BPC-A: Data Alliance on Persistence and Perception in Computing (DAPPIC)

BPC-A:计算持久性和感知数据联盟 (DAPPIC)

基本信息

  • 批准号:
    2216629
  • 负责人:
  • 金额:
    $ 132.3万
  • 依托单位:
  • 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

项目摘要

Northeastern University’s Center for Inclusive Computing (the CIC), the Computing Research Association’s (CRA) Center for Evaluating the Research Pipeline (CERP) and 28 individual universities collaborate to improve the availability and use of quantitative and qualitative data to support the efforts of individual schools and the sector overall in broadening participation inundergraduate computing education. University leaders are highly motivated to increase the representation of populations historically minoritized in computing. However, while best practices for broadening participation in computing (BPC) have been developed and evaluated, it is not always clear which practices align with an institution’s particular challenges. To accurately diagnose barriers to inclusion and to assess the impact of interventions, leaders need reliable access to detailed enrollment, retention and graduation data as well as qualitative data on the experience of students of different identities. The collaboration addresses the need to improve the availability and use of quantitative and qualitative data to support individual schools and the sector as a whole. The CIC collects term by term, class by class data on student enrollment, retention, and graduation, disaggregated by demographics. At present the CIC does this work with 57 schools. This data is then visualized in dashboards that allow the user to compare between different intersections of identities, compare changes and trends across terms, and benchmark against an average of the 57 partner schools. CRA’s CERP collects and disseminates data from 150+ computing departments that participate in the Data Buddies Survey (DBS). At the undergraduate level, DBS gathers information about the academic and demographic background of learners, career pathways, as well as various indicators related to the recruitment, retention, and persistence in computing. The Alliance will integrate the two datasets and set a new standard for the usage of data in BPC. Additionally, the Alliance will work with the National Student Clearinghouse’s (NCS) Post-secondary Data Partnership (PDP), which offers in-depth dashboards that allow institutions to visualize student outcomes in aggregated and disaggregated forms. We see a point-in-time opportunity with the PDP’s priority in 2022 to develop discipline-specific dashboards to bring our collective experience working with BPC data as well as a robust “voice of the client” perspective. The specific activities are: 1) add new functionality to CIC dashboards (ability to compare across intersectional identities, to benchmark against different peer groups, and to connect to outside data sources such as NCES’ IPEDS); 2) integrate CIC/DBS data; 3) evaluate the integration and disseminate learnings; 4) explore potential integration with NSC; and 5) plan for achieving a model that provides long-term sustainability and scale. We will evaluate the efficacy of the approach with 28 schools, all of which participate in both the CIC’s data collection and CERP’s DBS.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.
东北大学普惠计算中心(CIC)、计算研究协会(CRA)研究管道评估中心(CERP)和28所单独的大学合作,改善定量和定性数据的可用性和使用,以支持个别学校和整个行业在扩大本科计算教育参与度方面的努力。大学领导人非常有动力增加在计算领域历史上被划分为小规模的人群的代表性。然而,尽管已经开发和评估了扩大计算参与度(BPC)的最佳做法,但并不总是清楚哪些做法符合机构的特殊挑战。为了准确地诊断纳入的障碍并评估干预措施的影响,领导者需要可靠地获得详细的入学、保留率和毕业数据,以及关于不同身份学生经历的定性数据。这种协作解决了改善定量和定性数据的提供和使用的需要,以支持个别学校和整个部门。CIC逐个学期、逐个班级收集按人口统计分类的学生入学、留校和毕业数据。目前,CIC与57所学校开展了这项工作。然后,这些数据在仪表板中可视化,允许用户比较身份的不同交叉点,比较不同术语的变化和趋势,并以57所合作学校的平均水平为基准。CRA的CERP收集和传播参与数据伙伴调查(DBS)的150多个计算部门的数据。在本科生层面,DBS收集关于学习者的学术和人口背景、职业道路以及与招聘、保留和坚持计算有关的各种指标的信息。联盟将整合这两个数据集,并为BPC中数据的使用设定新的标准。此外,该联盟将与国家学生信息交换中心(NCS)的中学后数据伙伴关系(PDP)合作,该伙伴关系提供深入的仪表板,使各机构能够以聚合和分类的形式可视化学生结果。我们看到了PDP在2022年优先开发特定学科仪表板的时间点机会,以带来我们使用BPC数据的集体体验以及强大的“客户之声”视角。具体活动是:1)向CIC仪表板添加新功能(能够跨部门身份进行比较,以不同同行群体为基准,并连接到NCES的IPEDS等外部数据源);2)集成CIC/DBS数据;3)评估集成并传播经验;4)探索与NSC的潜在集成;以及5)计划实现可提供长期可持续性和规模的模型。我们将与28所学校一起评估这种方法的有效性,所有这些学校都参与了CIC的数据收集和CERP的数据库。这个奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

