Skip to main content

Advertisement

SpringerLink
Log in

Gender Gap in Science, Technology, Engineering, and Mathematics (STEM): Current Knowledge, Implications for Practice, Policy, and Future Directions

  • Review Article
  • Published:
Educational Psychology Review Aims and scope Submit manuscript

Abstract

Although the gender gap in math course-taking and performance has narrowed in recent decades, females continue to be underrepresented in math-intensive fields of Science, Technology, Engineering, and Mathematics (STEM). Career pathways encompass the ability to pursue a career as well as the motivation to employ that ability. Individual differences in cognitive capacity and motivation are also influenced by broader sociocultural factors. After reviewing research from the fields of psychology, sociology, economics, and education over the past 30 years, we summarize six explanations for US women’s underrepresentation in math-intensive STEM fields: (a) cognitive ability, (b) relative cognitive strengths, (c) occupational interests or preferences, (d) lifestyle values or work-family balance preferences, (e) field-specific ability beliefs, and (f) gender-related stereotypes and biases. We then describe the potential biological and sociocultural explanations for observed gender differences on cognitive and motivational factors and demonstrate the developmental period(s) during which each factor becomes most relevant. We then propose evidence-based recommendations for policy and practice to improve STEM diversity and recommendations for future research directions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Ackerman, P. L., Bowen, K. R., Beier, M. E., & Kanfer, R. (2001). Determinants of individual differences and gender differences in knowledge. Journal of Educational Psychology, 93, 797–825.

    Article  Google Scholar 

  • Alexander, G. M., Wilcox, T., & Woods, R. (2009). Sex differences in infants’ visual interest in toys. Archives of Sexual Behavior, 38, 427–433. doi:10.1007/s10508-008-9430-1.

    Article  Google Scholar 

  • Allen, S. (2004). Designs for learning: studying science museum exhibits that do more than entertain. Science Education. doi:10.1002/sce.20016.

    Google Scholar 

  • American Association of University Women Educational Foundation. (2008). Where the girls are: the facts about gender equity in education. Washington: Author.

    Google Scholar 

  • Baker, M., & Milligan, K. (2013). Boy-girl differences in parental time investments: evidence from three countries. National Bureau of Economic Research (NBER) Working Paper 18893. Retrieved from http://www.nber.org/papers/w18893. doi: 10.3386/w18893

  • 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, 246–263. doi:10.1111/j.1467-8624.2007.00995.x.

    Article  Google Scholar 

  • Bleeker, M. M., & Jacobs, J. E. (2004). Achievement in math and science: do mothers’ beliefs matter 12 years later? Journal of Educational Psychology, 96, 97–109. doi:10.1037/0022-0663.96.1.97.

    Article  Google Scholar 

  • Ceci, S. J., & Williams, W. M. (2011). Understanding current causes of women’s underrepresentation in science. PNAS, 108, 3157–3162. doi:10.1073/pnas.1014871108.

    Article  Google Scholar 

  • Ceci, S. J., Williams, W. M., & Barnett, S. M. (2009). Women’s underrepresentation in science: sociocultural and biological considerations. Psychological Bulletin, 135, 218–261. doi:10.1037/a0014412.

    Article  Google Scholar 

  • Ceci, S. J., Ginther, D. K., Kahn, S., & Williams, W. M. (2014). Women in academic science: a changing landscape. Psychological Science in the Public Interest, 15, 75–141. doi:10.1177/1529100614541236.

    Article  Google Scholar 

  • Cheryan, S., & Plaut, V. C. (2010). Explaining underrepresentation: a theory of precluded interest. Sex Roles, 63, 475–488. doi:10.1007/s11199-010-9835-x.

    Article  Google Scholar 

  • Cheryan, S., Plaut, V. C., Davies, P. G., & Steele, C. M. (2009). Ambient belonging: how stereotypical cues impact gender participation in computer science. Journal of Personality and Social Psychology, 97, 1045–1060. doi:10.1037/a0016239.

    Article  Google Scholar 

  • Cheryan, S., Meltzoff, A. N., & Kim, S. (2011a). Classrooms matter: the design of virtual classrooms influences gender disparities in computer science classes. Computers & Education, 57, 1825–1835. doi:10.1016/j.compedu.2011.02.004.

