Skip to main content
Log in

The Stereotypical Computer Scientist: Gendered Media Representations as a Barrier to Inclusion for Women

  • Original Article
  • Published:
Sex Roles Aims and scope Submit manuscript

Abstract

The present research examines undergraduates’ stereotypes of the people in computer science, and whether changing these stereotypes using the media can influence women’s interest in computer science. In Study 1, college students at two U.S. West Coast universities (N = 293) provided descriptions of computer science majors. Coding these descriptions revealed that computer scientists were perceived as having traits that are incompatible with the female gender role, such as lacking interpersonal skills and being singularly focused on computers. In Study 2, college students at two U.S. West Coast universities (N = 54) read fabricated newspaper articles about computer scientists that either described them as fitting the current stereotypes or no longer fitting these stereotypes. Women who read that computer scientists no longer fit the stereotypes expressed more interest in computer science than those who read that computer scientists fit the stereotypes. In contrast, men’s interest in computer science did not differ across articles. Taken together, these studies suggest that stereotypes of academic fields influence who chooses to participate in these fields, and that recruiting efforts to draw more women into computer science would benefit from media efforts that alter how computer scientists are depicted.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  • Allport, G. W. (1954). The nature of prejudice. England, Oxford: Addison-Wesley.

    Google Scholar 

  • Barker, L. J., & Aspray, W. (2006). The state of research on girls and IT. In J. M. Cohoon & W. Aspray (Eds.), Women and information technology: Research on underrepresentation (pp. 3–54). Cambridge: MIT Press.

    Google Scholar 

  • Barman, C. (1999). Students' views about scientists and school science: Engaging K-8 teachers in a national study. Journal of Science Teacher Education, 10, 43–54. doi:10.1023/1009424713416.

    Article  Google Scholar 

  • Beilock, S. L., Gunderson, E. A., Ramirez, G., & Levine, S. C. (2010). Female teachers’ math anxiety affects girls’ math achievement. Proceedings of the National Academy of Sciences, 107, 1860–1863. doi:10.1073/pnas.0910967107.

    Article  Google Scholar 

  • Beyer, S. (1999). Gender differences in the accuracy of grade expectancies and evaluations. Sex Roles, 41, 279–296. doi:10.1023/A:1018864803330.

    Article  Google Scholar 

  • Beyer, S., Rynes, K., Perrault, J., Hay, K., & Haller, S. (2003). Gender differences in computer science students. Paper presented at the Proceedings of the Thirty-fourth SIGCSE Technical Symposium on Computer Science Education, New York, NY. doi:10.1145/611892.611930

  • Borg, A. (1999). What draws women to and keeps women in computing? The Annuals of the New York Academy of Sciences, 869, 102–105. doi:10.1111/j.1749-6632.1999.tb08362.x.

    Article  Google Scholar 

  • Buldu, M. (2006). Young children's perceptions of scientists: A preliminary study. Educational Research, 48, 121–132. doi:10.1080/00131880500498602.

    Article  Google Scholar 

  • Bureau of Labor Statistics. (2005). Occupational Outlook Handbook, 2004–05 Edition: U.S. Department of Labor.

  • 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  PubMed  Google Scholar 

  • Cejka, M. A., & Eagly, A. H. (1999). Gender-stereotypic images of occupations correspond to the sex segregation of employment. Personality and Social Psychology Bulletin, 25, 413–423. doi:10.1177/0146167299025004002.

    Article  Google Scholar 

  • Chambers, D. W. (1983). Stereotypic images of the scientist: The draw a scientist test. Science Education, 67, 255–265. doi:10.1002/sce.3730670213.

    Article  Google Scholar 

  • Charles, M., & Bradley, K. (2006). A matter of degrees: Female underrepresentation in computer science programs cross-nationally. In J. M. Cohoon & W. Aspray (Eds.), Women and information technology: Research on underrepresentation (pp. 183–203). Cambridge: MIT Press.

    Google Scholar 

  • Cherney, I. D., & London, K. (2006). Gender-linked differences in the toys, television shows, computer games, and outdoor activities of 5-to 13-year-old children. Sex Roles, 54, 717–726. doi:10.1007/s11199-006-9037-8.

