc.identifier.citedreferenceBattle, A., & Wigfield, A. ( 2003 ). College women’s value orientations toward family, career, and graduate school. Journal of Vocational Behavior, 62 ( 1 ), 56 – 75. https://doi.org/10.1016/s0001-8791(02)00037-4
dc.identifier.citedreferenceBong, M., & Skaalvik, E. M. ( 2003 ). Academic self-concept and self-efficacy: How different are they really? Educational Psychology Review, 15 ( 1 ), 1 – 40. https://doi.org/10.1023/a:1021302408382
dc.identifier.citedreferenceBorrego, M., Knight, D. B., Gibbs, K., Jr., & Crede, E. ( 2018 ). Pursuing graduate study: Factors underlying undergraduate engineering students’ decisions. Journal of Engineering Education, 107 ( 1 ), 140 – 163. https://doi.org/10.1002/jee.20185
dc.identifier.citedreferenceByars-Winston, A., Estrada, Y., Howard, C., Davis, D., & Zalapa, J. ( 2010 ). Influence of social cognitive and ethnic variables on academic goals of underrepresented students in science and engineering. Journal of Counseling Psychology, 57 ( 2 ), 205 – 218. https://doi.org/10.1037/a0018608
dc.identifier.citedreferenceByars-Winston, A., & Rogers, J. G. ( 2019 ). Testing intersectionality of race/ethnicity × gender in a social–cognitive career theory model with science identity. Journal of Counseling Psychology, 66 ( 1 ), 30 – 44. https://doi.org/10.1037/cou0000309
dc.identifier.citedreferenceChen, X. ( 2013 ). STEM attrition: College students’ paths into and out of STEM fields. National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. https://doi.org/10.3926/jotse.136
dc.identifier.citedreferenceCheryan, S., Ziegler, S., Montoya, A., & Jiang, L. ( 2017 ). Why are some STEM fields more gender balanced than others? Psychological Bulletin, 143 ( 1 ), 1 – 35. https://doi.org/10.1037/bul0000052
dc.identifier.citedreferenceChow, A., Eccles, J. S., & Salmela-Aro, K. ( 2012 ). Task value profiles across subjects and aspirations to physical and IT-related sciences in the United States and Finland. Developmental Psychology, 48 ( 6 ), 1612 – 1628. https://doi.org/10.1037/a0030194
dc.identifier.citedreferenceConcannon, J. P., & Barrow, L. H. ( 2009 ). A cross-sectional study of engineering students’ self-efficacy by gender, ethnicity, year, and transfer status. Journal of Science Education and Technology, 18 ( 2 ), 163 – 172. https://doi.org/10.1007/s10956-008-9141-3
dc.identifier.citedreferenceDewsbury, B. M., Taylor, C., Reid, A., & Viamonte, C. ( 2019 ). Career choice among first-generation, minority STEM college students. Journal of Microbiology & Biology Education, 20 ( 3 ), 1 – 7. https://doi.org/10.1128/jmbe.v20i3.1775
dc.identifier.citedreferenceEagan, M. K., Hurtado, S., Chang, M. J., Garcia, G. A., Herrera, F. A., & Garibay, J. C. ( 2013 ). Making a difference in science education: The impact of undergraduate research programs. American Educational Research Journal, 50 ( 4 ), 683 – 713. https://doi.org/10.3102/0002831213482038
dc.identifier.citedreferenceEccles, J. S. ( 1983 ). Expectancies, values, and academic behavior. In J. T. Spence (Ed.), Achievement and achievement motivation (pp. 75 – 146 ). Freeman.
dc.identifier.citedreferenceEccles, J. S. ( 2011 ). Understanding women’s achievement choices: Looking back and looking forward. Psychology of Women Quarterly, 35 ( 3 ), 510 – 516. https://doi.org/10.1177/0361684311414829
dc.identifier.citedreferenceFlake, J. K., Barron, K. E., Hulleman, C., McCoach, B. D., & Welsh, M. E. ( 2015 ). Measuring cost: The forgotten component of expectancy-value theory. Contemporary Educational Psychology, 41, 232 – 244. https://doi.org/10.1016/j.cedpsych.2015.03.002
dc.identifier.citedreferenceGodfrey, E. ( 2014 ). Understanding disciplinary cultures: The first step to cultural change. In A. Johri & B. M. Olds (Eds.), Cambridge handbook of engineering education research (pp. 437 – 455 ). Cambridge University Press. https://doi.org/10.1017/cbo9781139013451.028
dc.identifier.citedreferenceGodwin, A., Potvin, G., Hazari, Z., & Lock, H. ( 2016 ). Identity, critical agency, and engineering: An affective model for predicting engineering as a career choice. Journal of Engineering Education, 105 ( 2 ), 312 – 340. https://doi.org/10.1002/jee.20118
dc.identifier.citedreferenceGreenman, S. J., Chepp, V., & Burton, S. ( 2022 ). High-impact educational practices: Leveling the playing field or perpetuating inequity? Teaching in Higher Education, 27 ( 2 ), 267 – 279. https://doi.org/10.1080/13562517.2021.2000384
dc.identifier.citedreferenceHenderson, T. S., Shoemaker, K. A., & Lattuca, L. R. ( 2019 ). Investigating engineering students’ career thinking after year 1 and year 2 in college. Paper presented at the American Educational Research Association Annual Meeting, Toronto, ON, Canada.
