Abstract
Ongoing policy discussions emphasize the need for more STEM professionals to keep the United States internationally competitive in scientific fields and industry. From a K-16 perspective, it is important to note that students’ trajectories into STEM professions are often shaped by their high school experiences—especially in mathematics. Accordingly, this study employs a strength-based framework to examine students’ high school math achievement with an emphasis on the role of their math-related personal and social strengths. This research uses data from the NCES High School Longitudinal Study, a large-scale national study that emphasizes students’ math outcomes. Moderated regression was utilized to examine associations between students’ high school math-related strengths and their math achievement, as well as how these relationships may differ based upon students’ prior math achievement. The findings suggest that a number of students’ strengths in math were positively related to their math achievement; however, some of these relationships differed base upon prior math achievement levels. Accordingly, while math-related strengths can be equally beneficial for students in some instances, in other instances there is a need to better understand these relationships with some nuance. Implications for K-16 STEM education policy, practice and research are discussed.
Similar content being viewed by others
Data Availability
The data that support the findings of this study are openly available from the National Center for Education Statistics at https://nces.ed.gov/surveys/hsls09/hsls09_data.asp
Change history
26 April 2021
A Correction to this paper has been published: https://doi.org/10.1007/s41979-021-00051-5
References
Ahmed, W., Minnaert, A., van der Wer, G., & Kuyper, H. (2010). Perceived social support and early adolescents’ achievement: The meditational roles of motivational beliefs and emotions. Journal of Youth Adolescence, 39(1), 36–46.
Aschbacher, P. R., Li, E., & Roth, E. J. (2010). Is science me? High school students' identities, participation and aspirations in science, engineering, and medicine. Journal of Research in Science Teaching: The Official Journal of the National Association for Research in Science Teaching, 47(5), 564–582.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman and Company.
Blackwell, L. S., Trzesniewski, K. H., & Dweck, C. S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78(1), 246–263.
Bottia, M. C., Stearns, E., Mickelson, R. A., Moller, S., & Parker, A. D. (2015). The relationships among high school STEM learning experiences and students' intent to declare and declaration of a STEM major in college. Teachers College Record, 117(3), n3.
Bowman, P. J. (1985). Black fathers and the provider role: Role strain, informal coping resources and life happiness. In A. W. Boykin (Ed.), Empirical research in black psychology (pp. 9–19). Washington, DC: National Institute for Mental Health.
Bowman, P. J. (2006). Role strain and adaptation issues in the strength-based model: Diversity, multilevel, and life-span considerations. The Counseling Psychologist, 34(1), 118–133.
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: The Official Journal of the National Association for Research in Science Teaching, 45(9), 971–1002.
Brown, K., Plozai, J., & Margetta, R. (2018). NASA, National Science Foundation announce support for White House STEM engagement plan. Retrieved from https://www.nasa.gov/press-release/nasa-national-science-foundation-announce-support-for-white-house-stem-engagement-plan Accessed April 6, 2020.
Burt, B. A., Williams, K. L., & Smith, W. A. (2018). Into the storm: Ecological and sociological impediments to black males’ persistence in engineering graduate programs. American Educational Research Journal, 55(5), 965–1006.
Burt, B. A., Williams, K. L., & Palmer, G. J. (2019). It takes a village: The role of emic and etic adaptive strengths in the persistence of black men in engineering graduate programs. American Educational Research Journal, 56(1), 39–74.
Chatterjee, S., & Hadi, A. S. (2015). Regression analysis by example. Hoboken: Wiley.
Cheema, J. R., & Galluzzo, G. (2013). Analyzing the gender gap in math achievement: Evidence from a large-scale US sample. Research in Education, 90(1), 98–112.
Chubin, D. E., & DePass, A. L. (2015). Understanding interventions that broaden participation in research careers: Translating research, impacting practice, vol. 7. Retrieved from http://understanding-interventions.org/wp-content/uploads/2016/05/Understanding-Interventions-2015-Report.pdf Accessed April 6, 2020.