    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  PubMed  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  PubMed  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 in Education, 57, 1825–1835. doi:10.1016/j.compedu.2011.02.004.

    Article  Google Scholar 

  • Cheryan, S., Siy, J. O., Vichayapai, M., Drury, B., & 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 

  • Clarke, V. A., & Teague, G. J. (1996). Characterizations of computing careers: Students and professionals disagree. Computers in Education, 26, 241–246. doi:10.1016/0360-1315(96)00004-8.

    Article  Google Scholar 

  • Creamer, E., Lee, S., & Meszaros, P. (2007). Predicting women’s interest in and choice of a career in information technology: A statistical model. In C. J. Burger, E. G. Creamer, & P. S. Meszaros (Eds.), Reconfiguring the firewall: Recruiting women to information technology across cultures and continents (pp. 15–38). Wellesley: AK Peters Publishing.

    Chapter  Google Scholar 

  • Davies, P. G., Spencer, S. J., Quinn, D. M., & Gerhardstein, R. (2002). Consuming images: How television commercials that elicit stereotype threat can restrain women academically and professionally. Personality and Social Psychology Bulletin, 28, 1615–1628. doi:10.1177/014616702237644.

    Article  Google Scholar 

  • de Cohen, C. C., & Deterding, N. (2009). Widening the net: National estimates of gender disparities in engineering. Journal of Engineering Education, 211–226.

  • Deaux, K., & Lewis, L. L. (1984). Structure of gender stereotypes: Interrelationships among components and gender label. Journal of Personality and Social Psychology, 46, 991–1004. doi:10.1037/0022-3514.46.5.991.

    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  PubMed  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, 87, 796–816. doi:10.1037/a0025199.

    Google Scholar 

  • Dryburgh, H. (2000). Underrepresentation of girls and women in computer science: Classification of 1990s research. Journal of Educational Computing Research, 23, 181–202. doi:10.2190/8RYV-9JWH-XQMB-QF41.

    Article  Google Scholar 

  • Eagly, A. H. (1987). Sex differences in social behavior: A social-role interpretation. Hillsdale, NJ, England: Lawrence Erlbaum Associates, Inc.

    Google Scholar 

  • Eagly, A. H., & Steffen, V. J. (1984). Gender stereotypes stem from the distribution of women and men into social roles. Journal of Personality and Social Psychology, 46, 735–754. doi:10.1037/0022-3514.46.4.735.

    Article  Google Scholar 

  • El Nasser, H. (2012, April 12). Geek chic: 'Brogrammer?' Now that's hot, USA Today. Retrieved from http://www.usatoday.com/tech/news/story/2012-04-10/techie-geeks-cool/54160750/1

  • Fennema, E., Peterson, P. L., Carpenter, T. P., & Lubinski, C. A. (1990). Teachers’ attributions and beliefs about girls, boys, and mathematics. Educational Studies in Mathematics, 21, 55–69. doi:10.1007/BF00311015.

    Article  Google Scholar 

  • Finson, K. D. (2002). Drawing a scientist: What we do and do not know after fifty years of drawings. School Science and Mathematics, 102, 335–345. doi:10.1111/j.1949-8594.2002.tb18217.x.

    Article  Google Scholar 

  • Finson, K. D. (2003). Applicability of the DAST-C to the images of scientists drawn by students of different racial groups. Journal of Elementary Science Education, 15, 15–26. doi:10.1007/BF03174741.

    Article  Google Scholar 

  • Flick, L. (1990). Scientists in residence program improving children’s image of science and scientists. School Science and Mathematics, 90, 204–214. doi:10.1111/j.1949-8594.1990.tb15536.x.

    Article  Google Scholar 

  • Fort, D. C., & Varney, H. L. (1989). How students see scientists: Mostly male, mostly White, and mostly benevolent. Science and Children, 26, 8–13.

