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ABSTRACT Research Experiences for Teachers (RET) programs are a burgeoning approach to engage teachers in STEM (science, technology, engineering, mathematics) research that they can translate into their K‐12 classrooms. Despite an increase in studies of RETs, there is a need for comparison of RET and non‐RET teachers' student outcomes. This mixed methods, quasi‐experimental comparison study, using a revised third‐generation activity theory framework, investigates how an RET program for preservice and early career STEM teachers impacted participating teachers and their students up to 8 years after RET participation. Specifically, we conducted a matched comparison of student achievement data from students of nine RET teachers versus many non‐RET comparison teachers within the same districts (n = 830–1132 students). We also investigated student and teacher perceptions of classroom practices through surveys (n = 576 students) and interviews (15 teacher interviews). Omnibus tests revealed no statistically significant differences by treatment in math or science achievement. However, students of the RET teachers reported stronger perceptions of STEM career awareness, greater value for learning STEM subjects, and a greater propensity to persist in STEM course tasks (three of the five constructs measured). This was consistent with teacher interview responses in which RET teachers spoke about STEM career awareness in a broader context for understanding the value of STEM in society, and also discussed struggles in research and attempts to bring this mindset to their students, which may have resulted in greater student engagement in their courses. Implications for teacher education and for supporting science and engineering practices in STEM classrooms are discussed along with recommendations for further research on the impacts of RET programs guided by a revised third‐generation activity theory framework informed by this work.more » « lessFree, publicly-accessible full text available January 2, 2026
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Jansen, Peter; Smith, Kelly J.; Moreno, Dan; Ortiz, Huitzilin (, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing)
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