DePass, A. L., & Chubin, D. E. (2014). Understanding interventions that broaden participation in research careers: Growing the community, vol. 6. Retrieved from http://understanding-interventions.org/wp-content/uploads/2015/06/Understanding-Interventions-2014.pdf.
DePass, A. L., & Chubin, D. E. (2016). Understanding interventions that broaden participation in research careers: Collaborative interventions, vol. 8. Retrieved from http://understanding-interventions.org/wp-content/uploads/2017/10/UI-2016-Conference-Report.pdf Accessed April 6, 2020.
Dweck, C. (2006). Mindset: The new psychology of success. New York: Random House.
Dweck, C. S. (2007). Is math a gift? Beliefs that put females at risk. In S. J. Ceci & W. M. Williams (Eds.), Why aren't more women in science?: Top researchers debate the evidence (pp. 47–55). Washington, DC: American Psychological Association.
Eris, O., Chachra, D., Chen, H. L., Sheppard, S., Ludlow, L., Rosca, C., et al. (2010). Outcomes of a longitudinal administration of the persistence in engineering survey. Journal of Engineering Education, 99(4), 371–395.
Erturan, S., & Jansen, B. (2015). An investigation of boys’ and girls’ emotional experience of math, their math performance, and the relation between these variables. European Journal of Psychology in Education, 30(4), 421–435.
Fantuzzo, J., LeBoeuf, W., Rouse, H., & Chen, C. C. (2012). Academic achievement of African American boys: A city-wide, community-based investigation of risk and resilience. Journal of School Psychology, 50(5), 559–579.
French, B. F., Immekus, J. C., & Oakes, W. C. (2005). An examination of indicators of engineering students' success and persistence. Journal of Engineering Education, 94(4), 419–425.
Garcia-Melgar, A., & Meyers, N. (2020). STEM near peer mentoring for secondary school students: A case study of university mentors’ experiences with online mentoring. Journal for STEM Education Research, 1–24. https://doi.org/10.1007/s41979-019-00024-9.
Goode, W. J. (1960). A theory of role strain. American Sociological Review, 25(1), 483–496.
Gottfried, M. A., & Plasman, J. S. (2018). From secondary to postsecondary: Charting an engineering career and technical education pathway. Journal of Engineering Education, 107(4), 531–555.
Griffith, D. M., Gunter, K., & Allen, J. O. (2011). Male gender role strain as a barrier to African American men’s physical activity. Health Education & Behavior, 38(5), 482–491.
Hahs-Vaughn, D. L. (2005). A primer for using and understanding weights with national datasets. The Journal of Experimental Education, 73(3), 221–248.
Howard, T. C., & Reynolds, R. (2008). Examining parent involvement in reversing the underachievement of African American students in middle-class schools. Educational Foundations, 22(1–2), 79–98.
Hyde, J. S., Lindberg, S. M., Linn, M. C., Ellis, A. B., & Williams, C. C. (2008). Gender similarities characterize math performance. Science, 321(5888), 494–495.
Ingels, S. J., Pratt, D. J. Herget, D. R., Dever, J. A., Fritch, L. B., Ottem, R.,… Leinwand, S. (2013). High School longitudinal study of 2009 (HSLS:09) base year to first follow-up data file documentation (NCES 2014-361). Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education.
Jeynes, W. H. (2007). The relationship between parental involvement and urban secondary school student academic achievement: A meta-analysis. Urban Education, 42(1), 82–110.
Jones, 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.
Kim, T. E. (2019). LA’s school counselors strike back. Retrieved from https://hechingerreport.org/las-school-counselors-strike-back/ Accessed April 6, 2020.
Kotok, S. (2017). Unfulfilled potential: High-achieving minority students and the high school achievement gap in math. High School Journal, 100(3), 183–202.
