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

BPC-DP：利用机构数据收集和分析作为 BPC 工作的入口：支持新兴 DEI 工作的试点计划

• 批准号: 2215697
• 负责人: Kathleen Lehman
• 金额: $ 30万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2215697&HistoricalAwards=false
• 关键词: BPC; DP; Leveraging; Institutional; Data

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.

扩大参与计算（BPC）是国家的优先事项。然而，高等教育机构监测和报告预算和预算执行情况数据的能力差异很大。在通过BRAID计划（BPC在15个本科计算部门的努力）成功开展的工作的基础上，该项目吸引了三到五个机构参与，这些机构没有或有限地参与了以前的BPC计划。努力包括收集按性别和种族/民族分类的本科计算入学和学位获得（EDA）数据，创建数据可视化来分析部门趋势和模式，并与机构合作伙伴密切合作，以了解他们的BPC数据，并制定有效的战略，以维护和报告它。该项目旨在为变革和数据驱动的决策提供信息，以改善机构的BPC，提高提供给外部利益相关者的BPC数据的水平和有效性。在解决计算中持续存在的参与差距方面，可靠数据的关键必要性已达成广泛共识。该项目的数据收集过程是有意设计的，作为一个初始的切入点，利用部门的数据为BPC的努力，专注于EDA模式狭窄的计算机科学专业和更广泛的跨“所有计算”专业。该项目的主要成果包括：1）详细的交互式数据可视化，按性别描绘趋势（例如，计算中的女性），种族/民族（例如，黑人学生在计算），以及这些身份的组合（例如，2）与每个参与机构举办一对一讲习班，以强调主要调查结果，并指导参与者考虑采取具体行动和干预措施，以解决参与差距。随着对其BPC数据和相关趋势的深入了解，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NSF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。