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Carla Brodley其他文献

Carla Brodley的其他文献

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{{ truncateString('Carla Brodley', 18)}}的其他基金

CUE-M: LEVEL UP: Charting a Pathway toward Inclusive Computing
CUE-M:LEVEL UP:绘制包容性计算之路
  • 批准号:
    2246079
  • 财政年份:
    2023
  • 资助金额:
    $ 132.3万
  • 项目类别:
    Standard Grant
Broadening Participation in the CyberCorps(R) Scholarship for Service Program
扩大 Cyber​​Corps(R) 服务奖学金计划的参与范围
  • 批准号:
    2208797
  • 财政年份:
    2022
  • 资助金额:
    $ 132.3万
  • 项目类别:
    Standard Grant
BPC-AE: An Extension to Widening the Research Pipeline
BPC-AE:拓宽研究渠道的延伸
  • 批准号:
    0739229
  • 财政年份:
    2008
  • 资助金额:
    $ 132.3万
  • 项目类别:
    Standard Grant
III-CXT-Medium: Interdisciplinary Machine Learning Research and Education
III-CXT-Medium:跨学科机器学习研究和教育
  • 批准号:
    0803409
  • 财政年份:
    2008
  • 资助金额:
    $ 132.3万
  • 项目类别:
    Standard Grant
Multidisciplinary Research Opportunities for Women
女性的多学科研究机会
  • 批准号:
    0636325
  • 财政年份:
    2007
  • 资助金额:
    $ 132.3万
  • 项目类别:
    Standard Grant
SEI: Collaborative Research: Discovering Unexpected Planets and Other Astronomical Oddities
SEI:合作研究:发现意想不到的行星和其他天文奇异现象
  • 批准号:
    0713259
  • 财政年份:
    2007
  • 资助金额:
    $ 132.3万
  • 项目类别:
    Continuing Grant
Collaborative Research: SGER: Mining for Planets
合作研究:SGER:行星采矿
  • 批准号:
    0540902
  • 财政年份:
    2005
  • 资助金额:
    $ 132.3万
  • 项目类别:
    Standard Grant
SGER: Behavioral Authentication of Server Flows
SGER:服务器流的行为身份验证
  • 批准号:
    0446030
  • 财政年份:
    2004
  • 资助金额:
    $ 132.3万
  • 项目类别:
    Standard Grant
SGER: Behavioral Authentication of Server Flows
SGER:服务器流的行为身份验证
  • 批准号:
    0335574
  • 财政年份:
    2003
  • 资助金额:
    $ 132.3万
  • 项目类别:
    Standard Grant
Workshop: Student Scholarship Program for the International Conference on Machine Learning (ICML 2001)
研讨会:国际机器学习会议学生奖学金计划 (ICML 2001)
  • 批准号:
    0004495
  • 财政年份:
    2000
  • 资助金额:
    $ 132.3万
  • 项目类别:
    Standard Grant

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