Liu, X., & Koirala, H. (2009). The effect of mathematics self-efficacy on mathematics achievement of high school students. NERA Conference Proceedings.
Lombardo, C. (2018). With hundreds of students, school counselors just try to ‘stay afloat’. Retrieved from https://www.npr.org/sections/ed/2018/02/26/587377711/with-hundreds-of-students-school-counselors-just-try-to-stay-afloat Accessed April 6, 2020.
Mandara, J., Varner, F., Greene, N., & Richman, S. (2009). Intergenerational family predictors of the black-white achievement gap. Journal of Educational Psychology, 101(4), 867–878.
McGee, E., & Pearman II, F. A. (2014). Risk and protective factors in mathematically talented black male students: Snapshots from kindergarten through eighth grade. Urban Education, 49(4), 363–393.
Means, B., Wang, H., Wei, X., Iwatani, E., & Peters, V. (2018). Broadening participation in STEM college majors: Effects of attending a STEM-focused high school. AERA Open, 4(4). https://doi.org/10.1177/2332858418806305.
Meece, J. L., Wigfield, A., & Eccles, J. S. (1990). Predictors of math anxiety and its influence on young adolescents' course enrollment intentions and performance in mathematics. Journal of Educational Psychology, 82(1), 60.
Murayama, K., Pekrun, R., Lichtenfeld, S., & Vom Hofe, R. (2013). Predicting long-term growth in students’ mathematics achievement: The unique contributions of motivation and cognitive strategies. Child Development, 84(4), 1475–1490.
Nosek, B. A., Banaji, M. R., & Greenwald, A. G. (2002). Math=male, me=female, therefore math≠me. Journal of Personality and Social Psychology, 83(1), 44–59.
Pajares, F., & Miller, D. (1994). Role of self-efficacy and self-concept beliefs in mathematical problem solving: A path analysis. Journal of Educational Psychology, 86(2), 193–203.
Pantziara, M. (2016). Student self-efficacy beliefs. In M. S. Hannula (Ed.), Attitudes, beliefs, motivation, and identity in mathematics education: An overview of the field and future directions (pp. 7–11). Heidelberg: Springer International Publishing.
Redwood, F. (2019). Advocates: school counselor shortage hurts school safety. Retrieved from https://nbc25news.com/news/local/advocates-school-counselor-shortage-hurts-school-safety Accessed April 6, 2020.
Skaalvik, E. M., Federici, R. A., & Klassen, R. M. (2015). Mathematics achievement and self-efficacy: Relations with motivation for mathematics. International Journal of Educational Research, 72, 129–136.
SMASH Academy (2018). How SMASH academy works. Retrieved from https://www.smash.org/programs/smash-academy/# Accessed April 6, 2020.
STEP (n.d.). The Science and Technology Entry Program (STEP). Retrieved from https://www.nyu.edu/admissions/undergraduate-admissions/how-to-apply/all-freshmen-applicants/opportunity-programs/pre-college-programs.html Accessed April 6, 2020.
Stinson, D. W. (2006). African American male adolescents, schooling (and mathematics): Deficiency, rejection, and achievement. Review of Educational research, 76(4), 477–506.
Strauss, V. (2013). How big is the school counselor shortage? Big. Retrieved from https://www.washingtonpost.com/news/answer-sheet/wp/2013/03/20/how-big-is-the-school-counselor-shortage-big/ Accessed April 6, 2020.
Strayhorn, T. L. (2010). The role of schools, families, and psychological variables on math achievement of black high school students. The High School Journal, 93(4), 177–194.
Syed, M., Azmitia, M., & Cooper, C. R. (2011). Identity and academic success among underrepresented ethnic minorities: An interdisciplinary review and integration. Journal of Social Issues, 67(3), 442–468.
Talafian, H., Moy, M. K., Woodard, M. A., & Foster, A. N. (2019). STEM identity exploration through an immersive learning environment. Journal for STEM Education Research, 2(2), 105–127.