    Article  Google Scholar 

  • Cheryan, S., Siy, J. O., Vichayapai, M., Drury, B. J., & Kim, S. (2011b). Do female and male role models who embody STEM stereotypes hinder women’s anticipated success in STEM? Social Psychological and Personality Science, 2, 656–664. doi:10.1177/1948550611405218.

    Article  Google Scholar 

  • Chow, 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, 1612–1628. doi:10.1037/a0030194.

    Article  Google Scholar 

  • Correll, S. J. (2001). Gender and the career choice process: the role of biased self‐assessments. American Journal of Sociology, 106, 1691–1730. doi:10.1086/321299.

    Article  Google Scholar 

  • Crosnoe, R., Riegle-Crumb, C., Field, S., Frank, K., & Muller, C. (2008). Peer group contexts of girls’ and boys’ academic experiences. Child Development, 79, 139–155. doi:10.1111/j.1467-8624.2007.01116.x.

    Article  Google Scholar 

  • Crowley, K., Callanan, M. A., Tenenbaum, H. R., & Allen, E. (2001). Parents explain more often to boys than to girls during shared scientific thinking. Psychological Science, 12, 258–261. doi:10.1111/1467-9280.00347.

    Article  Google Scholar 

  • Cvencek, D., Meltzoff, A. N., & Greenwald, A. G. (2011). Math–gender stereotypes in elementary school children. Child Development, 82, 766–779. doi:10.1111/j.14678624.2010.01529.x.

    Article  Google Scholar 

  • Deutsch, F. M. (2003). How small classes benefit high school students. NASSP Bulletin, 87, 35–44. doi:10.1177/019263650308763504.

    Article  Google Scholar 

  • Diekman, A. B., Brown, E., Johnston, A., & Clark, E. (2010). Seeking congruity between goals and roles: a new look at why women opt out of STEM careers. Psychological Science, 21, 1051–1057. doi:10.1177/0956797610377342.

    Article  Google Scholar 

  • Diekman, A. B., Clark, E. K., Johnston, A. M., Brown, E. R., & Steinberg, M. (2011). Malleability in communal goals and beliefs influences attraction to STEM careers: evidence for a goal congruity perspective. Journal of Personality and Social Psychology, 101, 902–918. doi:10.1037/a0025199.

    Article  Google Scholar 

  • Dweck, C. S. (2002). The development of ability conceptions. In A. Wigfield & J. S. Eccles (Eds.), Development of achievement motivation. A volume in the educational psychology series: Vol. xvii, (pp. 57–88). San Diego, CA: Academic Press. doi:10.1016/B978-012750053-9/50005-X.

  • Dweck, C. (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 1460 science? Top researchers debate the evidence (pp. 47–55). Washington: APA Press. doi:10.1037/11546-004.

    Chapter  Google Scholar 

  • Eccles, J. S. (2009). Who am I and what am I going to do with my life? Personal and collective identities as motivators of action. Educational Psychologist, 44, 78–89. doi:10.1080/00461520902832368.

    Article  Google Scholar 

  • Eccles, J. S., Wigfield, A., Harold, R. D., & Blumenfeld, P. (1993). Age and gender differences in children’s self- and task perceptions during elementary school. Child Development, 64, 830–847. doi:10.1111/j.1467-8624.1993.tb02946.x.

    Article  Google Scholar 

  • Eccles, J. S., Barber, B., & Jozefowicz, D. (1999). Linking gender to educational, occupational, and recreational choice: applying the Eccles et al. model of achievement-related choices. In J. T. Spence (Ed.), Sexism and stereotypes in modern society: the gender science of Janet Taylor Spence (pp. 153–191). Washington: APA. doi:10.1037/10277-007.

    Chapter  Google Scholar 

  • Else-Quest, N. M., Hyde, J. S., & Linn, M. C. (2010). Cross-national patterns of gender differences in mathematics: a meta-analysis. Psychological Bulletin, 136, 103–127. doi:10.1037/a0018053.

    Article  Google Scholar 

  • Ferriman, K., Lubinski, D., & Benbow, C. P. (2009). Work preferences, life values, and personal views of top math/science graduate students and the profoundly gifted: developmental changes and gender differences during emerging adulthood and parenthood. Journal of Personality and Social Psychology, 97, 517–532. doi:10.1037/a0016030.

    Article  Google Scholar 

  • Freund, A. M., Weiss, D., & Wiese, B. S. (2012). Graduating from high school: the role of gender-related attitude, attributes, and motives for a central transition in late adolescence. Switzerland: Department of Psychology, University of Zurich. doi:10.1080/17405629.2013.772508. Unpublished manuscript.

