Societal stereotypes depict girls as less interested than boys in computer science and engineering. We demonstrate the existence of these stereotypes among children and adolescents from first to 12th grade and their potential negative consequences for girls’ subsequent participation in these fields. Studies 1 and 2 ( n = 2,277; one preregistered) reveal that children as young as age six (first grade) and adolescents across multiple racial/ethnic and gender intersections (Black, Latinx, Asian, and White girls and boys) endorse stereotypes that girls are less interested than boys in computer science and engineering. The more that individual girls endorse gender-interest stereotypes favoring boys in computer science and engineering, the lower their own interest and sense of belonging in these fields. These gender-interest stereotypes are endorsed even more strongly than gender stereotypes about computer science and engineering abilities. Studies 3 and 4 ( n = 172; both preregistered) experimentally demonstrate that 8- to 9-y-old girls are significantly less interested in an activity marked with a gender stereotype (“girls are less interested in this activity than boys”) compared to an activity with no such stereotype (“girls and boys are equally interested in this activity”). Taken together, both ecologically valid real-world studies (Studies 1 and 2) and controlled preregistered laboratory experiments (Studies 3 and 4) reveal that stereotypes that girls are less interested than boys in computer science and engineering emerge early and may contribute to gender disparities.
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Pink for Princesses, Blue for Superheroes: The Need to Examine Gender Stereotypes in Kid's Products in Search and Recommendations
In this position paper, we argue for the need to investigate if and how gender stereotypes manifest in search and recommender this http URL a starting point, we particularly focus on how these systems may propagate and reinforce gender stereotypes through their results in learning environments, a context where teachers and children in their formative stage regularly interact with these systems. We provide motivating examples supporting our concerns and outline an agenda to support future research addressing the phenomena.
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- Award ID(s):
- 1751278
- NSF-PAR ID:
- 10335669
- Date Published:
- Journal Name:
- KidRec '21: 5th International and Interdisciplinary Perspectives on Children \& Recommender and Information Retrieval Systems (KidRec) Search and Recommendation Technology through the Lens of a Teacher- Co-located with ACM IDC 2021
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Children’s memberships in social groups have profound effects on their motivation. Stereotypes about social groups shape children’s beliefs about what is expected for their group members. These beliefs can influence children’s developing beliefs about themselves (self‐perceptions). In this article, I review research on how gender stereotypes influence children’s motivation in science, technology, engineering, and math (STEM), including ability beliefs and sense of belonging. When children belong to a gender group that is negatively stereotyped in a STEM field, they may doubt their own capabilities and whether they belong in that field, making it harder for them to develop interest over time. Developmentally, the influence of gender stereotypes on motivation begins during preschool and strengthens during late childhood. I also address the consequences of different kinds of stereotypes and why some children are more influenced by stereotypes than others. Understanding this process in childhood will help researchers design effective interventions to remedy educational inequities in STEM.
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We investigated how gender is represented in children’s books using a novel 200,000 word corpus comprising 247 popular, contemporary books for young children. Using human judgments and word co-occurrence data, we quantified gender biases of words in individual books and in the whole corpus. We find that children’s books contain many words that adults judge as gendered. Semantic analyses based on co-occurrence data yielded word clusters related to gender stereotypes (e.g., feminine: emotions; masculine: tools). Co-occurrence data also indicate that many books instantiate gender stereotypes identified in other research (e.g., girls are better at reading and boys at math). Finally, we used large-scale data to estimate the gender distribution of the audience for individual books, and find that children are more often exposed to gender stereotypes for their own gender. Together the data suggest that children’s books may be an early source of gender associations and stereotypes.more » « less
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This qualitative study explored how 21 Black women enrolled in engineering and computing doctoral programs characterize and understand how they code-switch. We define code-switching as when Black women consciously or unconsciously modify the way they behave in engineering and computing environments to dissociate themselves from negative stereotypes held against their intersectional identities across gender and race. Utilizing Black feminist thought (BFT) as a theoretical framework, this study found that Black women experienced a host of detrimental challenges. Due to their environ- ments, participants modified how they dressed and spoke in a conscious attempt to avoid reinforcing negative stereotypes held against Black women (i.e., the angry Black woman, the incompetent Black woman scientist, nega- tive connotations of Black sounding names, and respectability politics of Black womanhood) and instead dispel these myths. To cope with the effects of code-switching, Black women relied heavily on their spirituality and identifying ways to reaffirm their Blackness. The implications of the findings indicate that Black women experience stress due to code-switching because of the stereotypes they encounter at the intersection of their gender and race.more » « less
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There is a need to help more students succeed in science, technology, engineering, and mathematics (STEM) education, with particular interest in reducing current gender gaps in motivation and participation. We propose a new theoretical model, the STEreotypes, Motivation, and Outcomes (STEMO) developmental model, to account for and integrate recent data emerging in social and developmental psychology. Based on this model, we synthesize research suggesting that social factors, such as stereotypes and self-representations about “belonging,” are powerful contributors to observed gender differences in STEM interest and academic outcomes. The review has four parts. First, we examine how cultural stereotypes specific to STEM contribute to gender gaps by negatively impacting interest and academic outcomes. Second, we review the central role of the self-representations affected by those stereotypes, including the particular importance of a sense of belonging. Third, we discuss various interventions that buffer against stereotypes and enhance a sense of belonging to reduce gender gaps in STEM interest and academic outcomes. Finally, we suggest theory-driven directions for future research. By organizing the research in this way, our review and theoretical analysis clarify key factors contributing to current gender gaps in STEM and mechanisms by which psychological interventions can help address STEM gender gaps.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.48550/arXiv.2105.09296
