Undergraduate Data Science Education at Scale

本项目在美国国家科学基金会“改善本科STEM教育计划：教育与人力资源”（IUSE: EHR）的支持下，旨在通过改善STEM和非STEM专业的本科数据科学教育，为国家利益服务。它计划通过在加州大学伯克利分校（R1大学）、马里兰大学巴尔的摩县分校（R2大学）和米尔斯学院（主要是女子文理学院）实施、完善和扩展一个创新的原型数据科学项目来实现这一目标。该原型程序为以前在统计或数据科学方面经验有限的学生提供了进入数据科学的切入点。它是围绕零先决条件的数据科学课程构建的，并发连接器课程介绍了如何在不同领域中使用数据科学。它包括将数据科学“推向”现有课程和发现项目的模块，使学生能够在现实环境中应用数据科学技能。它还纳入了一个数据科学学者项目，以支持学生的成功，特别是来自STEM中代表性不足的群体的学生。该原型项目采用同伴指导模式来支持学生学习，建立社区，提供指导，并与教师共同创建课程材料。该项目将制作一套开放资源课程材料和技术基础设施，以促进在其他机构成功实施原型计划。预计通过该项目开发的模型和材料将支持面向不同类型机构的不同学生的大规模数据科学教学。由于数据科学是一个相对较新的领域，需要做很多工作来调查教学和课程方法如何在这个领域发挥作用。该项目旨在产生关于如何最好地设计数据科学课程和教学法的新知识，以促进不同本科生的学习，包括来自STEM中代表性不足群体的学生。该项目的研究目标包括评估原型项目的具体组成部分如何影响学生的成绩；评估原型是否以及如何扩大数据科学的参与。项目的混合方法评估将包括形成性评估，以实现持续的质量改进，以及总结性评估，以衡量项目成果。该项目将开发课程和教学数据科学材料以及技术基础设施，这些材料和技术基础设施可以在不同的学生群体和不同的资源的不同机构中有效地定制和扩展。材料和研究成果将被广泛传播，以帮助推动本科数据科学教育的社区转型，以满足学生的需求，并最终在多个不同的机构环境中扩大对数据科学的参与。NSF IUSE: EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。该项目属于机构和社区转型轨道，支持在高等教育机构和学科社区之间转变和改善STEM教育的努力。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。

With support from the NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE: EHR), this project aims to serve the national interest by improving undergraduate data science education for STEM and non-STEM majors. It plans to achieve this goal by implementing, refining, and expanding an innovative prototype data science program at the University of California Berkeley (an R1 university), the University of Maryland, Baltimore County (an R2 university) and Mills College (a primarily women's liberal arts college). The prototype program serves as an entry point into data science for students with limited previous experience in statistics or data science. It is built around a zero-prerequisites data science course, with concurrent connector courses that introduce how data science is used in different fields. It includes modules that "push" data science into existing courses and Discovery Projects that enable students to apply data science skills in real-world settings. It also incorporates a Data Science Scholars program to support student success, particularly students from groups underrepresented in STEM. The prototype program uses a peer instruction model to support student learning, build community, provide mentoring, and co-create course materials with faculty. The project will produce a set of open source curricular materials and the technical infrastructure to facilitate successful implementation of the prototype program at other institutions. It is expected that the models and materials developed through this project will support the teaching of data science at scale to a diverse set of students in diverse types of institutions. Because data science is a comparatively new field, much work needs to be done to investigate how pedagogical and curricular approaches function in this domain. This project aims to generate new knowledge about how to best design data science curricula and pedagogy to promote learning among diverse undergraduate students, including students from underrepresented groups in STEM. The project's research objectives include evaluation of how specific components of the prototype program impact student outcomes; and assessment of whether and how the prototype can broaden participation in data science. The project's mixed-methods evaluation will include formative evaluation to enable continuous quality improvement, as well as summative evaluation to measure project outcomes. The project will develop curricular and pedagogical data science materials and technical infrastructure that can be efficiently tailored and scaled at different institutions with diverse student bodies and disparate resources. The materials and research findings will be widely disseminated, to help drive a community transformation in undergraduate data science education that can scale with student demand and ultimately broaden participation in data science across multiple, diverse institutional settings. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. This project is in the Institutional and Community Transformation track, which supports efforts to transform and improve STEM education across institutions of higher education and disciplinary communities.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.