Robert Noyce Teacher Scholarship Program Track 2 Project: Creating STEM Teacher Fellows To Leverage AI

About This Grant

This Noyce Track 2 project aims to serve the national need to address lagging achievement scores in STEM education by preparing highly-qualified STEM teachers who can effectively leverage artificial intelligence (AI) to advance student learning. AI holds significant promise for enriching learning through its ability to personalize learning experiences, provide timely feedback and support, and help teachers identify and address student needs. This project plans to support one cohort of 12 STEM professionals (i.e., biological & physical science, computer science, engineering, mathematics, and statistics undergraduate majors) to become 7-12th grade teachers through an innovative program that combines research-based pedagogies with strategic AI integration. First, participants are expected to complete an integrated post-baccalaureate teaching credential and MA program while gaining hands-on experience using AI tools in high-need schools. The project is designed to provide participants training in, and conduct teacher research on, AI applications for advancing student learning. Finally, participants are scheduled to host an "AI for Advancing Learning in STEM Education" conference to share their research and practical strategies with other educators to help build a broader community of teachers skilled in leveraging AI to create supportive and engaging learning environments. The proposed project components intends to prepare highly-qualified STEM professionals to become highly-effective 7-12th grade STEM teacher leaders who have a strong understanding of the practical applications, challenges, and successes of leveraging AI to advance student achievement and success in STEM. This project at the University of California, Davis, includes partnerships with the high-needs Twin Rivers Unified School District, and the non-profit organization Wicket who is dedicated to empowering STEM learners via technology. Project goals include recruiting one cohort of 12 STEM professionals (i.e., biological & physical science, computer science, engineering, mathematics, and statistics undergraduate majors) to become 7-12th grade teachers in high-need school districts, providing training in research-based pedagogies and the strategic use of AI to support these practices, and cultivating these teachers as leaders who can effectively leverage and advocate for the use of AI to advance student learning in their schools and beyond. This project seeks to utilize an iterative evaluation process. The evaluation plan is designed to draw on the following project goals: (1) recruit one cohort of 12 highly-qualified STEM professionals to become 7-12th grade STEM teachers serving high-need schools, (2) provide comprehensive training in research-based pedagogies early in the project, while developing teacher fellows who are AI-ready, and (3) cultivate a cadre of teacher leaders who can effectively leverage and advocate for the use of AI to advance student learning in their schools, the region, and nationally. Through surveys, interviews, and an array of teaching artifacts, this project can offer new knowledge about approaches for recruiting, preparing, and supporting STEM teachers to use AI to advance student learning - insights particularly valuable given the novelty of AI technologies and the need to understand their use in education. Broader impacts include addressing the shortage of highly-qualified STEM teachers while building capacity among educators to effectively leverage AI to support and advance learning. Project findings plan to be disseminated through publications and conference presentations to inform both research and practice in STEM education. This Track 2 Teaching Fellowship project is supported through the Robert Noyce Teacher Scholarship Program (Noyce). The Noyce program supports talented STEM undergraduate majors and professionals to become effective K-12 STEM teachers and experienced, exemplary K-12 teachers to become STEM master teachers in high-need school districts. It also supports research on the effectiveness and retention of K-12 STEM teachers in high-need school districts. 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.