    Google Scholar 

  • Fryberg, S., Markus, H. R., Oyserman, D., & Stone, J. M. (2008). Of warrior chiefs and Indian princesses: The psychological consequences of American Indian mascots on American Indians. Basic and Applied Social Psychology, 30, 208–218. doi:10.1080/01973530802375003

    Google Scholar 

  • Hannover, B., & Kessels, U. (2004). Self-to-prototype matching as a strategy for making academic choices. Why high school students do not like math and science. Learning and Instruction, 14, 51–67. doi:10.1080/01973530802375003.

    Article  Google Scholar 

  • Harackiewicz, J. M., Rozek, C. S., Hulleman, C. S., & Hyde, J. S. (2012). Helping parents to motivate adolescents in mathematics and science: An experimental test. Psychological Science, 23, 899–906. doi:10.1177/0956797611435530.

    Article  PubMed  Google Scholar 

  • Hess, R. D., & Miura, I. T. (1985). Gender differences in enrollment in computer camps and classes. Sex Roles, 13, 193–203. doi:10.1007/BF00287910.

    Article  Google Scholar 

  • Hong, L., & Page, S. E. (2004). Groups of diverse problem solvers can outperform groups of high-ability problem solvers. Proceedings of the National Academy of Sciences of the United States of America, 101, 16385–16389. doi:10.1037/pnas.0403723101.

    Article  PubMed  Google Scholar 

  • Jacobs, J. E. (1991). Influence of gender stereotypes on parent and child mathematics attitudes. Journal of Educational Psychology, 83, 518–527. doi:10.1037/0022-0663.83.4.518.

    Article  Google Scholar 

  • Katz, D., & Braly, K. (1933). Racial stereotypes of one hundred college students. Journal of Abnormal and Social Psychology, 28, 280–290. doi:10.1037/h0074049.

    Article  Google Scholar 

  • Kendall, L. (1999). Nerd nation: Images of nerds in US popular culture. International Journal of Cultural Studies, 2, 260–283. doi:10.1177/136787799900200206.

    Article  Google Scholar 

  • Kiousis, S. (2001). Public trust or mistrust? perceptions of media credibility in the information age. Mass Communication & Society, 4, 381–403. doi:10.1207/S15327825MCS0404_4.

    Article  Google Scholar 

  • Knight, M., & Cunningham, C. (2004). Draw an Engineer Test (DAET): Development of a tool to investigate students' ideas about engineers and engineering. Paper presented at the American Society for Engineering Education Annual Conference & Exposition, Salt Lake City, Utah.

  • Lang, C. (2007). Twenty-first century Australian women and IT: Exercising the power of choice. Computer Science Education, 17, 215–226. doi:10.1080/08993400701538120.

    Article  Google Scholar 

  • Lang, C., Craig, A., Fisher, J., & Forgasz, H. (2010). Dualisms: What women say about working in ICT. Paper presented at the Australasian Conference on Information Systems 2010 Proceedings, Brisbane, AU.

  • Linde, N. (2011, July 13). Bringing girls into the science-major pipeline. The Chronicle of Higher Education. Retrieved from http://chronicle.com/article/Bringing-Girls-Into-the/128099/

  • Lippa, R. (1998). Gender-related individual differences and the structure of vocational interests: The importance of the people–things dimension. Journal of Personality and Social Psychology, 74, 996–1009. doi:10.1037//0022-3514.74.4.996.

    Article  PubMed  Google Scholar 

  • Lippman, W. (1922). Public opinion. New York: Harcourt Brace.

    Google Scholar 

  • Margolis, J., & Fisher, A. (2002). Unlocking the clubhouse: Women in computing. Cambridge: MIT Press.

    Google Scholar 

  • Master, A., Markman, E. M., & Dweck, C. S. (2012). Thinking in categories or along a continuum: Consequences for children’s social judgments. Child Development, 83, 1145–1163. doi:10.1111/j.1467-8624.2012.01774.x.

    Article  PubMed  Google Scholar 

  • Mead, M., & Metraux, R. (1957). Image of the scientist among high-school students. Science, 126, 384–390. doi:10.1126/science.126.3270.384.

