Analysis of a Teaching School Model for Improving STEM Undergraduate Teacher Education and Professionalism

Regents Of The University Of Michigan - Ann Arbor, Ann Arbor MI

Investigators

Abstract

With support from the NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE: EHR), this project serves the national interest by expanding the number of well-prepared STEM majors who choose careers in urban STEM teaching. An important national priority is to provide all young people in US schools with STEM teachers of the highest caliber. To be fully successful, urban STEM teachers must have deep STEM knowledge, the ability to translate STEM knowledge and practices into something young people can understand, and deep understanding of urban environments and youth. To prepare the next generation of highly-skilled, urban STEM teachers at scale requires new ways of attracting, preparing, and retaining teachers. A team of researchers and educators from the University of Michigan and the Detroit Public Schools Community District seeks to bring about substantive institutional-level changes in how undergraduate STEM majors at the University are recruited and prepared to be STEM teachers. At the core of this project is the design and implementation of a "Teaching School," which draws upon the best dimensions of the Teaching Hospital Model to prepare novices for skilled and contextually sensitive professional practice. During students' college and early teaching years, the Teaching School will provide an immersive teaching practice in a shared urban school setting. It is expected that this experience will enhance the pre- and in-service teachers' professional skills and professional identities as teachers. An associated research study will examine the success of the Teaching School Model. Thus, the project has the potential generate new knowledge about how alignment of university and secondary school systems can support the preparation of skilled teachers who can provide rigorous STEM teaching for all students. In the project's Teaching School, undergraduate STEM majors enrolled in the University's secondary teacher education program ("Interns") will learn to teach using sophisticated inquiry-based and student-centered approaches. This learning will occur as the Interns teach alongside one another, with guidance from expert teachers ("Attending Teachers") and university-based teacher educators ("Attending Teacher Educators"). As they move through the three-semester training program, the Interns will take on increasingly higher levels of responsibility. After graduation and certification, they will have paid "Residencies," with continued mentoring by Attending Teachers and Attending Teacher Educators. This project will employ design-based research methods and process evaluation across iterative cycles of work and multiple institutions to support and study the implementation of the Teaching School. The project will examine: 1) how STEM undergraduates' learning is related to and supported by institutional structures, practices, and tools; 2) how STEM teachers trained in the Teaching School contribute to adolescents' STEM learning; and 3) the sustainability and practical value of the Teaching School model. The analysis intends to improve the teacher-training model, establish a proof of concept, and generate new knowledge about how undergraduate STEM pre-service teachers can be recruited and supported to provide equitable and rigorous STEM teaching through the transformation and alignment of university and secondary systems. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the IUSE Institutional and Community Transformation track, the program supports efforts to transform and improve STEM education across institutions of higher education and disciplinary communities. 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.