    Google Scholar 

  • Frick, A., & Wang, S. H. (2014). Mental spatial transformations in 14‐ and 16‐month‐old infants: effects of action and observational experience. Child Development, 85, 278–293. doi:10.1111/cdev.12116.

    Article  Google Scholar 

  • Friedel, J. M., Cortina, K. S., Turner, J. C., & Midgley, C. (2007). Achievement goals, efficacy beliefs and coping strategies in mathematics: the role of perceived parent and teacher goal emphases. Contemporary Educational Psychology, 32, 434–458. doi:10.1016/j.cedpsych.2006.10.009.

    Article  Google Scholar 

  • Glick, P., & Fiske, S. T. (1997). Hostile and benevolent sexism: measuring ambivalent sexist attitudes toward women. Psychology of Women Quarterly, 21, 119–135. doi:10.1111/j.1471-6402.1997.tb00104.x.

    Article  Google Scholar 

  • Hakim, C. (2006). Women, careers, and work-life preferences. British Journal of Guidance and Counseling, 34, 279–294. doi:10.1080/03069880600769118.

    Article  Google Scholar 

  • Hanson, S. L. (2004). African American women in science: experiences from high school through the post-secondary years and beyond. NWSA Journal, 16, 96–115. doi:10.1353/nwsa.2004.0033.

    Article  Google Scholar 

  • Hanson, S. L. (2007). Success in science among young African American women: the role of minority families. Journal of Family Issues, 28, 3–33. doi:10.1177/0192513X06292694.

    Article  Google Scholar 

  • Haughey, M., Snart, F., & da Costa, J. (2001). Literacy achievement in small grade 1 classes in high-poverty environments. Canadian Journal of Education, 26, 301–320. doi:10.2307/1602210.

    Article  Google Scholar 

  • Hill, C., Corbett, C., & St. Rose, A. (2010). Why so few? Women in science, technology, engineering and mathematics. Washington: American Association of University Women.

    Google Scholar 

  • Hyde, J. S., Lindberg, S. M., Linn, M. C., Ellis, A. B., & Williams, C. C. (2008). Gender similarities characterize math performance. Science, 321, 494–495. doi:10.1126/science.1160364.

    Article  Google Scholar 

  • Jacobs, J. E., & Eccles, J. S. (1992). The impact of mothers’ gender-role stereotypic beliefs on mothers’ and children’s ability perceptions. Journal of Personality and Social Psychology, 63, 932–944. doi:10.1037/0022-3514.63.6.932.

    Article  Google Scholar 

  • Jacobs, J. E., & Winslow, S. E. (2004). Overworked faculty: job and stresses and family demands. Annals of American Political and Social Scientist, 596, 104–129. doi:10.1177/0002716204268185.

    Article  Google Scholar 

  • Kelleher, C., Pausch, R., & Kiesler, S. (2007). Storytelling alice motivates middle school girls to learn computer programming. Proceeding of the SIGCHI Conference on Human Factors in Computing Systems, 1455-1464.

  • Kena, G., Musu-Gillette, L., Robinson, J., Wang, X., Rathbun, A., Zhang, J., et al. (2015). The condition of education 2015 (NCES 2015–144). U.S. Department of Education, National Center for Education Statistics. Washington, DC. Retrieved from http://nces.ed.gov/pubsearch. Accessed 26 Aug 2015.

  • King, D. K. (1992). Unraveling fabric, missing the beat: class and gender in Afro-American social issues. The Black Scholar, 22, 36–44.

    Article  Google Scholar 

  • Knobloch-Westerwick, S., Glynn, C. J., & Huge, M. (2013). The Matilda effect in science communication: an experiment on gender bias in publication quality perceptions and collaboration interest. Science Communication, 35, 603–625. doi:10.1177/1075547012472684.

    Article  Google Scholar 

  • Leaper, C., Anderson, K. J., & Sanders, P. (1998). Moderators of gender effects on parents’ talk to their children: a meta-analysis. Developmental Psychology, 34, 3–27. doi:10.1037/0012-1649.34.1.3.

    Article  Google Scholar 

  • Leaper, C., Farkas, T., & Brown, C. S. (2012). Adolescent girls’ experiences and gender-related beliefs in relation to their motivation in math/science and English. Journal of Youth and Adolescence, 41, 268–282. doi:10.1007/s10964-011-9693-z.

