Archives
Current issue
About
About us
Aims and Scope
Abstracting and Indexing
Editorial Office
Open Access Policy
Publication Ethics
Journal History
Publisher
Follow us: Twitter
Contact
For Authors
Editorial Policy
Peer Review Policy
Manuscript Preparation Guidelines
Copyright & Licencing
Publication Fees
Fee Waiver Policy for Doctoral Students
EJMSTE Language Editing Service
More
Statistics
Special Issues
Special Issue Announcements
Published Special Issues
RESEARCH PAPER
The Relationship of STEM Attitudes and Career Interest
1
Department of STEM Education, NC State University, Raleigh, NC, USA
2
Department of Mathematics and Statistics, California State University, Monterey Bay, CA, USA
3
Friday Institute for Educational Innovation, NC State University, Raleigh, NC, USA
Publication date: 2018-06-14
EURASIA J. Math., Sci Tech. Ed 2018;14(10):em1580
KEYWORDS
ABSTRACT
This study examines the relationships between attitudes toward all core STEM subjects and interest in STEM careers among 4th through 12th grade US students through the administration of the Student Attitudes toward STEM (S-STEM) Survey to over 15,000 public school students. The research developed a model based on expectancy-value theory that incorporates key demographic factors of age, gender, and race/ethnicity. Our findings reinforce prior research that students across key demographic factors perceive biological/clinical and physical science career paths differently, resulting in two career clusters. Of interest, the relationship of mathematics attitudes to career interest varied by STEM career cluster. Findings were also supportive of the conclusion that students’ attitudes towards STEM careers are not static over their primary and secondary grades, stabilizing and leveling during their secondary years. Gender showed significantly different interest levels for the two career clusters: males higher for physical sciences and females higher for biological/clinical sciences. Racial/ethnic disparity in STEM career interests can be seen more readily in physical sciences and engineering than in the biological sciences. Overall, our work reinforces findings that students, as young as elementary grades, are forming attitudinal associations between their academic and life experience and future STEM careers.
REFERENCES (75)
1.
ACT. (2009). Act Interest Inventory Technical Manual. Retrieved from Iowa City, IA: http://www.act.org/stemconditi....
3.
Andersen, L., & Ward, T. J. (2013). Expectancy-Value Models for the STEM Persistence Plans of Ninth-Grade, High-Ability Students: A Comparison between Black, Hispanic, and White Students. Science Education, 98(2), 216-242. https://doi.org/10.1002/sce.21....
4.
Andre, T., Whigham, M., Hendrickson, A., & Chambers, S. (1999). Competency beliefs, positive affect, and gender stereotypes of elementary students and their parents about science versus other school subjects. Journal of Research in Science Teaching, 36(6), 719-747. https://doi.org/10.1002/(SICI)...<719::AID-TEA8>3.0.CO;2-R.
5.
Beal, S. J., & Crockett, L. J. (2010). Adolescents’ occupational and educational aspirations and expectations: Links to high school activities and adult educational attainment. Developmental Psychology, 46(1), 258-265. https://doi.org/10.1037/a00174....
6.
Beede, D., Julian, T., Khan, B., Lehrman, R., McKittrick, G., Langdon, D., & Doms, M. (2011). Education Supports Racial and Ethnic Equality in STEM. ESA Issue Brief# 05-11 (05‐11).
7.
Brotman, J. S., & Moore, F. M. (2008). Girls and science: A review of four themes in the science education literature. Journal of Research in Science Teaching, 45(9), 971-1002. https://doi.org/10.1002/tea.20....
8.
Byars-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: a multiple-groups analysis. Journal of Counseling Psychology, 57(2), 205. https://doi.org/10.1037/a00186....
9.
Caleon, I. S., & Subramaniam, R. (2008). Attitudes towards science of intellectually gifted and mainstream upper primary students in Singapore. Journal of Research in Science Teaching, 45(8), 940-954.
10.
