Social Psychology of Education

, Volume 22, Issue 3, pp 557–577 | Cite as

Modeling gender counter-stereotypic group behavior: a brief video intervention reduces participation gender gaps on STEM teams

  • Neil A. LewisJr.Email author
  • Denise Sekaquaptewa
  • Lorelle A. Meadows


In STEM project group teams, men speak for more time (Meadows and Sekaquaptewa, in: Proceedings of ASEE annual conference, 2011) and engage in more active technical participation than women, which can have negative long-term consequences (Cheryan et al. in Psychol Bull 143:1–35, 2017; Lord et al. in IEEE Trans Educ 54(4):610–618, 2011). In the current study, we tested the effects of a brief counter-stereotypic video intervention on gender gaps in verbal participation on mixed-gender teams of STEM students (N = 143). Participants viewed either a control video of an engineering student team behaving in a gender stereotype-consistent way (men talked longer and presented more technical information than women) in a group presentation and group interview, or a gender counter-stereotypic intervention version (roles reversed) prior to engaging in their own STEM group project task in a laboratory setting. Analysis of video footage of the groups showed that men spoke longer than women in the control condition, but men and women spoke for equal time in the intervention condition. This result was corroborated by participants’ self-report of their verbal participation in their group.


Teaching intervention Group dynamics Behavior change STEM Stereotypes 



The authors wish to recognize the contributions of the following individuals who served as research assistants for this project: Sophie Bright, Haben Debassai, Jenna Dehne, Nader Hakim, Katie Hu, Laura Knutilla, Subramonian Mahadevan, Adrianna Pierce, Golnoosh Rasoulifar, Kelsey Reimenschneider, Jennifer Schoenberger, Linsa Varghese, Julianne Vernon, and Jakob Williams. This study was funded by the National Science Foundation, Grant No. 1137031. “Research Initiation Grant: Developing strategies to improve women’s active participation in engineering student group project teams.” D. Sekaquaptewa, co-PI, with L. A. Meadows, co-PI.

Compliance with ethical standards

Conflict of interest

The authors declared that they had no conflicts of interest with respect to their authorship or the publication of this article.

Supplementary material

11218_2019_9489_MOESM1_ESM.pdf (208 kb)
Supplementary material 1 (PDF 207 kb)