    Article  Google Scholar 

  • Leslie, S.-J., Cimpian, A., Meyer, M., & Freeland, E. (2015). Expectations of brilliance underlie gender distributions across academic disciplines. Science, 347, 262–265. doi:10.1126/science.1261375.

    Article  Google Scholar 

  • Liben, L. S., & Coyle, E. F. (2014). Chapter three-developmental interventions to address the STEM gender gap: exploring intended and unintended consequences. Advances in Child Development and Behavior, 47, 77–115.

    Article  Google Scholar 

  • Lindberg, S. M., Hyde, J. S., Petersen, J. L., & Linn, M. C. (2010). New trends in gender and mathematics performance: a meta-analysis. Psychological Bulletin, 136, 1123–1135. doi:10.1037/a0021276.

    Article  Google Scholar 

  • Lippa, R. A., Collaer, M. L., & Peters, M. (2010). Sex differences in mental rotation and line angle judgments are positively associated with gender equality and economic development across 53 nations. Archives of Sexual Behavior, 39, 990–997. doi:10.1007/s10508-008-9460-8.

    Article  Google Scholar 

  • Lohman, D. F., Gambrell, J., & Lakin, J. (2008). The commonality of extreme discrepancies in the ability profiles of academically gifted students. Psychology Science Quarterly, 50, 269–282.

    Google Scholar 

  • Lubienski, S. T., Robinson, J. P., Crane, C. C., & Ganley, C. M. (2013). Girls’ and boys’ mathematics achievement, affect, and experiences: findings from ECLS-K. Journal for Research in Mathematics Education, 44, 634–645. doi:10.5951/jresematheduc.44.4.0634.

    Article  Google Scholar 

  • Lubinski, D., & Benbow, C. P. (2006). Study of mathematically precocious youth after 35 years: uncovering antecedents for the development of math-science expertise. Perspectives on Psychological Science, 1, 316–345. doi:10.1111/j.1745-6916.2006.00019.x.

    Article  Google Scholar 

  • Lubinski, D., Benbow, C. P., Webb, R. M., & Bleske-Rechek, A. (2006). Tracking exceptional human capital over two decades. Psychological Science, 17, 194–199. doi:10.1111/j.1467-9280.2006.01685.x.

    Article  Google Scholar 

  • Maeda, Y., & Yoon, S. Y. (2013). A meta-analysis on gender differences in mental rotation ability measured by the Purdue spatial visualization tests: visualization of rotations (PSVT: R). Educational Psychology Review, 25, 69–94. doi:10.1007/s10648-012-9215-x.

    Article  Google Scholar 

  • Maltese, A. V., & Tai, R. H. (2010). Eyeballs in the fridge: sources of early interest in science. International Journal of Science Education, 32, 669–685. doi:10.1080/09500690902792385.

    Article  Google Scholar 

  • 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, 877–907. doi:10.1002/sce.20441.

    Article  Google Scholar 

  • Mason, M. A., & Goulden, M. (2004). Marriage and baby blues: redefining gender equity and the academy. Annals of the American Political and Social Sciences, 596, 86–103. doi:10.1177/000271620459600104.

    Article  Google Scholar 

  • Meece, J. L., Anderman, E. M., & Anderman, L. H. (2006). Classroom goal structure, student motivation, and academic achievement. Annual Review of Psychology, 57, 387–503. doi:10.1146/annurev.psych.56.091103.070258.

    Article  Google Scholar 

  • Meyer, M., Cimpian, A., & Leslie, S. J. (2015). Women are underrepresented in fields where success is believed to require brilliance. Frontiers in Psychology, 6, 1–12. doi:10.3389/fpsyg.2015.00235.

    Article  Google Scholar 

  • Miller, D. I., & Halpern, D. F. (2014). The new science of cognitive sex differences. Trends in Cognitive Sciences, 18, 37–45. doi:10.1016/j.tics.2013.10.011.

    Article  Google Scholar 

  • Miller, D. I., Eagly, A. H., & Linn, M. C. (2015). Women’s representation in science predicts national gender-science stereotypes: evidence from 66 nations. Journal of Educational Psychology, 107, 631–644.

