Collaborative Research: Broadening Inclusive Participation in Artificial Intelligence Undergraduate Education for Social Good Using A Situated Learning Approach

该项目旨在通过提高大学水平的人工智能(AI)教育来服务于国家利益。人工智能的进步可能会改善交通、教育、医疗保健和其他社会问题。大学生掌握人工智能技能，为成为未来的领导者和创新者做好准备，这一点很重要。然而，目前的人工智能教育既缺乏广泛的多学科参与，也缺乏多样性。该项目计划制定和实施改善人工智能教育的战略，这些战略对所有学生都适用，而不仅仅是那些注册计算机科学课程的学生。为了做到这一点，项目组希望开发出识别社会问题的材料，并教会学生应用人工智能的概念和方法来解决这些问题。因此，该项目可能会为今天的大学生进入未来的STEM劳动力做好更好的准备。该项目旨在开发人工智能学习模块，以刺激学生社区的人工智能学习。学生们将接受如何识别社会问题的培训。教师将通过亲身实践的人工智能实验室向学生传授人工智能概念和应用。学生们将学习如何提出人工智能支持的解决方案，以解决社会问题，同时考虑到好处和风险。跨学科的AI for Social Good(AI4SG)模块将在加州州立大学三个校区的管理信息系统、地理和计算机科学项目中实施。该团队计划主办一次年度研讨会，展示学生项目并传播AI4SG教育的最佳实践。该项目将使用定量和定性研究方法，并希望通过文化响应性计算，产生AI4SG教育如何影响动机、学习结果、创新和公平差距的证据。该项目由NSF IUSE：EHR计划支持，该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。通过参与式学生学习路径，该计划支持创建、探索和实施有前途的实践和工具。NSF IUSE：HSI计划提供额外的支持，该计划旨在加强本科生STEM教育，扩大对STEM的参与，并建设HSIS的能力。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 improving college-level education in artificial intelligence (AI). Advances in AI will likely improve transportation, education, healthcare, and other societal issues. It is important that college students gain skills in AI to prepare them to be future leaders and innovators. However, current AI education lacks both broad multidisciplinary participation and diversity. The project plans to develop and implement strategies for improving education in AI that are available to all students, not just those enrolled in computer science programs. To do so, the project team hopes to develop materials that identify social problems and teach students to apply AI concepts and methods to address these problems. As a result, this project may better prepare today’s college students to enter the STEM workforce of the future.The project intends to develop AI learning modules to stimulate AI learning in students’ communities. The students will be trained how to identify social problems. The instructors will teach students AI concepts and applications through hands-on AI labs. The students will learn how to propose AI-powered solutions to address social issues considering both benefits and risks. The interdisciplinary AI For Social Good (AI4SG) modules will be implemented in the programs of management information systems, geography, and computer science at three California State University campuses. The team plans to host an annual workshop to showcase student projects and disseminate best practices of AI4SG education. The project will use both quantitative and qualitative research methods and hopes to generate evidence on how AI4SG education, through culturally responsive computing, can impact motivation, learning outcomes, innovation, and equity gaps. This project is supported by the NSF IUSE: EHR Program, which supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. Additional support is provided by the NSF IUSE:HSI program, which seeks to enhance undergraduate STEM education, broaden participation in STEM, and build capacity at HSIs.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.