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Abstract
The digital gaming industry has been undergoing expansion, and its further development necessitates the education and inclusion of a diverse and competent workforce, including engineers. The labor market shows a significant gender imbalance in favor of men in this field. The aim of the research is to identify the existence of stereotypical gender differences and behaviors in learning digital games programming, in order to reduce, eliminate, or reshape their effect during the educational process. The article identifies and presents a dual model of the stereotype threat and self-stereotyping, which significantly negatively affects the motivation of female students to pursue education and careers in the field of digital games programming. The research involved 44 information technology students at the Faculty of Technical Sciences in Čačak. The results confirmed the existence of gender stereotypes and highlighted the need to adapt teaching practices and activities to effectively eliminate these negative effects.
References
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Wheeler, S. C., & Petty, R. E. (2001). The effects of stereotype activation on behavior: A review of possible mechanisms. Psychological Bulletin, 127(6), 797-826. https://doi.org/10.1037//0033-2909.127.6.797
Aleksić, V. (2020). iTV: Exposure Risks?. Advanced Technologies and Standards for Interactive Educational Television: Emerging Research and Opportunities, 134-139. Hershey, PA: IGI Global. https://doi.org/10.4018/978-1-7998-0253-2.ch006
Archer, L., DeWitt, J., Osborne, J., Dillon, J., Willis, B., & Wong, B. (2010). “Doing” science versus “being” a scientist: Examining 10/11‐year‐old schoolchildren’s constructions of science through the lens of identity. Science Education, 94(4), 617–639. Portico. https://doi.org/10.1002/sce.20399
Beilock, S. L., Rydell, R. J., & McConnell, A. R. (2007). Stereotype threat and working memory: Mechanisms, alleviation, and spillover. Journal of Experimental Psychology: General, 136(2), 256-276. https://doi.org/10.1037/0096-3445.136.2.256
Cimpian, A., & Leslie, S.-J. (2017). The Brilliance Trap. Scientific American, 317(3), 60–65. https://doi.org/10.1038/scientificamerican0917-60
Coffman, K. B. (2014). Evidence on Self-Stereotyping and the Contribution of Ideas. The Quarterly Journal of Economics, 129(4), 1625-1660. https://doi.org/10.1093/qje/qju023
Fogliati, V. J., & Bussey, K. (2013). Stereotype Threat Reduces Motivation to Improve. Psychology of Women Quarterly, 37(3), 310-324. https://doi.org/10.1177/0361684313480045
Gann-Bociek, M., & Harvey, R. D. (2020). Gender Stereotypes. Stereotypes, 175-193. https://doi.org/10.5040/9798216018902.ch-010
Liu, S., Liu, P., Wang, M., & Zhang, B. (2021). Effectiveness of stereotype threat interventions: A meta-analytic review. Journal of Applied Psychology, 106(6), 921-949. https://doi.org/10.1037/apl0000770
Luong, K. T., & Knobloch-Westerwick, S. (2016). Can the Media Help Women Be Better at Math? Stereotype Threat, Selective Exposure, Media Effects, and Women’s Math Performance. Human Communication Research, 43(2), 193-213. https://doi.org/10.1111/hcre.12101
Makarova, E., Aeschlimann, B., & Herzog, W. (2019). The Gender Gap in STEM Fields: The Impact of the Gender Stereotype of Math and Science on Secondary Students’ Career Aspirations. Frontiers in Education, 4. https://doi.org/10.3389/feduc.2019.00060
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). https://doi.org/10.1073/pnas.2100030118
Qazi, A., Hasan, N., Abayomi-Alli, O., Hardaker, G., Scherer, R., Sarker, Y., Kumar Paul, S., & Maitama, J. Z. (2021). Gender differences in information and communication technology use & skills: a systematic review and meta-analysis. Education and Information Technologies, 27(3), 4225-4258. https://doi.org/10.1007/s10639-021-10775-x
Ramírez-Uclés, I. M., & Ramírez-Uclés, R. (2020). Gender Differences in Visuospatial Abilities and Complex Mathematical Problem Solving. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.00191
Seitchik, A. E., & Harkins, S. G. (2015). Stereotype threat, mental arithmetic, and the mere effort account. Journal of Experimental Social Psychology, 61, 19-30. https://doi.org/10.1016/j.jesp.2015.06.006
Spieler, B., & Slany, W. (2019). Game Development-Based Learning Experience: Gender Differences in Game Design. In Proceedings of the 12th European Conference on Game Based Learning, 4-5 October, Sophia Antipolis, France, 616-625. ISBN: 978-1-911218-99-9
Stewart, C. A. (2021). Underrepresentation of Women STEM Leaders: Twelve Women on Different Journeys Using Their Voices to Shape the World through Science. European Journal of STEM Education, 6(1), 16. https://doi.org/10.20897/ejsteme/11387
Sweller, J. (2019). Cognitive load theory. Advances in Cognitive Load Theory (pp. 1-12). Routledge. https://doi.org/10.4324/9780429283895-1
Thalmann, M., Souza, A. S., & Oberauer, K. (2019). How does chunking help working memory? Journal of Experimental Psychology: Learning, Memory, and Cognition, 45(1), 37-55. https://doi.org/10.1037/xlm0000578
Ullmann, S. (2022). Gender bias in machine translation systems. In Artificial Intelligence and Its Discontents: Critiques from the Social Sciences and Humanities (pp. 123-144). Cham: Springer International Publishing.
United Nations Women (2023). Progress on the Sustainable Development Goals: The Gender Snapshot 2023. Progress on the Sustainable Development Goals. https://doi.org/10.18356/9789210029063
Wheeler, S. C., & Petty, R. E. (2001). The effects of stereotype activation on behavior: A review of possible mechanisms. Psychological Bulletin, 127(6), 797-826. https://doi.org/10.1037//0033-2909.127.6.797