The White House. (n.d.). Education. Retrieved from https://www.whitehouse.gov/issues/education/ Accessed April 6, 2020.
Thomas, S. L., & Heck, R. H. (2001). Analysis of large-scale secondary data in higher education research: Potential perils associated with complex sampling designs. Research in Higher Education, 42(5), 517–540.
Ting, S. M. R., & Man, R. (2001). Predicting academic success of first-year engineering students from standardized test scores and psychosocial variables. International Journal of Engineering Education, 17(1), 75–80.
Tyson, W., Lee, R., Borman, K. M., & Hanson, M. A. (2007). Science, technology, engineering, and mathematics (STEM) pathways: High school science and math coursework and postsecondary degree attainment. Journal of Education for Students Placed at Risk, 12(3), 243–270.
U.S. Department of Education. (n.d.). Science, technology, engineering and math: Education for global leadership. Retrieved from https://www.ed.gov/stem Accessed April 6, 2020.
Usher, E. L., & Pajares, F. (2008). Sources of self-efficacy in school: Critical review of the literature and future directions. Review of Educational Research, 78(4), 751–796.
Wang, X. (2013). Why students choose STEM majors: Motivation, high school learning, and postsecondary context of support. American Educational Research Journal, 50(5), 1081–1121.
Wang, M. T., & Degol, J. (2013). Motivational pathways to STEM career choices: Using expectancy–value perspective to understand individual and gender differences in STEM fields. Developmental Review, 33(4), 304–340.
White House Office of Science and Technology Policy (2018). Charting a course for success: America’s strategy for STEM education. Retrieved from https://www.whitehouse.gov/wp-content/uploads/2018/12/STEM-Education-Strategic-Plan-2018.pdf
Williams, K. L. (2014a) Financial impediments, academic challenges and pipeline intervention efficacy: A role strain and adaptation approach to successful STEM outcomes for underrepresented students (unpublished doctoral dissertation). University of Michigan.
Williams, K. L. (2014b). Strains, strengths, and intervention outcomes: A critical examination of intervention efficacy for underrepresented groups. New Directions for Institutional Research, 2013(158), 9–22.
Williams, M. M., & George-Jackson, C. (2014). Using and doing science: Gender, self-efficacy, and science identity of undergraduate students in STEM. Journal of Women and Minorities in Science and Engineering, 20(2), 99–126.
Williams, K. L., Burt, B. A., & Hilton, A. (2016). Math achievement: A strain and adaptive strengths approach. Journal for Multicultural Education, 10(3), 368–383.
Williams, K. L., Mustafaa, F. N., & Burt, B. A. (2019). Black males and early math achievement: An examination of students’ strengths and role strain with policy implications. Journal of Women and Minorities in Science and Engineering, 25(4), 325–352.
Zhang, G., Anderson, T. J., Ohland, M. W., & Thorndyke, B. R. (2004). Identifying factors influencing engineering student graduation: A longitudinal and cross-institutional study. Journal of Engineering Education, 93(4), 313–320.
Acknowledgements
I would like to thank Akeisha Young for her assistance with earlier stages of this research. I would also like to thank Dr. Jane Daquin for her insightful feedback regarding the research design and development of this study.
Funding
This research was supported by a grant from the American Educational Research Association which receives funds for its “AERA Grants Program” from the National Science Foundation under NSF award NSF-DRL #1749275. Opinions reflect those of the author and do not necessarily reflect those AERA or NSF.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest
The corresponding author states that there is no conflict of interest.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Williams, K.L. Contextualizing Math-Related Strengths and Math Achievement: Positive Math Orientations, Social Supports and the Moderating Effects of Prior Math Knowledge. Journal for STEM Educ Res 3, 317–342 (2020). https://doi.org/10.1007/s41979-020-00033-z
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41979-020-00033-z