  1. Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888–918.Google Scholar
  2. Bandura, A. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of Social and Clinical Psychology, 4(3), 359–373.Google Scholar
  3. Bandura, A. (1997). Self-efficacy: The exercise of control. London: Macmillan.Google Scholar
  4. Bem, D. J. (1972). Self-perception theory. In Advances in experimental social psychology (Vol. 6, pp. 1-62). London: Academic Press.Google Scholar
  5. Bennett, J. E., & Sekaquaptewa, D. (2014). Setting an egalitarian social norm in the classroom: Improving attitudes towards diversity among male engineering students. Social Psychology of Education, 17(2), 343–355.Google Scholar
  6. Betz, D. E., & Sekaquaptewa, D. (2012). My fair physicist? Feminine math and science role models demotivate young girls. Social Psychological and Personality Science, 3(6), 738–746.Google Scholar
  7. Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Cambridge, MA: Harvard University Press.Google Scholar
  8. Bullock, J. G., Green, D. P., & Ha, S. E. (2010). Yes, But what’s the mechanism? (Don’t expect an easy answer). Journal of Personality and Social Psychology, 98(4), 550–558.Google Scholar
  9. Carberry, A. R., Lee, H. S., & Ohland, M. W. (2010). Measuring engineering design self-efficacy. Journal of Engineering Education, 99(1), 71–79.Google Scholar
  10. Cheryan, S., Ziegler, S. A., Montoya, A. K., & Jiang, L. (2017). Why are some STEM fields more gender balanced than others? Psychological Bulletin, 143, 1–35.Google Scholar
  11. Cialdini, R. B. (1984). Influence: The psychology of persuasion. New York: Harper Collins.Google Scholar
  12. Cialdini, R. B. (2016). Pre-suasion: A revolutionary way to influence and persuade. New York: Simon & Schuster.Google Scholar
  13. Cialdini, R. B., Kallgren, C. A., & Reno, R. R. (1991). A focus theory of normative conduct: A theoretical refinement and reevaluation of the role of norms in human behavior. Advances in Experimental Social Psychology, 24, 201–234.Google Scholar
  14. Dasgupta, N., McManus Scircle, M., & Hunsinger, M. (2015). Female peers in small work groups enhance women’s motivation, verbal participation, and career aspirations in engineering. In Proceedings of the National Academy of Sciences.
  15. Dennehy, T. C., & Dasgupta, N. (2017). Female peer mentors early in college increase women’s positive academic experiences and retention in engineering. Proceeding of the National Academy of Sciences, 114(23), 5964–5969.Google Scholar
  16. Devine, P. G. (1989). Stereotypes and prejudice: Their automatic and controlled components. Journal of Personality and Social Psychology, 56(1), 5–18.Google Scholar
  17. Devine, P. G., Forscher, P. S., Austin, A. J., & Cox, W. T. (2012). Long-term reduction in implicit race bias: A prejudice habit-breaking intervention. Journal of Experimental Social Psychology, 48(6), 1267–1278.Google Scholar
  18. Diekman, A. B., Steinberg, M., Brown, E. R., Belanger, A. L., & Clark, E. K. (2017). A goal congruity model of role entry, engagement, and exit: understanding communal goal processes in STEM gender gaps. Personality and Social Psychology Review, 21(2), 142–175.Google Scholar
  19. Earl, A., & Lewis, N. A., Jr. (2019). Health in context: New perspectives on healthy thinking and healthy living. Journal of Experimental Social Psychology, 81(3), 1–4.Google Scholar
  20. Forscher, P. S., Mitamura, C., Dix, E. L., Cox, W. T. L., & Devine, P. G. (2017). Breaking the prejudice habit: Mechanisms, timecourse, and longevity. Journal of Experimental Social Psychology, 72, 133–146.Google Scholar
  21. Freeman, T. M., Anderman, L. H., & Jensen, J. M. (2007). Sense of belonging in college freshmen at the classroom and campus levels. Journal of Experimental Education, 75, 203–220.Google Scholar
  22. Greenwald, A. G., Poehlman, T. A., Uhlmann, E. L., & Banaji, M. R. (2009). Understanding and using the implicit association test. Journal of Personality and Social Psychology, 97(1), 17–41.Google Scholar
  23. Haidet, P., Kubitz, K., & McCormack, W. T. (2014). Analysis of the team-based learning literature: TBL comes of age. Journal on Excellence in College Teaching, 25(3–4), 303–333.Google Scholar
  24. Latu, I. M., Mast, M. S., Lammers, J., & Bombari, D. (2013). Successful female leaders empower women’s behavior in leadership tasks. Journal of Experimental Social Psychology, 49(3), 444–448.Google Scholar
  25. Leaper, C., & Ayres, M. M. (2007). A meta-analytic review of gender variations in adults’ language use: Talkativeness, affiliative speech, and assertive speech. Personality and Social Psychology Review, 11(4), 328–363.Google Scholar
  26. Lewis, N. A., Jr., & Sekaquaptewa, D. (2016). Beyond test performance: A broader view of stereotype threat. Current Opinion in Psychology, 11, 40–43.Google Scholar
  27. Lewis, N. A., Jr., & Yates, J. F. (2019). Preparing disadvantaged students for success in college: Lessons learned from the preparation initiative. Perspectives on Psychological Science, 14(1), 54–59.Google Scholar
  28. Lord, S. M., Layton, R. A., & Ohland, M. W. (2011). Trajectories of electrical engineering and computer engineering students by race and gender. Education, IEEE Transactions on Education, 54(4), 610–618.Google Scholar
  29. Love, A. G., Dietrich, A., Fitzgerald, J., & Gordon, D. (2014). Integrating collaborative learning inside and outside of the classroom. Journal on Excellence in College Teaching, 25(3/4), 177–196.Google Scholar
  30. Markus, H., & Wurf, E. (1987). The dynamic self-concept: A social psychological perspective. Annual Review of Psychology, 38(1), 299–337.Google Scholar
