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: North Carolina Central University
• 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
• 起止时间: 2023-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2245958&HistoricalAwards=false
• 关键词: data; analytics; certificate; non; computing

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.

该项目旨在通过创建和测试非计算专业的创新途径来满足国家利益，以将微观证书叠加在技术技能上，以符合与现实世界中职业应用相符的学术证书，并为学生提供各自学科中数据驱动的调查所需的技能。由此产生的课程将使用针对高代码方法的无代码进行节目介绍，以使其吸引广泛学科部分的学生。该课程将位于社会正义背景下，使其对历史上边缘化的计算社区有吸引力。该项目将使数据科学更广泛地访问，更相关，并且对计算机科学以外的领域的学生更加感兴趣。该课程将在严格的研究设计中开发和测试，其中包括评估提高意识，访问和对数据科学兴趣的方法的效率。研究活动将为非计算专业的课程中的社会正义证书途径提供信息，衡量认证创新的效率及其对参与者的影响，并提供一种在计算机科学培训领域中产生根本的结构性变化的手段。项目团队将使用基于设计的研究方法（DBR）评估（i）从从业人员的角度评估这种认证的实用性和好处，（ii）在增加数据科学的基本知识，身份，认识，知觉，能力和职业选择的效率，尤其是使用历史上的社会范围内的社会知识II（SCCT）框架（SCCT）框架（SCCT）框架（SCCT），以及（SCCT）通过确定能够使用系统映射来研究系统级变化的因素和支持来改变本科计算教育，以反映NSF的法定任务，并被认为是通过基金会的智力优点和更广泛的影响来审查标准的评估，认为这是宝贵的支持。