CHS: Large: Collaborative Research: Gender-Inclusive Open Source through Gender-Inclusive Tools

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This research will investigate whether and how open source software (OSS) tools and technologies have gender biases tied with diverse problem-solving styles, and how to remove any such biases that are found. OSS is having a significant impact on society, in the products it produces and the career paths that it facilitates. However, women are vastly underrepresented among OSS developers. This is a significant concern to OSS communities because it prevents them from receiving the benefits of a larger talent pool and the benefits that ensue from team diversity. Further, the problem feeds upon itself: women developers then miss out on the learning and professional growth opportunities that OSS projects provide, and professional opportunities evade women developers when open source contributions are used to make hiring decisions, both of which hold them back from OSS engagement.This work will harness foundational gender research to provide theory-based yet practical solutions, towards addressing the underrepresentation of women in OSS communities. In Phase 1, the research will experimentally identify gender biases through the GenderMag research technique, and cross-validate results empirically. This is an inspection method for software professionals to use to find gender-bias "bugs" in their own software, by assessing to what extent their software supports diverse cognitive styles in terms of five facets: (1) motivations, (2) computer self-efficacy, (3) risk aversion with technology, (4) information processing styles, and (5) styles of learning new technology. Starting with each facet implicated in the bugs identified in Phase 1, the Phase 2 research will derive redesigns for each facet identified by working closely with the teams. The redesigns and the process of creating inclusive tools will be empirically evaluated to create a compendium of "best practices" for fixing gender-bias bugs, in both products (what suitable fixes are to such bugs) and processes (how OSS teams can work together to fix gender-bias bugs). Continuous evaluation will be a critical component throughout, to determine which practices and processes work and which do not.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.