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

San Jose State University Foundation, San Jose CA

Investigators

Abstract

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.