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�鶹��ý���� Department of Mathematical Sciences Assistant Professors Eileen Murray and Joseph DiNapoli will be leading a team of researchers on a project funded by a four-year $1.7 million National Science Foundation (NSF) Discovery Research PreK-12 (DRK-12) grant.

Each year, the NSF awards a small number of DRK-12 grants to projects that have the potential to transform the education system. �鶹��ý���� researchers have received $532,224 for the project “Building a Teacher Knowledge Base for the Implementation of High-quality Instructional Resources through the Collaborative Investigation of Video Cases.”

The prestigious DRK-12 grant was awarded to researchers at �鶹��ý����, the State University of New York at Buffalo and DePaul University, who will collaborate with Math for America, the New York State Master Teacher Program and the DePaul University STEM Center, on a Math of America teachers-based project.

Established in 2004, Math for America is committed to improving teacher retention by building and supporting communities of outstanding STEM educators. Its innovative video library, which features Math for America teachers using high-quality math lesson plans in their classrooms, is central to the team’s project.

The researchers will address the pressing national need to generate shared, classroom-based knowledge about how to implement freely available, quality instructional resources that can improve student learning outcomes.

The funding will also give teachers a unique window into one another’s classrooms by supporting teacher-leaders in different U.S. cities as they execute lesson plans, create new videos for the Math for America video library and seek to understand how to teach more effectively.

“In this innovative professional development model, teachers use videos to break down complex teaching situations and think about what can be improved,” says Murray. “It’s similar to how professional athletes use video to review what worked and what didn’t in games.”

By studying what teachers learn and how they share that knowledge with others, the �鶹��ý���� team aims to learn how the model might ultimately be scaled nationwide.