Double Isolation: Social Pressure and Gender Disparities in Computer Science

University Of Washington, Seattle WA

Investigators

Abstract

In 2010, women earned about half of all science undergraduate degrees; yet in the same year, women earned less than 20% of computer science degrees. Computer science remains one of the least gender diverse of the STEM fields and one of the most impervious to change. Current theories that explain this disparity typically focus on women's attitudes and backgrounds (e.g., lower confidence, lack of prerequisites) or the unwelcoming climate of the field (e.g., negative stereotypes about women's abilities). This work will focus on an overlooked component of women's experience in the selection of an academic field: social pressure from peers to conceal an interest in the field. Specifically, the research will investigate whether women express less interest in computer science because they anticipate negative judgment for entering a stereotypically masculine field. Current interventions to draw girls into male-dominated fields typically focus on changing women (e.g., providing computing experience). The research proposed here suggests that women may be forsaking important learning opportunities in STEM before trying them because of the social pressure they perceive. However, relatively simple changes to educational environments may be able to "turn off" this social pressure and increase women's interest in computer science. The current work develops and tests a theoretical model that identifies the sources of social pressure on women and the consequences of this social pressure on women's interest and performance in computer science. To test the theory, researchers will conduct two surveys in Year 1 and seven behavioral experiments in Years 1 to 3. In Year 1, the focus will be on whether women perceive more social pressure than men in computer science but not in other fields (e.g., English), and the effects of perceived social pressure on interest and performance in computer science. In Year 2, the research will examine how to reduce social pressure by using private learning mechanisms and broadening stereotypes. In Year 3, the researchers will partner with the Computer Science Teachers Association to conduct a large-scale field experiment across multiple high schools that tests whether exposure to female computer science role models who are portrayed with their friends reduces perceived social pressure on women and increases their interest in computer science.