RET Site: Berkeley Engineering Research Experiences for Teachers - Artificial Intelligence Resources for a Cleaner Environment (BERET-AIRE)

The three-year renewal REU Site: Berkeley Engineering Research Experiences for Teachers focused on Artificial Intelligence Resources for a Cleaner Environment (BERETAIRE) is hosted by the University of California-Berkeley. Teams of undergraduate STEM majors, high school teachers and community college educators will collaborate to uncover, understand, and utilize AI for environmental-related research.

The power of Artificial Intelligence (AI) to change the way we interact with the world is visible around us every day. This includes routine internet searches for information, teaching and learning in elementary through graduate school settings, and basic and applied research at the frontiers of discovery across all disciplinary fields. This project immerses science and math teachers from local high schools and community colleges in a variety of mechanical, civil and environmental engineering laboratories using AI tools.

BERETAIRE will recruit science and math teachers from a broad range of schools in the San Francisco area. Participants will educate, prepare, and encourage their high school and community college students to pursue STEM majors and careers.

The three-year REU Site: Berkeley Engineering Research Experiences for Teachers focused on Artificial Intelligence Resources for a Cleaner Environment (BERETAIRE) is hosted by the University of California-Berkeley. This project focuses on research to uncover, understand, and utilize artificial intelligence (AI) resources for environmental sustainability research studies in a variety of engineering laboratories.

BERET-AIRE will establish teams of pre-service teachers enrolled in the UC Berkeley CalTeach secondary teacher education program, in-service high school and community college teachers serving broad populations of students in the San Francisco Bay Area. These participants will develop essential research and computational skills using AI resources to complete engineering research projects.

One area where AI is particularly powerful is finding features and connections in datasets that cannot be determined utilizing traditional approaches. This can lead to a wide variety of beneficial uses, from enhanced voice recognition and caption generation to benefit the hearing impaired, to discovering new medicine compounds. Teacher teams will also participate in a sequence of summer and academic-year professional development activities that support them to translate their research into classroom instruction.

Each RET participant will develop curricula that connects current research to high school and community college science and math learning.

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.