Do Stereotypical vs. Counter-stereotypical Role Models Affect Teacher Candidates’ Stereotypes and Attitudes toward Teaching Computer Science?

https://doi.org/10.21585/ijcses.v6i2.174

Authors

Keywords:

stereotypes, role models, teacher candidates, attitudes, computer science

Abstract

Computer Science (CS) stereotypes promote the mindset that nerdy White males who have a high IQ and are technology enthusiasts are the ones to succeed in the field, leading to gender and racial disparities. This quasi-experimental study investigated if exposing teacher candidates to a stereotypical vs. counter-stereotypical CS role model affects their stereotypes and attitudes toward teaching CS. Participants exposed to a counter-stereotypical role model reported a statistically significant decrease in stereotypes about social skills, and slightly weaker stereotypes about appearance, cognitive skills, and work preferences. Participants exposed to a stereotypical role model reported no changes in stereotypes. Participants in both groups showed increasingly positive attitudes toward teaching CS. Implications for CS teacher education are discussed.

Downloads

Download data is not yet available.

Author Biographies

Lucas Vasconcelos, University of South Carolina

Lucas Vasconcelos is an Assistant Professor in the Learning Design and Technologies program at the University of South Carolina. His research agenda seeks to broaden participation of minorities in computer science and STEM fields through technology-enhanced learning experiences. Specifically, his scholarly efforts revolve around computer science education, stereotypes, block-based coding, educational robotics, scientific modeling, and debugging.

Fatih Ari, University of South Carolina

Fatih Ari is an Assistant Professor in the Learning Design and Technologies program at the University of South Carolina. He earned his Ed.D. in Instructional Technology with a minor in Management Information Systems, and his M.S. in Software Engineering from Texas Tech University. His research interests include design and development of online learning environments, feedback design and delivery, multimedia learning, and computer science education.

Ismahan Arslan-Ari, University of South Carolina

Ismahan Arslan-Ari is an Associate Professor in the Learning Design and Technologies program at the University of South Carolina. She is also the director of the South Carolina Center for Assistive Technology and Educational Research. Her research mainly focuses on multimedia learning, human computer interaction, the use of assistive technologies and online learning.

Lily Lamb, University of South Carolina

Lily Lamb is an undergraduate honors student majoring in Computer Engineering at the University of South Carolina.

References

Asgari, S., Dasgupta, N., & Stout, J. G. (2012). When do counterstereotypic ingroup members inspire versus deflate? The effect of successful professional women on young women’s leadership self-concept. Personality and Social Psychology Bulletin, 38(3), 370–383. https://doi.org/10.1177/0146167211431968 DOI: https://doi.org/10.1177/0146167211431968

Authors (2022a).

Authors (2022b).

Belland, B. R., Kim, C., & Hannafin, M. J. (2013). A framework for designing scaffolds that improve motivation and cognition. Educational Psychologist, 48(4), 243-270. https://doi.org/10.1080/00461520.2013.838920 DOI: https://doi.org/10.1080/00461520.2013.838920

Berg, T., Sharpe, A., & Aitkin, E. (2018). Females in computing: Understanding stereotypes through collaborative picturing. Computers & Education, 126, 105–114. https://doi.org/10.1016/j.compedu.2018.07.007

Beyer, S. (2014). Why are women underrepresented in Computer Science? Gender differences in stereotypes, self-efficacy, values, and interests and predictors of future CS course-taking and grades. Computer Science Education, 24(2–3), 153–192. https://doi.org/10.1080/08993408.2014.963363 DOI: https://doi.org/10.1080/08993408.2014.963363

Bian, L., Leslie, S., & Cimpian, A. (2017). Gender stereotypes about intellectual ability emerge early and influence children’s interests. Science, 355(6323), 389–391. https://doi.org/10.1126/science.aah6524 DOI: https://doi.org/10.1126/science.aah6524

Block, J. H. (1973). Conceptions of sex role: Some cross-cultural and longitudinal perspectives. American Psychologist, 28(6), 512–526. https://doi.org/10.1037/h0035094 DOI: https://doi.org/10.1037/h0035094

