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.

扩大计算参与（BPC）是国家优先事项。但是，高等教育机构监视和报告BPC数据的能力是高度可变的。该项目以BPC的15个本科计算部门的BPC努力成功进行，该项目与BPC的努力成功进行，该项目与3至5个与以前的BPC计划没有或有限参与的机构相关。努力包括收集本科计算注册和学位事件（EDA）数据，该数据被性别和种族/种族分开，创建数据可视化以分析部门趋势和模式，并与机构合作伙伴紧密合作，以了解其BPC数据并制定有效的策略来维持和报告和报告。该项目旨在为变更和数据驱动的决策提供信息，以改善机构级别的BPC，并提高提供给外部利益相关者提供的BPC数据的有效性。关于解决持续参与计算方面的持续参与差距的鲁棒数据的关键必要性有广泛的共识。该项目的数据收集过程故意旨在作为利用部门数据进行BPC努力的初始入口，通过关注计算机科学专业的EDA模式，并且在“所有计算”专业的大满贯范围内都更加广泛。该项目的关键输出包括：1）详细的互动数据可视化，这些可视化描述了性别趋势（例如，计算机中的妇女），种族/族裔（例如，计算机中的黑人学生）以及这些身份的结合（例如，计算机中的黑人妇女）的结合（例如，计算机中的黑人妇女），以及与每种参与者的参与式的介绍和指导的指导，并指导参与的机构，并指出了一定的参与者，并指出了参与的机构，并指出了参与的启示仪，并指出了参与式的调查。空白。鉴于对其BPC数据和相关趋势的了解，机构可以更有意义地参与其他现有的BPC努力。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子和更广泛的影响评估标准来评估，通过评估来诚实地支持支持。