  31. Marx, D. M., & Roman, J. S. (2002). Female role models: Protecting women’s math test performance. Personality and Social Psychology Bulletin, 28(9), 1183–1193.Google Scholar
  32. Meadows, L., & Sekaquaptewa, D. (2011). The effect of group gender composition on student participation and learning in undergraduate engineering project teams. In Proceedings of ASEE annual conference (pp. 2011–1319).Google Scholar
  33. Meadows, L. A., & Sekaquaptewa, D. (2013). The influence of gender stereotypes on role adoption in student teams. In Proceedings of the 120th ASEE annual conference exposition (pp. 1–16). Washington, DC: American Society for Engineering Education.Google Scholar
  34. Michaelsen, L. K., Davidson, N., & Major, C. H. (2014). Team-based learning practices and principles in com-parison with cooperative learning and problem-based learning. Journal on Excellence in College Teaching, 25(3/4), 57–84.Google Scholar
  35. Montgomery, J. M., Nyhan, B., & Torres, M. (2018). How conditioning on posttreatment variables can ruin your experiment and what to do about it. American Journal of Political Science, 62(3), 760–775.Google Scholar
  36. Nisbett, R. E., & Wilson, T. D. (1977). Telling more than we can know: Verbal reports on mental processes. Psychological Review, 84(3), 231–259.Google Scholar
  37. Nosek, B. A., Smyth, F. L., Sriram, N., Lindner, N. Am., Devost, T., Ayala, A., et al. (2009). National differences in gender-science stereotypes predict national sex differences in science and math achievement. Proceedings of the National Academy of Science, 106(26), 10593–10597.Google Scholar
  38. O’Dwyer, L. M., & Parker, C. E. (2014). A primer for analyzing nested data: Multilevel modeling in SPSS using an example from a REL study (REL (2015-046). Washington, DC: US.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Education Laboratory Northeast & Islands. Retrieved from
  39. Oyserman, D., Destin, M., & Novin, S. (2015). The context-sensitive future self: Possible selves motivate in context, not otherwise. Self and Identity, 14(2), 173–188.Google Scholar
  40. Oyserman, D., & Lewis, N. A., Jr. (2017). Seeing the destination AND the path: Using identity-based motivation to understand and reduce racial disparities in academic achievement. Social Issues and Policy Review, 11(1), 159–194.Google Scholar
  41. Page, S. (2007). The difference: How the power of diversity creates better groups, firms, schools, and societies. NJ: Princeton University Press.Google Scholar
  42. Page, S. E. (2017). The diversity bonus: How great teams pay off in the knowledge economy. Princeton: Princeton University Press.Google Scholar
  43. Paluck, E. L. (2017, October). Messy Interventions. In Presentation at the group processes pre-conference to the society for experimental social psychology annual meeting. Boston, MA.Google Scholar
  44. President’s Council of Advisors on Science and Technology (PCAST). (2012). Report to the President: Engage to excel: Producing one million additional college graduates with degrees in science, technology, engineering, and mathematics. Accessed 21 October 2013.
  45. Rosser, S. V. (1998). Group work in science, engineering, and mathematics: Consequences of ignoring gender and race. College Teaching, 46(6), 82–88.Google Scholar
  46. Severiens, S., & Schmidt, H. (2009). Academic and social integration and study progress in problem based learning. Higher Education, 58(1), 59–69.Google Scholar
  47. Shepherd, H., & Paluck, E. L. (2015). Stopping the drama: Gendered influence in a network field experiment. Social Psychology Quarterly, 78(2), 173–193.Google Scholar
  48. Simons, D. J., Shoda, Y., & Lindsay, D. S. (2017). Constraints on generality (COG): A proposed additional to all empirical papers. Perspectives on Psychological Science, 12(6), 1123–1128.Google Scholar
  49. Stout, J. G., Dasgupta, N., Hunsinger, M., & McManus, M. A. (2011). STEMing the tide: using ingroup experts to inoculate women’s self-concept in science, technology, engineering, and mathematics (STEM). Journal of Personality and Social Psychology, 100(2), 255.Google Scholar
  50. Strobel, J., & Van Barneveld, A. (2009). When is PBL more effective? A meta-synthesis of meta-analyses comparing PBL to conventional classrooms. Interdisciplinary Journal of Problem-Based Learning, 3(1), 44–58.Google Scholar
  51. Tankard, M. E., & Paluck, E. L. (2016). Norm perception as a vehicle for social change. Social Issues and Policy Review, 10(1), 181–211.Google Scholar
  52. Tankard, M. E., & Paluck, E. L. (2017). The effect of a supreme court decision regarding gay marriage on social norms and personal attitudes. Psychological Science, 28(9), 1334–1344.Google Scholar
  53. Walton, G. M., & Cohen, G. L. (2007). A question of belonging: Race, social fit, and achievement. Journal of Personality and Social Psychology, 92(1), 82–96.Google Scholar
  54. Webb, T. L., & Sheeran, P. (2006). Does changing behavioral intentions engender behavior change? A meta-analysis of the experimental evidence. Psychological Bulletin, 132(2), 249–268.Google Scholar
  55. Wilson, D. M., Bell, P., Jones, D., & Hansen, L. (2010). A cross sectional study of belonging in engineering communities. International Journal of Engineering Education, 26(3), 687–698.Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Communication, Center for Health Equity, Center for the Study of Inequality, Roper Center for Public Opinion ResearchCornell UniversityIthacaUSA
  2. 2.Department of PsychologyUniversity of MichiganAnn ArborUSA
  3. 3.Pavlis Honors CollegeMichigan Technological UniversityHoughtonUSA

Personalised recommendations