    Article  PubMed  Google Scholar 

  • Mercier, E. M., Barron, B., & O'Connor, K. M. (2006). Images of self and others as computer users: The role of gender and experience. Journal of Computer Assisted Learning, 22, 335–348. doi:10.1111/j.1365-2729.2006.00182.x.

    Article  Google Scholar 

  • Morgan, C., Isaac, J. D., & Sansone, C. (2001). The role of interest in understanding the career choices of female and male college students. Sex Roles, 44, 295–320. doi:10.1023/A:1010929600004.

    Article  Google Scholar 

  • National Science Foundation. (2002). Women, minorities, and persons with disabilities in science and engineering: 2002. Arlington, VA: Division of Science Resources Statistics.

  • National Science Foundation. (2009). TABLE C-4. Bachelor's degrees, by sex and field: 1997–2006. Arlington, VA: Retrieved from http://www.nsf.gov/statistics/wmpd/tables.cfm.

  • Newton, L. D., & Newton, D. P. (1988). Primary children’s conceptions of science and the scientist: Is the impact of a National Curriculum breaking down the stereotype? International Journal of Science Education, 20, 1137–1149. doi:10.1080/0950069980200909.

    Article  Google Scholar 

  • Nosek, B. A., Smyth, F. L., Sriram, N., Lindner, N. M., Devos, 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 Sciences, 106, 10593–10597. doi:10.1073/pnas.0809921106.

    Article  Google Scholar 

  • Oakes, P. J., Haslam, S. A., & Turner, J. C. (1994). Stereotyping and social reality. Malden: Blackwell Publishing.

    Google Scholar 

  • Paluck, E. L. (2010). Peer pressure against prejudice: A high school field experiment examining social network change. Journal of Experimental Social Psychology, 211, 350–358. doi:10.1016/j.jesp.2010.11.017.

    Google Scholar 

  • Park, B., & Judd, C. M. (1990). Measures and models of perceived group variability. Journal of Personality and Social Psychology, 59, 173. doi:10.1037/0022-3514.59.2.173.

    Article  Google Scholar 

  • Pion, G. M., & Lipsey, M. W. (1981). Public attitudes toward science and technology: What have the surveys told us? Public Opinion Quarterly, 45, 303–316. doi:10.1086/268666.

    Article  PubMed  Google Scholar 

  • Plaut, V. C., Garnett, F. G., Buffardi, L. E., & Sanchez-Burks, J. (2011). “What about me?” perceptions of exclusion and whites’ reactions to multiculturalism. Journal of Personality and Social Psychology, 101, 337–353. doi:10.1037/a0022832.

    Article  PubMed  Google Scholar 

  • Plaut, V. C., Cheryan, S., & Garnett, F. G. (in press). New frontiers in diversity research: Theoretical and practical implications. In E. Borgida & J. A. Bargh (Eds.), APA Handbook of Personality and Social Psychology: Vol. 1. Attitudes and Social Cognition. Washington D.C.: APA Books.

  • Pronin, E., Steele, C. M., & Ross, L. (2004). Identity bifurcation in response to stereotype threat: Women and mathematics. Journal of Experimental Social Psychology, 40, 152–168. doi:10.1016/S0022-1031(03)00088-X.

    Article  Google Scholar 

  • Schibeci, R. A. (1986). Images of science and scientists and science education. Science Education, 70, 139–149. doi:10.1002/sce.3730700208.

    Article  Google Scholar 

  • Schibeci, R. A., & Sorensen, I. (1983). Elementary school children’s perceptions of scientists. School Science and Mathematics, 83, 14–20. doi:10.1111/j.1949-8594.1983.tb10087.x.

  • Schott, G., & Selwyn, N. (2000). Examining the “male, antisocial” stereotype of high computer users. Journal of Educational Computing Research, 23, 291–303. doi:10.2190/V98R-5ETX-W9LY-WD3J.

    Article  Google Scholar 

  • Singh, K., Allen, K. R., Scheckler, R., & Darlington, L. (2007). Women in computer-related majors: A critical synthesis of research and theory from 1994 to 2005. Review of Educational Research, 77, 500–533. doi:10.3102/0034654307309919.

