课题基金 / 基金详情

A data analytics certificate for non-computing majors.

A data analytics certificate for non-computing majors.
非计算机专业的数据分析证书。
批准号:
2245958
负责人:
Ravanasamudram Uma
金额:
$118.31万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-07-01 至 2027-06-30

项目摘要

项目成果

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中文摘要
翻译
该项目旨在通过为非计算专业学生创建和测试一种创新途径来服务于国家利益,以在技术技能中堆叠微证书,从而获得与现实世界职业应用相一致的学术证书,并为学生提供数据驱动调查所需的技能。由此产生的课程将采用无代码到低代码到高代码的方法对编程进行温和的介绍,以吸引来自广泛学科的学生。该课程将位于社会正义的背景下,使其吸引历史上边缘化的社区在计算。该项目将使数据科学更广泛地获得,更相关,并对计算机科学以外的领域的学生产生更大的兴趣。该课程将在严格的研究设计中开发和测试,其中包括评估该方法在提高对数据科学的认识,访问和兴趣方面的有效性。研究活动将为非计算专业课程中的新兴数据科学社会正义证书途径提供信息,衡量认证创新的有效性及其对参与者的影响,并提供一种在计算机科学培训领域产生根本性结构性变化的手段。项目团队将评估(i)使用基于设计的研究方法(DBR)从从业者的角度来看这种认证的效用和好处,(ii)该方法在增加数据科学基础知识,塑造身份,感知,能力感和学生职业选择方面的有效性,特别是从历史上被边缘化的社区使用社会认知职业理论(SCCT)框架,以及(iii)所提出的创新通过识别能够使用系统映射来研究系统的复制和可持续性的因素和支持来改变本科计算教育的能力-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。
英文摘要
This project aims to serve the national interest by creating and testing an innovative pathway for non-computing majors to stack micro credentials in technical skills, towards an academic certificate aligned to real-world career applications and providing students the skills needed for data-driven investigations in their respective disciplines. The resulting curriculum will feature a gentle introduction to programming using a no-code to low-code to high-code approach, to make it appealing to students from a broad-cross section of disciplines. The curriculum will be situated within the social justice context, making it appealing to historically marginalized communities in computing. This project will make data science more widely accessible, more relevant, and of greater interest to students in fields outside of Computer Science. The curriculum will be developed and tested within a rigorous research design which includes assessing the efficacy of the approach at raising awareness, access, and interest in data science. Research activities will inform the emerging data science for social justice certificate pathway within courses for non-computing majors, measure the efficacy of the certification innovation and its impacts on participants, and provide a means to produce fundamental, structural change in the computer science training landscape. The project team will assess (i) the utility and benefit of such a certification from practitioners’ perspectives using the Design Based Research approach (DBR), (ii) the efficacy of the approach in increasing the foundational knowledge of data science, shaping identities, perceptions, sense of abilities, and career choices of students, particularly from historically marginalized communities using the Social Cognitive Career Theory (SCCT) framework, and (iii) the ability of the proposed innovation to transform undergraduate computing education by identifying factors and supports that enable replication and sustainability using system mapping to study system-level change.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.
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Broadening Participation Research Project: Investigating the Efficacy of Data Science for Environmental Justice based PBL Modules for Improving Diversity in Environmental Science
  • 批准号:
    2306658
  • 项目类别:
    Standard Grant
  • 资助金额:
    $34.91万
  • 财政年份:
    2023
  • 负责人:
    Ravanasamudram Uma
  • 依托单位:
Broadening Participation Research Project: Research for Social Justice - Broadening Participation through Data Science
  • 批准号:
    1912408
  • 项目类别:
    Standard Grant
  • 资助金额:
    $35.0万
  • 财政年份:
    2019
  • 负责人:
    Ravanasamudram Uma
  • 依托单位:
海外基金