HCC: Medium: Designing Human-Centered Environments for Enhancing Diversity in Open Source

To increase inclusion and enhance diversity at all levels of participation, this research will investigate gender-based barriers to involvement in open source software. Surveys show that the representation of women in open source software is only about 5%, even worse than the technical workforce overall. Previous research on gender in the computing profession has identified lack of self-efficacy and mentorship support as key barriers to participation and retention for women and underrepresented individuals.

This project will investigate how these barriers influence participation in open source software development communities. It will identify and disseminate actions project owners and contributors can take to enhance participation from underrepresented groups. This research will create tools and conduct workshops to enhance participation from underrepresented members.

Since participation in open source is increasingly important for obtaining employment in technical fields, this research has the potential to significantly enhance workforce development. Finding ways to make open source more welcoming to all genders could nearly double the available technical workforce, with major benefits both to industry, where talent is in short supply, and to society, by enhancing the nation’s ability to create software-intensive products and services.

This research will enhance diversity in open source by first performing a series of mixed-methods studies of practice, consisting of interviews, a large-scale survey, and archival analyses to understand: (a) how participation experiences vary based on subjects' genders; and (b) why they leave or do not join open source software projects. Based on these studies, the research team will design, deploy, and evaluate interventions that enhance self-efficacy and facilitate new forms of mentoring in open source environments.

The following specific research contributions are expected: (1) deeper knowledge about the causes of low participation by women in open source software development and open collaborative environments; (2) an understanding of how automation and visualization can support self-efficacy and mentorship for underrepresented contributors in open collaboration environments; and (3) guidelines for the design of inclusive collaboration environments. More generally, this research is expected to yield new knowledge about how to enhance human performance through the design of inclusive, open environments in software engineering and even more broadly, for computer-supported collaboration.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.