A data analytics certificate for non-computing majors.

该项目旨在通过为非计算机专业学生创建和测试一种创新的途径来积累技术技能的微证书，从而获得与现实世界职业应用相一致的学术证书，并为学生提供在各自学科中进行数据驱动调查所需的技能，从而服务于国家利益。由此产生的课程将以使用无代码到低代码再到高代码的方法对编程进行温和的介绍为特色，以吸引来自广泛学科的学生。该课程将置于社会公正的背景下，使其对历史上被边缘化的计算机社区具有吸引力。这个项目将使数据科学更容易被广泛使用，更相关，并且对计算机科学以外领域的学生更感兴趣。该课程将在严格的研究设计中开发和测试，其中包括评估该方法在提高对数据科学的认识、获取和兴趣方面的功效。研究活动将在非计算专业课程中为新兴的社会公正数据科学证书途径提供信息，衡量认证创新的有效性及其对参与者的影响，并为计算机科学培训领域提供一种产生根本性结构性变化的手段。项目团队将使用基于设计的研究方法（DBR）从从业者的角度评估这种认证的效用和好处，（ii）使用社会认知职业理论（SCCT）框架，评估该方法在增加数据科学基础知识，塑造身份，观念，能力感和学生职业选择方面的功效，特别是来自历史边缘化社区的学生。（iii）利用系统映射研究系统级变化，通过识别能够实现复制和可持续性的因素和支持，所提出的创新改造本科计算机教育的能力。该奖项反映了美国国家科学基金会的法定使命，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。

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.