BPC-DP: Leveraging Institutional Data Collection and Analysis as an Entry to BPC Work: A Pilot Program to Support Emerging DEI Efforts

扩大对计算机（BPC）的参与是国家的优先事项。然而，高等教育机构监测和报告BPC数据的能力变化很大。BRAID计划是BPC在15个本科计算机系开展的一项工作，在BRAID计划成功开展的基础上，该项目吸引了3到5个以前没有或有限参与BPC计划的机构。工作包括收集按性别和种族/民族分类的本科计算机入学和学位获得（EDA）数据，创建数据可视化以分析部门趋势和模式，并与机构合作伙伴密切合作以了解其BPC数据并制定维护和报告这些数据的有效策略。该项目旨在为变革和数据驱动的决策提供信息，以改善机构层面的BPC，并提高提供给外部利益相关者的BPC数据的有效性。在解决计算领域持续存在的参与差距方面，有一个广泛的共识，那就是强大的数据至关重要。这个项目的数据收集过程被有意设计成一个初始的切入点，通过专注于计算机科学专业的EDA模式和更广泛的跨“所有计算”专业的EDA模式，来为BPC工作利用部门数据。该项目的主要产出包括：1)详细的交互式数据可视化，按性别（例如，计算机领域的女性）、种族/民族（例如，计算机领域的黑人学生）以及这些身份的组合（例如，计算机领域的黑人女性）描述趋势；2)与每个参与机构进行一对一的研讨会，以突出关键发现，并指导参与者考虑具体的行动和干预措施，以解决参与差距。随着对BPC数据和相关趋势的进一步了解，机构可以更有意义地参与其他现有的BPC工作。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。

Broadening participation in computing (BPC) is a national priority. However, the capacity of higher education institutions to monitor and report on BPC data is highly variable. Building on work that was successfully conducted through the BRAID initiative, a BPC effort at 15 undergraduate computing departments, this project engages three to five institutions that have had no or limited engagement with previous BPC initiatives. Efforts include collecting undergraduate computing enrollment and degree attainment (EDA) data disaggregated by gender and race/ethnicity, creating data visualizations to analyze departmental trends and patterns, and working closely with institutional partners to understand their BPC data and develop effective strategies for maintaining and reporting it. This project stands to inform change and data-driven decisions to improve BPC at the institutional-level and enhance the validity of BPC data that is provided to external stakeholders.There is broad consensus on the critical necessity of robust data in addressing persistent participation gaps in computing. This project’s data collection process is intentionally designed to serve as an initial entry point into leveraging departmental data for BPC efforts by focusing on EDA patterns narrowly within the Computer Science major and more broadly across “All Computing” majors. The key outputs of this project include: 1) detailed, interactive data visualizations that depict trends by gender (e.g., women in computing), race/ethnicity (e.g., Black students in computing), and the combination of these identities (e.g., Black women in computing), and 2) one-on-one workshops with each participating institution to highlight key findings and guide participants to consider specific actions and interventions to address participation gaps. With an enhanced understanding of their BPC data and related trends, institutions can engage more meaningfully in other existing BPC efforts.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.