    Article  Google Scholar 

  • Steinke, J. (2005). Cultural representations of gender and science. Science Communication, 27, 27–63. doi:10.1177/1075547005278610.

    Article  Google Scholar 

  • Steinke, J., Lapinski, M. K., Crocker, N., Zietsman-Thomas, A., Williams, Y., Evergreen, S. H., et al. (2007). Assessing media influences on middle school–aged children’s perceptions of women in science using the Draw-A-Scientist Test (DAST). Science Communication, 29, 35–64. doi:10.1177/1075547007306508.

    Article  Google Scholar 

  • Stout, J. G., Dasgupta, N., Hunsinger, M., & McManus, M. (2011). STEMing the tide: Using ingroup experts to inoculate women’s self-concept and professional goals in science, technology, engineering, and mathematics (STEM). Journal of Personality and Social Psychology, 100, 255–270. doi:10.1037/a0021385.

    Article  PubMed  Google Scholar 

  • Walton, G., & Cohen, G. (2007). A question of belonging: Race, social fit, and achievement. Journal of Personality and Social Psychology, 92, 82–96. doi:10.1037/0022-3514.92.1.82.

    Article  PubMed  Google Scholar 

  • Williams, M. J., & Eberhardt, J. L. (2008). Biological conceptions of race and the motivation to cross racial boundaries. Journal of Personality and Social Psychology, 94, 1033–1047. doi:10.1037/0022-3514.94.6.1033.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sapna Cheryan.

Appendix

Appendix

Study finds computer science continues to be dominated by ‘geeks’

By Pat Atkins, USA TODAY

The recent dot-com bubble may have burst, but no corresponding shift in the type of students attracted to computer science is occurring in universities across the country.

A recent study by researchers Christine M. Pearson of the University of North Carolina and Mike M. Yang of Temple University found a full third of computer science majors describe themselves as ‘geeks,’ a number similar to the one obtained several years ago.

The stereotypical techno-nerds, with their short-sleeve shirts and pencil protectors in their pockets, are just as easy to come by these days. According to Pearson, it is not difficult to “walk around a campus and pick out the students on their way to the computer science department.”

Anyone can see that this image has profoundly been absorbed into the universal consciousness. The first image of a computer science major that pops into mind is still that of a pasty, willowy student in a dorky shirt, face hidden behind bangs and glasses.

Many image experts admit it: In a word association game, ‘Computer Scientist = Geek’ forever.

To observers, computer science continues to be ruled by geeks. And although the past few years has brought a new level of publicity to the field, the basic expectation of the major as populated by geeks who live and breathe programming endures.

Study finds computer science no longer dominated by ‘geeks’

By Pat Atkins, USA TODAY

The recent dot-com bubble may have burst, but its impact on the type of students attracted to computer science in universities across the country appears to be here to stay.

A recent study by researchers Christine M. Pearson of the University of North Carolina and Mike M. Yang of Temple University found that only a third of computer science majors describe themselves as ‘geeks,’ a significant decline from even just a few years ago.

The stereotypical techno-nerds, with their short-sleeve shirts and pencil protectors in their pockets, are hard to come by these days. In fact, it is not difficult to walk around a campus and see a variety of students on their way to the computer science department.

Anyone can see that this change is slowly being absorbed into the universal consciousness. The first image of a computer science major that pops into mind might no longer be a pasty, willowy student in a dorky shirt, face hidden behind bangs and glasses.

Many image experts admit it: In a word association game, ‘Computer Scientist = Geek’ no longer.

To observers, computer science has undergone a de-geeking. The seemingly less nerdy, more well-rounded, and generally more user-friendly student of late is a trend that many hope will mend the battered image of the computer science major.

Note: Articles were formatted to appear printed off the web.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cheryan, S., Plaut, V.C., Handron, C. et al. The Stereotypical Computer Scientist: Gendered Media Representations as a Barrier to Inclusion for Women. Sex Roles 69, 58–71 (2013). https://doi.org/10.1007/s11199-013-0296-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11199-013-0296-x

Keywords

Navigation