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

合作研究：利用情景学习方法扩大人工智能本科教育的包容性参与以造福社会

• 批准号: 2142594
• 负责人: Heather Macias
• 金额: $ 6.88万
• 依托单位: California State University-Long Beach Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2142594&HistoricalAwards=false
• 关键词: Collaborative; Research; Broadening; Inclusive; Participation

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.

该项目旨在通过提高大学水平的人工智能（AI）教育，为国家利益服务。人工智能的进步可能会改善交通、教育、医疗和其他社会问题。重要的是，大学生获得人工智能技能，为他们成为未来的领导者和创新者做好准备。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，面向所有学生，而不仅仅是计算机科学专业的学生。为此，项目团队希望开发能够识别社会问题的材料，并教学生应用人工智能的概念和方法来解决这些问题。因此，这个项目可以更好地为今天的大学生进入未来的STEM劳动力做好准备。该项目旨在开发人工智能学习模块，以促进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训练。讲师将通过人工智能实验室向学生讲授人工智能概念和应用。学生们将学习如何提出人工智能解决方案来解决社会问题，同时考虑利益和风险。跨学科的AI For Social Good （AI4SG）模块将在加州州立大学的三个校区的管理信息系统、地理和计算机科学项目中实施。该团队计划每年举办一次研讨会，展示学生的项目，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，并希望提供证据，证明AI4SG教育如何通过文化响应计算影响动机、学习成果、创新和公平差距。该项目由美国国家科学基金会IUSE: EHR项目支持，该项目支持研究和开发项目，以提高所有学生STEM教育的有效性。通过参与学生学习轨道，该计划支持有前途的实践和工具的创建，探索和实施。NSF IUSE:HSI项目提供了额外的支持，该项目旨在加强本科STEM教育，扩大STEM参与，并建设HSI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。