Buckley, C., Farrell, L., & Tyndall, I. (2021). Brief stories of successful female role models in science help counter gender stereotypes regarding intellectual ability among young girls: A pilot study. Early Education and Development. https://doi.org/10.1080/10409289.2021.1928444

Bureau of Labor Statistics, U.S. Department of Labor. (2021, April 15). Occupational outlook handbook: Computer and information technology occupations. U.S. Bureau of Labor Statistics. https://www.bls.gov/ooh/

Cheryan, S., Drury, B. J., & Vichayapai, M. (2012). Enduring influence of stereotypical computer science role models on women’s academic aspirations. Psychology of Women Quarterly, 37(1), 72–79. https://doi.org/10.1177/0361684312459328 DOI: https://doi.org/10.1177/0361684312459328

Cheryan, S., Master, A., & Meltzoff, A. N. (2015). Cultural stereotypes as gatekeepers: Increasing girls’ interest in computer science and engineering by diversifying stereotypes. Frontiers in Psychology, 6, 1–8. https://doi.org/10.3389/fpsyg.2015.00049 DOI: https://doi.org/10.3389/fpsyg.2015.00049

Cheryan, S., Meltzoff, A. N., & Kim, S. (2011). Classrooms matter: The design of virtual classrooms influences gender disparities in computer science classes. Computers & Education, 57(2), 1825–1835. https://doi.org/10.1016/j.compedu.2011.02.004 DOI: https://doi.org/10.1016/j.compedu.2011.02.004

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(6), 1045–1060. https://doi.org/10.1037/a0016239 DOI: https://doi.org/10.1037/a0016239

Cheryan, S., Plaut, V. C., Handron, C., & Hudson, L. (2013). The stereotypical computer scientist: Gendered media representations as a barrier to inclusion for women. Sex Roles, 69, 58–71. https://doi.org/10.1007/s11199-013-0296-x DOI: https://doi.org/10.1007/s11199-013-0296-x

Cheryan, S., Siy, J. O., Vichayapai, M., Drury, B. J., & Kim, S. (2011). Do female and male role models who embody STEM stereotypes hinder women’s anticipated success in STEM? Social Psychological and Personality Science, 2(6), 656–664. https://doi.org/10.1177/1948550611405218 DOI: https://doi.org/10.1177/1948550611405218

de Wit, S., Hermans, F., & Aivaloglou, E. (2021). Children’s implicit and explicit stereotypes on the gender, social skills, and interests of a computer scientist. Proceedings of the 17th ACM Conference on International Computing Education Research, 239–251. https://doi.org/10.1145/3446871.3469753

Drury, B. J., Siy, J. O., & Cheryan, S. (2011). When do female role models benefit women? The importance of differentiating recruitment from retention in STEM. Psychological Inquiry, 22(4) 265–269. https://doi.org/10.1080/1047840X.2011.620935 DOI: https://doi.org/10.1080/1047840X.2011.620935

Eagly, A. H., & Karau, S. J. (2002). Role congruity theory of prejudice toward female leaders. Psychological Review, 109(3), 573–598. https://doi.org/10.1037//0033-295X.109.3.573 DOI: https://doi.org/10.1037/0033-295X.109.3.573

Eagly, A. H., Wood, W., & Diekman, A. B. (2000). Social role thoery of sex differences and similarities: A current appraisal. In T. Eckes & H. M. Trautner (Eds.), The developmental social psychology of gender (pp. 123–174). Erlbaum.

Farrell, L., Nearchou, F., & McHugh, L. (2020). Examining the effectiveness of brief interventions to strengthen a positive implicit relation between women and STEM across two timepoints. Social Psychology of Education, 23, 1203-1231. https://doi.org/10.1007/s11218-020-09576-w

Field, A. (2017). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications.

Fraenkel, J., & Wallen, N. (2009). How to design and evaluate research in education (7th ed.). Boston: McGraw-Hill.

Gilbert, P. (2015). The role of role models: How does identification with STEM role models impact women’s implicit STEM stereotypes and STEM outcomes? [Unpublished doctoral dissertation/master’s thesis]. Tulate University.

