Authors: Eleanor Beck, Cora Sargeant and Sarah Wright
Published: 2023
Publication: International Journal of Gender, Science and Technology

There is an underrepresentation of women working in Science, Technology, Engineering and Mathematics (STEM) industries. Initiatives to encourage greater diversity in STEM have been less successful in computer science. This research investigates whether identification with gender stereotypes (defined as the extent to which one identifies with stereotypical masculine or feminine traits) and other factors predict enrolment interest in computer science and whether stereotypical cues impact on these relationships. British secondary school students were shown either a stereotypical or a non-stereotypical computer science classroom and completed measures assessing their identification with gender stereotypes, enrolment interest, belonging, stereotype threat, self-efficacy and utility value. Femininity significantly predicted lower enrolment interest and this relationship appeared to be mediated by stereotype threat. This study extends previous research by showing that young peoples’ identification with gender stereotypes predicts enrolment interest to some degree. We highlight the need to challenge persistent stereotypes regarding who best ‘fits’ computer science.

Beck, E., Sargeant, C. & Wright, S. (2023) Exploring the impact of gender identity and stereotypes on secondary pupils’ computer science enrolment interest (2023). International Journal of Gender, Science and Technology, 15(1), 48–71.

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