Chen, P., & Zimmerman, B. (2007). A Cross-National Comparison Study on the Accuracy of Self-Efficacy Beliefs of Middle-School Mathematics Students. The Journal of Experimental Education, 75(3), 221 - 244.
11.
Chen, X. (2009). Students Who Study Science, Technology, Engineering, and Mathematics (STEM) in Postsecondary Education. Retrieved from http://nces.ed.gov/pubs2009/20....
12.
Cisco Systems. (2008). Equipping every learner for the 21st century. White paper. San Jose, CA: Author.
13.
Correl, S. (2001). Gender and the career choice process: The role of biased self-assessments. American Journal of Sociology, 106(6), 1691-1730.
14.
Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum.
15.
DeWitt, J., Archer, L., & Osborne, J. (2014). Science-related Aspirations across the Primary–Secondary Divide: Evidence from two surveys in England. International Journal of Science Education, 36(10), 1609-1629. https://doi.org/10.1080/095006....
16.
DeWitt, J., Osborne, J., Archer, L., Dillon, J., Willis, B., & Wong, B. (2011). Young children’s aspiration in science: The unequivocal, the uncertain and the unthinkable. International Journal of Science Education, 35(6), 1037–1063. https://doi.org/10.1080/095006....
17.
Douglas, K., Rynearson, A., Yoon, S., & Diefes-Dux, H. (2015). Two elementary schools’ developing potential for sustainability of engineering education. International Journal of Technology and Design Education, 1-26. https://doi.org/10.1007/s10798....
18.
Drechsel, B., Carstensen, C., & Prenzel, M. (2011). The Role of Content and Context in PISA Interest Scales: A study of the embedded interest items in the PISA 2006 science assessment. International Journal of Science Education, 33(1), 73-95. https://doi.org/10.1080/095006....
19.
Eccles, J. S. (1994). Understanding Women’s Educational and Occupational Choices: Applying the Eccles et al. Model of Achievement-Related Choices. Psychology of Women Quarterly, 18(4), 585-609. https://doi.org/10.1111/j.1471....
20.
Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53, 109-132.
21.
Eccles, J. S., Vida, M. N., & Barber, B. (2004). The relation of early adolescents’ college plans and both academic ability and task-value beliefs to subsequent college enrollment. The Journal of Early Adolescence, 24(1), 63-77.
22.
Fouad, N. A., & Smith, P. L. (1996). A test of a social cognitive model for middle school students: Math and science. Journal of Counseling Psychology, 43(3), 338-346. https://doi.org/10.1037/0022-0....
23.
Ginder, S., & Mason, M. (2011). Postsecondary Awards in Science, Technology, Engineering, and Mathematics (STEM), by State: 2001 and 2009 (Report # NCES 2011-226). Retrieved from http://nces.ed.gov/pubs2011/20....
24.
Greenfield, T. A. (1997). Gender- and grade-level differences in science interest and participation. Science Education, 81(3), 259-276. https://doi.org/10.1002/(SICI)...<259::AID-SCE1>3.0.CO;2-C.
25.
Guo, J., Marsh, H. W., Morin, A. J. S., Parker, P. D., & Kaur, G. (2015). Directionality of the Associations of High School Expectancy-Value, Aspirations, and Attainment: A Longitudinal Study. American Educational Research Journal. https://doi.org/10.3102/000283....
26.
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. https://doi.org/10.1002/tea.20....
27.
ITEEA, International Technology and Engineering Educators Association. (2018). Homepage. Retrieved from http://www.iteea.org.
28.
Jaccard, J., & Turrisi, R. (Eds.). (2003). Interaction Effects in Multiple Regression (2nd ed.). Thousand Oaks, CA: SAGE Publications, Inc. https://doi.org/10.4135/978141....
29.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning. New York: Springer.
30.
Jenkins, E. W., & Nelson, N. W. (2005). Important but not for me: students’ attitudes towards secondary school science in England. Research in Science & Technological Education, 23(1), 41-57. https://doi.org/10.1080/026351....
31.