    Article  Google Scholar 

  • Möhring, W., & Frick, A. (2013). Touching up mental rotation: effects of manual experience on 6-month-old infants’ mental object rotation. Child Development, 84, 1554–1565. doi:10.1111/cdev.12065.

    Article  Google Scholar 

  • Moore, D. S., & Johnson, S. P. (2008). Mental rotation in human infants: a sex difference. Psychological Science, 19, 1063–1066. doi:10.1111/j.1467-9280.2008.02200.x.

    Article  Google Scholar 

  • Moss-Racusin, C. A., Dovidio, J. F., Brescoll, V. L., Graham, M. J., & Handelsman, J. (2012). Science faculty’s subtle gender biases favoring male students. PNAS, 109, 16474–16479. doi:10.1073/pnas.1211286109.

    Article  Google Scholar 

  • Mueller, C. M., & Dweck, C. S. (1998). Praise for intelligence can undermine children’s motivation and performance. Journal of Personality and Social Psychology, 75, 33–52. doi:10.1037/0022-3514.75.1.33.

    Article  Google Scholar 

  • National Science Foundation. (2011). Women, minorities, and persons with disabilities in science and engineering: 2011. Arlington: National Science Foundation.

    Google Scholar 

  • Park, G., Lubienski, D., & Benbow, C. P. (2007). Contrasting intellectual patterns predict creativity in the arts and sciences. Psychological Science, 18, 948–952.

    Article  Google Scholar 

  • Quinn, P. C., & Liben, L. S. (2008). A sex difference in mental rotation in young infants. Psychological Science, 19, 1067–1070. doi:10.1111/j.1467-9280.2008.02201.x.

    Article  Google Scholar 

  • Reuben, E., Sapienza, P., & Zingales, L. (2014). How stereotypes impair women’s careers in science. PNAS, 111, 4403–4408. doi:10.1073/pnas.1314788111.

    Article  Google Scholar 

  • Robinson, J. P., & Lubienski, S. T. (2011). The development of gender achievement gaps in mathematics and reading during elementary and middle school: examining direct cognitive assessments and teacher ratings. American Educational Research Journal, 48, 268–302. doi:10.3102/0002831210372249.

    Article  Google Scholar 

  • Roseth, C. J., Johnson, D. W., & Johnson, R. T. (2008). Promoting early adolescents’ achievement and peer relationships: the effects of cooperative, competitive and individualistic goal structure. Psychological Bulletin, 134, 223–246. doi:10.1037/0033-2909.134.2.223.

    Article  Google Scholar 

  • Sadik, A. (2008). Digital storytelling: A meaningful technology-integrated approach for engaged student learning. Educational Technology Research and Development, 56, 487–506. doi:10.1007/s11423-008-9091-8.

  • 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, 70–83. doi:10.1037/0012-1649.42.1.70.

    Article  Google Scholar 

  • Spelke, E. S. (2005). Sex differences in intrinsic aptitude for mathematics and science? American Psychologist, 60, 950–958. doi:10.1037/0003-066X.60.9.950.

    Article  Google Scholar 

  • Stake, J. E., & Nickens, S. D. (2005). Adolescent girls’ and boys’ science peer relationships and perceptions of the possible self as scientist. Sex Roles, 52, 1–11. doi:10.1007/s11199-005-1189-4.

    Article  Google Scholar 

  • Stecher, B. M., & Bohrnstedt, G. W. (Eds.). (2002). Class size reduction in California: findings from 1999-00 and 2000-01. Sacramento: California Department of Education.

    Google Scholar 

  • 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, 255–270. doi:10.1037/a0021385.

    Article  Google Scholar 

  • Su, R., Rounds, J., & Armstrong, P. I. (2009). Men and things, women and people: a meta-analysis of sex differences in interests. Psychological Bulletin, 135, 859–884. doi:10.1037/a0017364.

    Article  Google Scholar 

  • Swim, J. K., & Cohen, L. L. (1997). Overt, covert, and subtle sexism: a comparison between attitudes toward women and modern sexism scales. Psychology of Women Quarterly, 21, 103–118. doi:10.1111/j.1471-6402.1997.tb00103.x.

    Article  Google Scholar 

  • Swim, J. K., Aikin, K. J., Hall, W. S., & Hunter, B. A. (1995). Sexism and racism: old-fashioned and modern prejudices. Journal of Personality and Social Psychology, 68, 199–214. doi:10.1037/0022-3514.68.2.199.