Good, J. J., Woodzicka, J. A., & Wingfield, L. C. (2010). The effects of gender stereotypic and counter-stereotypic textbook images on science performance. The Journal of Social Psychology, 150(2), 132–147. DOI: https://doi.org/10.1080/00224540903366552

Gopalan, M., Rosinger, K., & Ahn, J. B. (2020). Use of quasi-experimental research designs in education research: Growth, promise, and challenges. Review of Research in Education, 44(1), 218–243. https://doi.org/10.3102/0091732X20903302

Graham, S., & Latulipe, C. (2003). CS girls rock: Sparking interest in computer science and debunking the stereotypes. 322–326. DOI: https://doi.org/10.1145/792548.611998

Ireland, D. T., Freeman, K. E., Winston-Proctor, C. E., DeLaine, K. D., Lowe, S. M., & Woodson, K. M. (2018). (Un)hidden figures: A synthesis of research examining the intersectional experiences of black women and girls in STEM education. Review of Research in Education, 42(1), 226-254. https://doi.org/10.3102/0091732X18759072 DOI: https://doi.org/10.3102/0091732X18759072

Kanahara, S. (2006). A review of the definitions of stereotype and a proposal for a progressional model. Individual Differences Research, 4(5), 306–321.

Master, A., Cheryan, S., & Meltzoff, A. N. (2016). Computing whether she belongs: Stereotypes undermine girls’ interest and sense of belonging in computer science. Journal of Educational Psychology, 108(3), 424–437. http://dx.doi.org/10.1037/edu0000061 DOI: https://doi.org/10.1037/edu0000061

Master, A., Meltzoff, A. N., & Cheryan, S. (2021). Gender stereotypes about interests start early and cause gender disparities in computer science and engineering. Proceedings of the National Academy of Sciences, 118(48), 1–7. https://doi.org/10.1073/pnas.2100030118

Mayer, R. E. (2005). Cognitive theory of multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 31–48). Cambridge University Press. https://doi.org/10.1017/CBO9780511816819.004 DOI: https://doi.org/10.1017/CBO9780511816819.004

Mayer, R. E., & Pilegard, C. (2014). Principles for managing essential processing in multimedia learning: Segmenting, pre-training, and modality principles. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 316–344). Cambridge University Press. https://doi.org/10.1017/CBO9781139547369.016 DOI: https://doi.org/10.1017/CBO9781139547369.016

National Science Foundation. (2019). Women, minorities, and persons with disabilities in science and engineering: 2019(Special Report NSF 19-304). https://www.nsf.gov/statistics/wmpd

Nolan, S. A., & Heinzen, T. E. (2012). Statistics for the behavioral sciences (2nd ed.). Worth Publishers.

Olsson, M., & Martiny, S. E. (2018). Does exposure to counterstereotypical role models influence girls’ and women’s gender stereotypes and career choices? A review of social psychological research. Frontiers in Psychology, 9, 1–15. https://doi.org/10.3389/fpsyg.2018.02264

Pantic, K., Clarke-Midura, J., Poole, F., Roller, J., & Allan, V. (2018). Drawing a computer scientist: Stereotypical representations or lack of awareness? Computer Science Education, 28(3), 232–254. https://doi.org/10.1080/08993408.2018.1533780

Papadakis, S. (2018). Gender stereotypes in Greek computer science school textbooks. International Journal of Teaching and Case Studies, 9(1), 48–71. https://doi.org/10.1504/IJTCS.2018.10011123 DOI: https://doi.org/10.1504/IJTCS.2018.10011123

Riegle-Crumb, C., Moore, C., & Buontempo, J. (2017). Shifting STEM stereotypes? Considering the role of peer and teacher gender. Journal of Research on Adolescence, 27(3), 492–505. https://doi.org/10.1111/jora.12289 DOI: https://doi.org/10.1111/jora.12289

Rodriguez, S. L., & Lehman, K. (2017). Developing the next generation of diverse computer scientists: the need for enhanced, intersectional computing identity theory. Computer Science Education, 27(3-4), 229-247. https://doi.org/10.1080/08993408.2018.1457899 DOI: https://doi.org/10.1080/08993408.2018.1457899