Katehi, L., Pearson, G., & Feder, M. (2009). Engineering in K-12 Education: Understanding the Status and Improving the Prospects (ISBN 978-0-309-13778-2). Retrieved from http://www.nap.edu/catalog.php....
32.
Maltese, A. V., & Tai, R. H. (2011). Pipeline persistence: Examining the association of educational experiences with earned degrees in STEM among U.S. students. Science Education, 95(5), 877-907. https://doi.org/10.1002/sce.20....
33.
Mau, W.-C. (2003). Factors That Influence Persistence in Science and Engineering Career Aspirations. Career Development Quarterly, 51(3), 234-243.
34.
Miller, C. C. (2014). Google Releases Employee Data, Illustrating Tech’s Diversity Challenge, New York Times. Retrieved from http://nyti.ms/1heUoxU5/14.
35.
Miller, P. H., Slawinski Blessing, J., & Schwartz, S. (2006). Gender differences in high school students’ views about science. International Journal of Science Education, 28(4), 363-381.
36.
NAE, National Academy of Engineering. (2014). STEM Integration in K-12 Education: Status, Prospects, and an Agenda for Research. Washington, DC: National Academies Press.
37.
NAEP, National Assessment of Educational Progress. (2014). Technology and Engineering Literacy Student Questionnaire (TELSQ) 2014 Grade 8 Computer-based Assessment. Washington, DC: NAEP.
38.
Nathan, M., Oliver, K., Prevost, A., Tran, N., & Phelps, A. (2009). Classroom Learning and Instruction in High School Pre-College Engineering Settings: A Video-Based Analysis. Paper presented at the American Society for Engineering Education, Austin, TX.
39.
NCDPI, North Carolina Department of Public Instruction. (2009). North Carolina Public Schools Statistical Profile. Raleigh, NC.
40.
NCSES, National Center for Science and Engineering Statistics. (2013). Science and Engineering Degrees: 1966 – 2010 (13-327). Retrieved from http://www.nsf.gov/statistics/....
41.
NGSS Lead States. (2013). Next Generation Science Standards. Washington, DC: The National Academies Press.
42.
NRC, National Research Council. (2010). Rising above the gathering storm, revisited: Rapidly rising to category 5. Washington, DC: Author.
43.
NSF, National Science Foundation. (2009). Women, minorities, and persons with disabilities in science and engineering: 2009 (NSF 09 – 305). Arlington, VA: Author.
44.
OECD, Organisation for Economic Co-operation and Development. (2006). PISA assessing scientific, reading and mathematical literacy: A framework for PISA 2006. Paris: Author.
45.
Osborne, J., Simon, S., & Collins, S. (2003). Attitudes towards science: A review of the literature and its implications. International Journal of Science Education, 25(9), 1049-1079.
46.
Pajares, F., & Graham, L. (1999). Self-Efficacy, Motivation Constructs, and Mathematics Performance of Entering Middle School Students. Contemporary Educational Psychology, 24(2), 124-139. https://doi.org/10.1006/ceps.1....
47.
PCAST, President’s Council of Advisors on Science and Technology. (2010). Prepare and Inspire: K-12 Education in Science, Technology, Engineering, and Math (STEM) for America’s Future. Washington, DC: Executive Office of the President.
48.
PCAST, President’s Council of Advisors on Science and Technology. (2012). Engage to excel: Producing one million additional college graduates with degrees in science, technology, engineering and mathematics. Washington, DC: Executive Office of the President.
49.
PTCS, Partnership for 21st Century Skills. (2005). Learning for the 21st Century. Retrieved from http://www.21stcenturyskills.o....
50.
Riegle-Crumb, C., & King, B. (2010). Questioning a White Male Advantage in STEM Examining Disparities in College Major by Gender and Race/Ethnicity. Educational Researcher, 39(9), 656-664. https://doi.org/10.3102/001318....
51.
Rothwell, J. (2013). The Hidden STEM Economy. The Metropolitan Policy Program at Brookings: Washington, DC.
52.
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.21....
54.
Schunk, D. H. (1991). Self-Efficacy and Academic Motivation. Educational Psychologist, 26, 207-232.
