This project aims to serve the national need for teaching and learning data literacy in teacher education. Data literacy is important for foundational STEM learning, civic engagement, and democratic decision-making. Moreover, Common Core Math Standards and the Next Generation Science Standards prioritize teaching data-rich inquiry. The proposed project will redesign teacher training courses to help future teachers learn how to develop students’ disciplinary thinking and ability to communicate with data. The project will focus on building a community of teacher graduates who are committed to teaching socially relevant STEM data literacy in high-need schools in urban and rural school districts.
This project at the University of California, Berkeley, includes partnerships with: the University of California, Merced; Oakland Unified School District; Berkeley Unified School District; West Contra Costa Unified School District; Merced City School District; Lawrence Hall of Science; Exploratorium; California Academy of Science; Chabot Space & Science Center; Kids Discovery Station Merced; and Mission Science Workshop. Project goals are to provide scholarships to 65 pre-service teachers (upper-division undergraduates and STEM post-baccalaureates) over five years, and offer paid summer internships at informal-education institutions and classroom-intensive externships for 90 lower-division STEM undergraduates. The project will also guide teacher leadership development of ten in-service teachers, and perform a longitudinal study with a focus on teacher diversity and retention. The rise of publicly available data, the many new forms of data, and purposes for which data are collected and analyzed, create a markedly new context for STEM teachers. Although this proliferation of data offers new opportunities, it also poses new challenges in developing culturally relevant, scientifically sound pedagogies. This project will design novel curricula and professional development for pre-service teachers that focus on data science, to support them in developing the capacity to innovate their students’ use of data to address a range of STEM content and complex questions. This Track 1: Scholarships and Stipends 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 STEM teachers to become STEM master teachers in high-need school districts. It also supports research on the persistence, retention, and effectiveness 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.