Rosenkrantz, P., Vogel, S., Bee, H., Broverman, I., & Broverman, D. M. (1968). Sex-role stereotypes and self-concepts in college students. Journal of Consulting and Clinical Psychology, 32(3), 287–295. https://doi.org/10.1037/h0025909 DOI: https://doi.org/10.1037/h0025909

Shapiro, J. R., & Williams, A. M. (2012). The role of stereotype threats in undermining girls’ and women’s performance and interest in STEM fields. Sex Roles, 66, 175–183. https://doi.org/10.1007/s11199-011-0051-0 DOI: https://doi.org/10.1007/s11199-011-0051-0

Shin, J. E. L., Levy, S. R., & London, B. (2016). Effects of role model exposure on STEM and non-STEM student engagement. Journal of Applied Social Psychology, 46(7), 410–427. https://doi.org/10.1111/jasp.12371 DOI: https://doi.org/10.1111/jasp.12371

Siegel, S. (1956). Non-parametric statistics for the behavioral sciences. McGraw-Hill.

Sills, D. L. (1968). International encyclopedia of the social sciences. The Macmillan Company & The Free Press.

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), 255–270. https://doi.org/10.1037/a0021385 DOI: https://doi.org/10.1037/a0021385

Taylor, S. E., Peplau, L. A., & Sears, D. O. (1994). Social psychology. Prentice Hall.

Trauth, E. M., Cain, C. C., Joshi, K. D., Kvasny, L., & Booth, K. M. (2016). The influence of gender-ethnic intersectionality on gender stereotypes about IT skills and knowledge. The Data Base for Advances in Information Systems, 47(3), 9-39. https://doi.org/10.1145/2980783.2980785 DOI: https://doi.org/10.1145/2980783.2980785

Vandenberg, J., Rachmatullah, A., Lynch, C., Boyer, K. E., & Wiebe, E. (2021). Interaction effects of race and gender in elementary CS attitudes: A validation and cross-sectional study. International Journal of Child-Computer Interaction, 29, 1-11. https://doi.org/10.1016/j.ijcci.2021.100293

Varma, R. (2020). Women in computing education: A Western or a global problem? Lessons from India. In C. Frieze & J. L. Quesenberry (Eds.), Cracking the digital ceiling: Women in computing around the world (pp. 299–310). Cambridge University Press. https://doi.org/10.1017/9781108609081.018

Veletsianos, G. (2010). Contextually relevant pedagogical agents: Visual appearance, stereotypes, and first impressions and their impact on learning. Computers & Education, 55(2), 576-585. https://doi.org/10.1016/j.compedu.2010.02.019 DOI: https://doi.org/10.1016/j.compedu.2010.02.019

Wood, W., & Eagly, A. H. (2012). Biosocial construction of sex differences and similarities in behavior. In J. M. Olson & M. P. Zanna (Eds.), Advances in Experimental Social Psychology (Vol. 46, pp. 55–123). Academic Press. https://doi.org/10.1016/B978-0-12-394281-4.00002-7 DOI: https://doi.org/10.1016/B978-0-12-394281-4.00002-7

Yadav, A., Zhou, N., Mayfield, C., Hambrusch, S., & Korb, J. T. (2011). Introducing computational thinking in education courses. Proceedings of the 42nd ACM Technical Symposium on Computer Science Education, 465–470. http://dl.acm.org/citation.cfm?id=1953297 DOI: https://doi.org/10.1145/1953163.1953297

Published

2023-10-19

How to Cite

Vasconcelos, L., Ari, F., Arslan-Ari, I., & Lamb, L. (2023). Do Stereotypical vs. Counter-stereotypical Role Models Affect Teacher Candidates’ Stereotypes and Attitudes toward Teaching Computer Science?. International Journal of Computer Science Education in Schools, 6(2). https://doi.org/10.21585/ijcses.v6i2.174

Issue

Vol. 6 No. 2 (2023): International Journal of Computer Science Education in Schools

Section

Full Papers
Copyright & Licensing

Copyright (c) 2023 Lucas Vasconcelos, Fatih Ari, Ismahan Arslan-Ari, Lily Lamb

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
    2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
    3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).