55.
Schwarz, G. (1978). Estimating the Dimension of a Model. The Annals of Statistics, 6(2), 461–464.
56.
Scott, A. B., & Mallinckrodt, B. (2005). Parental Emotional Support, Science Self-Efficacy, and Choice of Science Major in Undergraduate Women. Career Development Quarterly, 53(3), 263-273.
57.
Simon, R. A., Aulls, M. W., Dedic, H., Hubbard, K., & Hall, N. C. (2014). Exploring Student Persistence in STEM Programs: A Motivational Model. Canadian Journal of Education, 38(1), 1-27.
58.
Simpkins, S. D., Davis-Kean, P. E., & Eccles, J. S. (2006). Math and science motivation: A longitudinal examination of the links between choices and beliefs. Developmental Psychology, 42(1), 70.
59.
Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Allyn and Bacon. https://doi.org/10.1037/022267.
60.
Tai, R. H., Qi Liu, C., Maltese, A. V., & Fan, X. (2006). Planning Early for Careers in Science. Science, 312(5777), 1143-1144. https://doi.org/10.1126/scienc....
61.
Truxillo, C. (2005). Maximum Likelihood Parameter Estimation with Incomplete Data. In Proceedings of the Thirtieth Annual SAS® Users Group International Conference (paper 111–30). Cary, NC: SAS Institute Inc.
62.
U.S. Bureau of Labor Statistics (2011). Occupational Outlook Handbook. Retrieved on May, 2017 from https://www.bls.gov/ooh/.
63.
Unfried, A., Faber, M., & Wiebe, E. (2014). Gender and Student Attitudes toward STEM. Presented at the AERA Annual Meeting, Philadelphia, PA.
64.
Unfried, A., Faber, M., Stanhope, D. & Wiebe, E. (2015). The development and validation of a measure of student attitudes toward science, technology, mathematics, and engineering. Journal of Psychoeducational Assessment 33(7), 622-639. https://doi.org/10.1177/073428....
65.
USCB, U.S. Census Bureau. (2016). ACS Demographic and Housing Estimates, 2016. Retrieved on March, 2018 from https://factfinder.census.gov/....
66.
Wang, M.-T. (2012). Educational and career interests in math: A longitudinal examination of the links between classroom environment, motivational beliefs, and interests. Developmental Psychology, 48(6), 1643-1657. https://doi.org/10.1037/a00272....
67.
Washington, J. (2011). What’s behind declining numbers of blacks in science, tech, engineering and math fields? AP.
68.
Watson, M., & McMahon, M. (2005). Children’s career development: A research review from a learning perspective. Journal of Vocational Behavior, 67(2), 119-132. https://doi.org/10.1016/j.jvb.....
69.
Watt, 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/a00278....
70.
Wigfield, A., & Eccles, J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68-81.
71.
Xie, Y., & Achen, A. (2009). Science on the decline? Educational outcomes of three cohorts of young Americans. Ann Arbor, MI: Population Studies Center, University of Michigan.
72.
Yerdelen, S., Kahraman, N., & Tas, Y. (2016). Low Socioeconomic Status Students’ STEM Career Interest in Relation to Gender, Grade Level, and STEM Attitude. Journal of Turkish Science Education, 13, 59-74.
73.
Yerdelen-Damar, S., & Pesman, H. (2013). Relations of Gender and Socioeconomic Status to Physics through Metacognition and Self-Efficacy. Journal of Educational Research, 106(4), 280-289. https://doi.org/10.1080/002206....
74.
Yildirim, B., & Selvi, M. (2015). Adaption of STEM Attitude Scale to Turkish. Electronic Turkish Studies, 10(3), 1117-1130.
75.
Yore, L., Bisanz, G. L., & Hand, B. M. (2003). Examining the literacy component of science literacy: 25 years of language arts and science research. International Journal of Science Education, 25(6), 689-725.
Share
RELATED ARTICLE
| eISSN: | 1305-8223 |
| ISSN: | 1305-8215 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