    Article  Google Scholar 

  • Swim, J. K., Mallett, R., Russo-Devosa, Y., & Stangor, C. (2005). Judgements of sexism: a comparison of the subtlety of sexism measures and sources of variability in judgements of sexism. Psychology of Women Quarterly, 29, 406–411. doi:10.1111/j.1471-6402.2005.00240.x.

    Article  Google Scholar 

  • Tai, R. H., Liu, C. Q., Maltese, A. V., & Fan, X. (2006). Planning early for careers in science. Science, 312, 1143–1144. doi:10.1126/science.1128690.

    Article  Google Scholar 

  • Tenenbaum, H. R. (2009). ‘You'd be good at that’: gender patterns in parent‐child talk about courses. Social Development, 18, 447–463. doi:10.1111/j.1467-9507.2008.00487.x.

    Article  Google Scholar 

  • Tenenbaum, H. R., & Leaper, C. (2002). Are parents’ gender schemas related to their children’s gender-related cognitions? A meta-analysis. Developmental Psychology, 38, 615–630. doi:10.1037//0012-1649.38.4.615.

    Article  Google Scholar 

  • Tiedemann, J. (2000a). Gender-related beliefs of teachers in elementary school mathematics. Educational Studies in Mathematics, 41, 191–207. doi:10.1023/A:1003953801526.

    Article  Google Scholar 

  • Tiedemann, J. (2000b). Parents’ gender stereotypes and teachers’ beliefs as predictors of children's concept of their mathematical ability in elementary school. Journal of Educational Psychology, 92, 144–151. doi:10.1007/s11199-011-9996-2.

    Article  Google Scholar 

  • Turner, J. C., & Patrick, H. (2004). Motivational influences on student participation in math classroom learning activities. Teachers College Record, 106, 1759–1785. doi:10.1111/j.1467-9620.2004.00404.x.

    Article  Google Scholar 

  • U.S. Department of Education, National Center for Education Statistics. (2012). Higher education: gaps in access and persistence study. Retrieved from http://nces.ed.gov/pubs2012/2012046/index.asp

  • U.S. Department of Education, National Center for Education Statistics (NCES). (2014). Digest of education statistics. Retrieved from https://nces.ed.gov/programs/digest/2014menu_tables.asp

  • Valla, J., & Ceci, S. J. (2011). Can sex differences in science be tied to the long reach of prenatal hormones? Brain organization theory, digit ratio (2D/4D), and sex differences in preference and cognition. Perspectives on Psychological Science, 6, 134–136. doi:10.1177/174569161140023.

    Article  Google Scholar 

  • Valla, J. M., & Ceci, S. J. (2014). Breadth-based models of women’s underrepresentation in STEM fields: an integrative commentary on Schmidt (2011) and Nye et al. (2012). Perspectives on Psychological Science, 9, 219–224. doi:10.1177/1745691614522067.

    Article  Google Scholar 

  • Voyer, D. (2011). Time limits and gender differences on paper-and-pencil tests of mental rotation: a meta-analysis. Psychonomic Bulletin & Review, 18, 267–277. doi:10.3758/s13423-010-0042-0.

    Article  Google Scholar 

  • Voyer, D., & Voyer, S. D. (2014). Gender differences in scholastic achievement: a meta-analysis. Psychological Bulletin, 140, 1174–1204. doi:10.1037/a0036620.

    Article  Google Scholar 

  • Voyer, D., Postma, A., Brake, B., & Imperato-McGinley, J. (2007). Gender differences in object location memory: a meta-analysis. Psychonomic Bulletin & Review, 14, 23–38. doi:10.3758/BF03194024.

    Article  Google Scholar 

  • Wai, J., Lubinski, D., Benbow, C. P., & Steiger, J. H. (2010). Accomplishment in science, technology, engineering, and mathematics (STEM) and its relation to STEM educational dose: a 25-year longitudinal study. Journal of Educational Psychology, 102, 860–871. doi:10.1037/a0019454.

    Article  Google Scholar 

  • Wai, J., Putallaz, M., & Makel, M. C. (2012). Studying intellectual outliers: Are there sex differences, and are the smart getting smarter? Current Directions in Psychological Science, 21, 382–390. doi:10.1177/0963721412455052.

  • Wang, M. T. (2012). Educational and career interests in math: a longitudinal examination of the links between perceived classroom environment, motivational beliefs, and interests. Developmental Psychology, 48, 1643–1657. doi:10.1037/a0027247.

