The aim of this NSF ECR project is to perform an extensive multi-method metasynthesis of literature published between 2011 and 2023 on strategies for enhancing undergraduate STEM instruction. Specifically, we update the previous review and examine the change strategies implemented after a decade of research. We present an updated methodology with the innovative application of machine learning methods to select and analyze articles. From initially determined potentially relevant articles (n = 9,262) from keyword search, 253 articles were included after the title and abstract and full-text screening. Subsequently, we conducted both human qualitative coding and quantitative machine learning analyses to examine the themes of the included articles. Preliminary findings from the qualitatively coding showed that most articles implemented a dissemination change strategy focusing on telling or teaching individuals about new teaching practices; the predominant target for disseminating pedagogy was individual faculty and developing reflective teachers-focused strategies, whereas departments and institutions tended to be the target for developing a policy or a shared vision. Additionally, preliminary findings from the quantitative machine-learning clustering analyses showed groupings related to specific science disciplines (e.g. engineering, chemistry). Next steps of the project are discussed.
The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025