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

为了在参与的各个层面增加包容性和多样性，本研究将调查基于性别的参与开源软件的障碍。调查显示，女性在开源软件行业的比例仅为5%左右，甚至比技术人员的总体比例还要低。之前关于计算机行业性别的研究发现，缺乏自我效能感和导师支持是女性和代表性不足的个人参与和保留的主要障碍。这个项目将调查这些障碍如何影响开源软件开发社区的参与。它将确定和传播项目所有者和贡献者可以采取的行动，以加强代表性不足群体的参与。这项研究将创造工具并举办讲习班，以加强代表性不足的成员的参与。由于参与开源对于在技术领域获得就业越来越重要，因此这项研究具有显著提高劳动力发展的潜力。找到让开源更受所有性别欢迎的方法，可以使可用的技术劳动力增加近一倍，这对人才短缺的行业和社会都有重大好处，因为它可以增强国家创造软件密集型产品和服务的能力。本研究将通过首先进行一系列混合方法的实践研究来增强开源的多样性，包括访谈、大规模调查和档案分析，以了解：(a)参与经验如何根据受试者的性别而变化；(b)他们为什么离开或不加入开源软件项目。基于这些研究，研究团队将设计、部署和评估增强自我效能的干预措施，并在开源环境中促进新形式的指导。期望在以下方面做出具体的研究贡献：(1)更深入地了解女性在开源软件开发和开放协作环境中参与度低的原因；(2)了解自动化和可视化如何支持开放协作环境中未被充分代表的贡献者的自我效能和指导；(3)包容性协作环境设计指南。更一般地说，这项研究有望产生关于如何通过在软件工程中设计包容、开放的环境来提高人类表现的新知识，甚至更广泛地说，用于计算机支持的协作。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.