Developing a Computing Application Minor and an Inclusive Learning Environment to Build the Diverse, Multidisciplinary Computer Science Workforce of the Future

该项目旨在解决STEM教育的两个迫切需求：1)增加数据和计算机科学专业毕业生的数量；2)提高STEM领域的多样性。旧金山州立大学（SFSU）的项目团队将通过开发和实现计算应用辅修课程来实现这些目标。该辅修课程将使用基于证据的方法来吸引、留住和支持学生，并关注那些在计算机/数据科学领域代表性不足的学生，包括女学生。通过根据学生的专业定制活动，该项目希望提高学生的参与度，并帮助学生体验数据和计算机科学如何应用于他们的专业和未来的职业。辅修课程的学生将有机会在当地工业和政府机构工作。此外，该项目将与NSF在旧金山州立大学的INCLUDES项目相连。因此，计算机应用的未成年人将能够作为计算机科学导师和榜样与高中生一起工作。这些经验可以支持关键技能的发展，包括领导能力。该项目旨在提供一种可持续的、可扩展的模式，向理科生介绍数据和计算机科学，这种模式可以被其他机构采用，并可以扩大这些领域的参与。计算机应用辅修课程为四个学期，五门课程，专为没有计算机/数据科学知识的STEM学生设计，并且需要在专业中完成全部课程。该项目将为参与的学生提供与其专业相关的学习经验，以基于证据的科学教学方法培训计算机科学教师，并邀请学生与K-12社区分享他们的知识。为了减少刻板印象威胁和冒名顶替综合症，该项目将采用一种基于群体的结构，利用同伴、教师和行业导师来创建一个培养和支持学习者的社区。该项目将确定能够提高学生对计算机/数据科学兴趣的教学方法，以及他们在专业中使用计算机/数据科学的动机。这些研究结果可以为其他努力提供信息，以扩大拥有计算专业知识的人的多样性，以及决定攻读计算机/数据科学研究生学位和职业的人。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 address two pressing needs in STEM education: 1) increasing the number of students graduating with expertise in data and computer science; and 2) improving diversity in STEM fields. The project team at San Francisco State University (SFSU) will achieve these goals by developing and implementing a Computing Application minor. This minor will use evidence-based approaches to attract, retain, and support students, with attention to students from groups that are underrepresented in computer/data science, including female students. By tailoring activities to students' majors, the project expects to increase student engagement and help students experience how data and computer science are applied in their majors and future professions. Students in the minor will have opportunities to work with local industry and governmental agencies. In addition, this project will link to the NSF INCLUDES project at SFSU. As a result, the Computing Application minors will be able to work with high school students as computer science mentors and role models. These experiences can support development of critical skills, including leadership. The project aims to provide a sustainable and scalable model for introducing data and computer science to science majors that can be adopted by other institutions, and that can broaden participation in those fields.The Computing Application minor will be a four-semester, five-course sequence designed for STEM students who have no prior computer/data science knowledge and who are taking a full course load in their major. The project will provide participating students with learning experiences related to their majors, train computer science faculty in evidence-based science teaching methods, and invite students to share their knowledge with the K-12 community. To reduce stereotype threat and imposter syndrome, the project will employ a cohort-based structure that uses peer, faculty, and industry mentors to create a nurturing and supportive community of learners. The project will identify pedagogies that promote students' interest in computer/data science and their motivation to use it in their majors. These research results can inform other efforts to broaden the diversity of people who have computational expertise, and who decide to pursue graduate degrees and careers in computer/data science.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.