Modeling for Understanding Physical Phenomena and Engaging Pre-Service Teachers in Science

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This project aims to serve the national interest by preparing elementary school teachers to integrate model-based inquiry into the curriculum to enhance student learning of science. In elementary schools, science is often taught utilizing English language arts best practices. Children read about and memorize science facts instead of engaging in science practices to develop scientific knowledge. In efforts to build prospective elementary science teacher understanding of, ability to, and preparedness for teaching using model-based inquiry (MBI) the project aims to situate MBI into a physical science course. The Modeling for Understanding Physical Phenomena and Engaging Teachers in Science (MUPPETS) project will develop a physical science course for prospective elementary teachers (to be taken prior to the science education methods course) in which the preservice teachers are learners of science in an environment that utilizes science education research-based pedagogical approaches. Pre-service teacher gain experience learning science using techniques well suited for elementary students and in accordance with the Next Generation Science Standards. When prospective elementary teachers enter the science education methods course, the physical science course experience is a familiar context to draw upon, an opportunity not typically found in elementary education teacher preparation programs.The purpose of the MUPPETS project is to determine how prospective elementary teachers engage with model-based inquiry (MBI) that centers on gathering and making sense of data and peer-to-peer discourse. More specifically, this project seeks to understand how making sense of phenomena through collaborative discussions influences the composition and substance of models and explanations across model iterations to establish the impact on their understanding of (1) physical science, science, and universal epistemological views; (2) meta-modeling knowledge; and (3) modeling practice. Data is analyzed using a mixed-methods approach employing a quantitative analysis of pre-and post-survey data to assess prospective elementary teachers’ views of knowledge (epistemology) and meta-modeling knowledge before and after engaging in MBI. The qualitative data component of the research includes the observed written explanations and think-aloud protocol to characterize types of modeling practice that pre-service elementary teachers use to explain phenomena through the visual, written, and oral representations they create across five sets of iterative models. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Partial funding is from the Robert Noyce Teacher Scholarship program. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.