dc.identifier.citedreferenceHolland, J. L. ( 1997 ). Making vocational choices: A theory of vocational personalities and work environments ( 3rd ed. ). Psychological Assessment Resources.
dc.identifier.citedreferenceHu, L., & Bentler, P. M. ( 1999 ). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6 ( 1 ), 1 – 55. https://doi.org/10.1080/10705519909540118
dc.identifier.citedreferenceHurtado, S., Newman, C. B., Tran, M. C., & Chang, M. J. ( 2010 ). Improving the rate of success for underrepresented racial minorities in STEM fields: Insights from a national project. New Directions for Institutional Research, 2010 ( 148 ), 5 – 15. https://doi.org/10.1002/ir.357
dc.identifier.citedreferenceJones, B. D. ( 2009 ). Motivating students to engage in learning: The MUSIC model of academic motivation. International Journal of Teaching and Learning in Higher Education, 21 ( 2 ), 272 – 285.
dc.identifier.citedreferenceJones, B. D., Osborne, J. W., Paretti, M. C., & Matusovich, H. M. ( 2014 ). Relationships among students’ perceptions of a first-year engineering design course and their engineering identification, motivational beliefs, course effort, and academic outcomes. International Journal of Engineering Education, 30 ( 6 ), 1340 – 1356.
dc.identifier.citedreferenceJones, B. D., Paretti, M. C., Hein, S. F., & Knott, T. W. ( 2010 ). An analysis of motivation constructs with first-year engineering students: Relationships among expectancies, values, achievement, and career plans. Journal of Engineering Education, 99 ( 4 ), 319 – 336. https://doi.org/10.1002/j.2168-9830.2010.tb01066.x
dc.identifier.citedreferenceJones, B. D., Tendhar, C., & Paretti, M. C. ( 2016 ). The effect of students course perception on their domain identification, motivational beliefs, and goals. Journal of Career Development, 43 ( 5 ), 383 – 397. https://doi.org/10.1177/0894845315603821
dc.identifier.citedreferenceKline, R. B. ( 2016 ). Principles and practice of structural equation modeling ( 4th ed. ). The Guilford Press.
dc.identifier.citedreferenceLent, R. W. ( 2012 ). Social cognitive career theory. In S. D. Brown & R. W. Lent (Eds.), Career development and counseling: Putting theory and research to work (pp. 115 – 146 ). Wiley.
dc.identifier.citedreferenceLent, R. W., & Brown, S. D. ( 2019 ). Social cognitive career theory at 25: Empirical status of interest, choice, and performance models. Journal of Vocational Behavior, 115, 1 – 14.
dc.identifier.citedreferenceLent, R. W., Brown, S. D., & 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
dc.identifier.citedreferenceLent, R. W., Miller, M. J., Smith, P. E., Watford, B. A., Lim, R. H., & Hui, K. ( 2016 ). Social cognitive predictors of academic persistence and performance in engineering: Applicability across gender and race/ethnicity. Journal of Vocational Behavior, 94, 79 – 88. https://doi.org/10.1016/j.jvb.2016.02.012
dc.identifier.citedreferenceLent, R. W., Sheu, H., Singley, D., Schmidt, J. A., Schmidt, L. C., & Gloster, C. S. ( 2008 ). Longitudinal relations of self-efficacy to outcome expectations, interests, and major choice goals in engineering students. Journal of Vocational Behavior, 73, 328 – 335. https://doi.org/10.1016/j.jvb.2008.07.005
dc.identifier.citedreferenceLent, 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
dc.identifier.citedreferenceLichtenstein, G., Loshbaugh, H. G., Claar, B., Chen, H. L., Jackson, K., & Sheppard, S. D. ( 2009 ). An engineering major does not an engineer make: Career decision making among undergraduate engineers. Journal of Engineering Education, 98 ( 3 ), 227 – 234. https://doi.org/10.1002/j.2168-9830.2009.tb01021.x
dc.identifier.citedreferenceMargolis, J., & Kotys-Schwartz, D. ( 2009 ). The post-graduation attrition of engineering students: An exploratory study on influential career choice factors. Paper presented at the ASME International Mechanical Engineering Congress and Exposition, La Buena Vista, FL. https://doi.org/10.1115/imece2009-10906
dc.identifier.citedreferenceMarra, R. M., & Bogue, B. ( 2006 ). Women engineering students’ self-efficacy—A longitudinal multi-institution study. Women in Engineering ProActive Network.
dc.identifier.citedreferenceMcGee, E. O. ( 2013 ). High-achieving Black students, biculturalism, and out-of-school STEM learning experiences: Exploring some unintended consequences. Journal of Urban Mathematics Education, 6 ( 2 ), 20 – 41.
dc.identifier.citedreferenceMcGee, E. O. ( 2016 ). Devalued black and Latino racial identities: A by-product of STEM college culture? American Educational Research Journal, 53 ( 6 ), 1626 – 1662. https://doi.org/10.3102/0002831216676572
dc.identifier.citedreferenceMcGee, E. O., & Bentley, L. ( 2017 ). The troubled success of Black women in STEM. Cognition and Instruction, 35 ( 4 ), 265 – 289. https://doi.org/10.1080/07370008.2017.1355211
dc.identifier.citedreferenceMosyjowski, E., Beverly, S., & Lattuca L. R. ( 2019 ). Negotiating social identities in time and place: Connections to undergraduates’ career thinking. Paper Presented at the Annual Meeting of the Association for the Study of Higher Education, Portland, OR.
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.