    Article  Google Scholar 

  • Wang, M. T., & Degol, J. L. (2014a). Motivational pathways to STEM career choices: using expectancy-value perspective to understand individual and gender differences in STEM fields. Developmental Review, 33, 304–340. doi:10.1016/j.dr.2013.08.001.

    Article  Google Scholar 

  • Wang, M. T., & Degol, J. L. (2014b). Staying engaged: knowledge and research needs in student engagement. Child Development Perspectives, 8, 137–143. doi:10.1111/cdep.12073.

    Article  Google Scholar 

  • Wang, M. T., & Degol, J. L. (2015). School climate: a review of the definition, measurement, and impact on student outcomes. Educational Psychology Review. doi:10.1007/s10648-015-9319-1.

    Google Scholar 

  • Wang, M. T., Degol, J. L., & Ye, F. (2015). Math achievement is important, but task values are critical too: Examining the intellectual and motivational factors leading to gender disparities in STEM careers. Frontiers in Psychology, 6, 1–9. doi:10.3389/fpsyq.2015.00036.

  • Wang, M. T., Eccles, J. S., & Kenny, S. (2013). Not lack of ability but more choice: individual and gender differences in STEM career choice. Psychological Science, 24, 770–775. doi:10.1177/0956797612458937.

    Article  Google Scholar 

  • Weisgram, E. S., & Bigler, R. S. (2006). Girls and science careers: the role of altruistic values and attitudes about scientific tasks. Journal of Applied Developmental Psychology, 27, 326–348. doi:10.1016/j.appdev.2006.04.004.

    Article  Google Scholar 

  • Weisgram, E. S., & Bigler, R. S. (2007). Effects of learning about gender discrimination on adolescent girls’ attitudes toward and interest in science. Psychology of Women Quarterly, 31, 262–269. doi:10.1111/j.1471-6402.2007.00369.x.

    Article  Google Scholar 

  • Williams, W. M., & Ceci, S. J. (2012). When scientists choose motherhood: a single factor goes a long way in explaining the dearth of women in math-intensive fields. How can we address it? American Scientist, 100, 138–145. doi:10.1511/2012.95.138.

    Article  Google Scholar 

  • Wolters, C. A. (2004). Advancing achievement goal theory: using goal structures and goal orientations to predict students’ motivation, cognition, and achievement. Journal of Educational Psychology, 96, 236–250. doi:10.1037/0022-0663.96.2.236.

    Article  Google Scholar 

  • Wong, W. I., Pasterski, V., Hindmarsh, P. C., Geffner, M. E., & Hines, M. (2012). Are there parental socialization effects on the sex-typed behavior of individuals with congenital adrenal hyperplasia? Archives of Sexual Behavior, 42, 381–391. doi:10.1007/s10508-012-9997-4.

    Article  Google Scholar 

  • Wood, W., & Eagly, A. H. (2002). A cross-cultural analysis of the behavior of women and men: implications for the origins of sex differences. Psychological Bulletin, 128, 699–727. doi:10.1037//0033-2909.128.5.699.

    Article  Google Scholar 

  • Yeager, D. S., & Dweck, C. S. (2012). Mindsets that promote resilience: when students believe that personal characteristics can be developed. Educational Psychologist, 47, 302–314. doi:10.1080/00461520.2012.722805.

    Article  Google Scholar 

Download references

Acknowledgments

This project was supported by Grant DRL1315943 from the National Science Foundation and Grant HD HD074731-01 from the Eunice Kennedy Shriver National Institute of Child Health and Development (NICHD).

Author information

Authors and Affiliations

  1. University of Pittsburgh, 230 South Bouquet Street, Pittsburgh, PA, 15260, USA

    Ming-Te Wang & Jessica L. Degol

  2. Penn State Altoona, 3000 Ivyside Park, Altoona, PA, 16601, USA

    Jessica L. Degol

Authors
  1. Ming-Te Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jessica L. Degol
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ming-Te Wang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, MT., Degol, J.L. Gender Gap in Science, Technology, Engineering, and Mathematics (STEM): Current Knowledge, Implications for Practice, Policy, and Future Directions. Educ Psychol Rev 29, 119–140 (2017). https://doi.org/10.1007/s10648-015-9355-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10648-015-9355-x

Keywords

Search

Navigation