Cracking the code: Encouraging girls in computer science and engineering

Gender stereotypes impact school students’ motivation to study STEM earlier than you might expect │3 min read
Published in Neuroscience
Cracking the code: Encouraging girls in computer science and engineering

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“It Starts Early: How STEM Stereotypes Impact Children.
A video about the power of gender stereotypes (2 min video).
UW Institute for Learning & Brain Sciences.

If we want to draw more women into STEM fields, we must start early. Our recent research in Proceedings of the National Academy of Sciences demonstrated that young children’s perceptions of STEM fields matter. By age eight, most children in the U.S. already believe that boys are more interested in computer science and engineering than girls are. What happens when girls believe these fields are “not for me”? It’s no surprise that they are not interested in pursuing them. We found the presence of stereotypes directly causes children, especially young girls, to lose interest and the motivation to study STEM subjects.

But parents, teachers, policymakers, and others who care for children have the power to alter the effects of these stereotypical beliefs before they become entrenched in the minds of children. One key piece to solving this puzzle is to recognize that early experiences matter. Books we read to children, the television shows they watch, and even the way toy stores display toys imply subtle messages about whether STEM activities are for girls or boys. Even well-intentioned statements like, “Girls are just as good as boys at coding!” may backfire and reinforce gender stereotypes.

We encourage parents to sign their daughters up for afterschool coding programs and summer camps. Or even better, sign them up and bring along a friend. These choices can send strong signals to girls about what their parents expect them to enjoy. And when more of these doorways are opened for girls, parents might be gratified to discover how much their girls end up enjoying STEM activities.

We encourage teachers to pay attention to their interactions with students. Teachers’ behaviors can send children implicit messages about who will be successful and who belongs, without being aware that they are doing so. Think about everyday behavior in a typical classroom. Who gets encouraged to try new STEM activities first? The boys. Who gets reassured that it’s okay to not be a math person? The girls.

We encourage policymakers to adopt education policies that offer foundational computer science classes to all elementary school students. In classrooms that convey a sense of belonging to everyone, girls have the opportunity to try STEM activities, potentially discover a passion for coding, and in the process, reshape the stereotypes of the students around them. Some states within the U.S. are already doing this. For example, Rhode Island has established an innovative computer science program in elementary school. But far too few states and countries start early enough.

We’ve made a lot of progress encouraging girls to participate in the fields of biology and math. But what we’re still missing are the mechanisms for encouraging young girls’ interests in computer science and engineering. Our research suggests elementary school is a critical time. Children are starting to form beliefs about ‘who does computer science and engineering’ as early as first grade. Fortunately, we have a window of opportunity to intervene before these beliefs impact students’ behavior and educational choices, and stop the stereotypes from growing into self-fulfilling prophecies.

Learn more about our open-access article, Gender stereotypes about interests start early and cause gender disparities in computer science and engineering, published by Proceedings of the National Academy of Sciences.

Authors: Allison Master, Andrew N. Meltzoff, and Sapna Cheryan.

Poster Image: UW Institute for Learning & Brain Sciences.


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, e2100030118.

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