Community Impact with Teacher Leaders in Data Science and Mathematical Modeling

Utah State University, Logan UT

Investigators

Abstract

The project aims to serve the national need of developing highly effective teacher leaders with the skills necessary to instruct secondary students in mathematical modeling and data science. In rural and Native American communities in Utah, teachers and university experts will partner to investigate local issues. Although using mathematics and data science to inform decision making regarding important scientific and social issues has been growing in significance, many secondary mathematics teachers, particularly in rural areas, have had limited opportunities to learn mathematical and data modeling skills or effective ways to teach these skills to their students. This project aspires to create more opportunities and teaching support to cultivate rich opportunities for learning among rural and Native American students by enhancing teacher leaders’ expertise in data science and mathematical modeling and in culturally responsive teaching practices in this context. In addition, teacher leaders will hone skills for mentoring other teachers in their schools. This project at Utah State University (USU) includes partnerships with Uintah, Duchesne, and San Juan School Districts, along with Uintah River High School within the Ute Tribe Education Department in Utah. Project goals include: (1) Develop teacher leaders with expertise in data science and mathematical modeling to levels requisite for strengthening modeling and data science education; (2) Develop teacher leaders with the pedagogical expertise to incorporate culturally responsive teaching in data science and mathematical modeling lessons; (3) Develop teacher leaders who will engage with their communities through research activities and mentor prospective and early career teachers in rural and Native communities. The project will recruit and support 24 master teacher fellows (MTFs) to become exemplary teacher-leaders who engage students with mathematical modeling and data science in culturally relevant contexts. To this end, the design of the project enables the creation of mathematical modeling and data science learning materials and instructional techniques that are grounded in the needs, culture, and experiences of rural and Native American communities. Through cultivating teacher leaders in high-need school districts with pedagogical content knowledge in mathematical modeling and data science, the project seeks to improve STEM education outcomes for students in the state of Utah. A panel comprised of professionals, educators, and state government officials will provide guidance and strategic advice to help attain project goals and maximize project outcomes. Additionally, the project evaluation employs mixed methods techniques to assess the effectiveness of the approaches used to support MTFs and examine the progress toward meeting project goals. Dissemination of project outcomes include presentations at professional conferences, regional professional workshops, and refereed publications. This Track 3: Master Teaching Fellowships 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.