Development of Inclusive STEM Curriculum Using Data Science Innovations of W.E.B. Du Bois to Promote Diversity in Science

该项目旨在通过开发、评估和传播新的课程材料来服务于国家利益，旨在增加学生的参与性学习，并促进本科理科课程的多样性和包容性。新材料将具有广泛的重要性，因为它们旨在教授一系列科学、技术、工程和数学课程中的科学推理和数据可视化过程。课程材料将介绍20世纪初黑人社会科学家W·E·B·杜博伊斯(W.E.B.Du Bois)的工作，他开创了数据可视化技术，这种技术在各科学学科中仍被认为是最先进的。此外，以杜博伊斯的学术工作为中心具有重要意义，因为他调查了种族不平等的社会原因，并以广泛受众可以接触到的方式促进黑人学者的赋权。该项目团队计划包括来自多个机构和科学学科的教职员工和学生，为课程开发做出贡献，并参与测试其影响。该项目旨在衡量课程如何影响本科生的学习、对科学的归属感和对科学的坚持性。课程材料和学习结果将在一个开放的在线资源库中广泛共享，这可能会使全国各地本科理科课程的大量学生和教职员工受益。该项目旨在开发、实施和评估杜博伊斯课程模块，该模块可以在三节50分钟的课堂或实验室课程中用于各种科学课程，同时还包括三项家庭作业。本科生将致力于探索杜博伊斯在数据科学方面的学术工作，使用杜博伊斯使用的数据分析和可视化技术，以及在其特定学科课程中使用适合领域的数据，并完成对他们学习的元认知书面反思。该课程将与三所合作院校的理科教职员工和学生合作开发，这三所院校分别是西班牙裔服务机构、杜博伊斯获得学位的历史上的黑人学院和大学，以及一流的常春藤盟校和主要是白人机构-每一所学校都有独特的学生群体。开发的课程将在40门课程中试行，覆盖三所合作院校的1600多名学生。该项目将检验这样一种假设，即实施这一全纳课程可以促进本科生的科学学习和归属感，特别是促进积极的科学协会，减少与边缘化背景的科学家有关的耻辱。对课程影响的调查将使用评估前/评估后设计和出版的评估工具，这些工具有证据表明可以衡量以下概念：1)归属感，2)积极(刻板印象促进)与污名化(刻板印象威胁)与种族和民族认同和科学家身份、刻板印象和关联性的联系，以及3)自我效能。此外，该项目将在使用模块干预的课程中收集评估证据，以及在不使用模块干预的课程中收集评估证据，从而使直接分析能够测试与干预相关的学生评估随时间的变化。该项目有很大的潜力促进人们了解，突出边缘群体科学家的成就的课程的开发和实施如何能够促进学生的成功和留住学生，同时也将科学概念和社会正义的教学结合起来。NSF IUSE：EDU计划支持研究和开发项目，以提高所有学生的STEM教育的有效性。通过其参与的学生学习跟踪，该计划支持有前途的实践和工具的创建、探索和实施。该奖项反映了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。

This project aims to serve the national interest by developing, evaluating, and disseminating novel curricular materials that aim to increase engaged student learning and promote diversity and inclusion in undergraduate science courses. The new materials will be of broad importance as they are intended to teach the process of scientific reasoning and data visualization across a range of science, technology, engineering, and math courses. Curriculum materials will feature the early 20th century work of the foundational Black social scientist, W.E.B. Du Bois who pioneered data visualization techniques that are still considered state of the art across science disciplines. Additionally, centering the scholarly work of Du Bois is of importance as he investigated the social causes of racial inequality and promoted empowerment of Black scholars in ways that were accessible for broad audiences. The project team plans to include faculty and students from multiple institutions and science disciplines to contribute to curriculum development and participate in testing its impact. The project intends to measure how the curriculum influences undergraduate student learning, sense of belonging in science, and persistence in science. Curricular materials and study results will be widely shared in an open, online repository, which could benefit large numbers of students and faculty in undergraduate science courses across the country. The project aims to develop, implement, and assess the Du Bois curriculum module that could be implemented in a variety of science courses during three, 50-minute class or laboratory sessions, along with three homework assignments. Undergraduate students will be engaged in exploring the scholarly work of Du Bois in data science, using data analysis and visualization techniques employed by Du Bois with domain-appropriate data for their particular disciplinary course, and completing metacognitive written reflections on their learning. The curriculum will be developed in collaboration with science faculty and students at each of the three partner institutions – a Hispanic Serving Institution, a Historically Black College and University where Du Bois earned a degree, and a top-ranked, Ivy League and Primarily White Institution – each of which has unique student populations. Developed curriculum will be piloted in 40 courses reaching over 1,600 students across the three collaborating institutions. The project will test the hypothesis that implementation of this inclusive curriculum can promote science learning and sense of belonging among undergraduate students, in particular fostering positive science associations and reducing stigma associated with scientists from marginalized backgrounds. Investigation of curriculum impact will use a pre/post-assessment design and published assessment tools that have evidence of validity for measuring constructs such as: 1) belonging, 2) positive (stereotype boost) vs stigmatized (stereotype threat) associations with racial and ethnic identity and scientist identity, stereotypes, and relatability, and 3) self-efficacy. Further, the project will collect assessment evidence in course offerings that use the module intervention as well as in course offerings that do not, enabling direct analyses to test for shifts in student assessments over time that are associated with the intervention. The project has strong potential to advance understanding of how development and implementation of curriculum highlighting the accomplishments of scientists from marginalized groups might promote student success and retention, while also integrating the teaching of science concepts and social justice. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.