This project developed a system of practical measures, and associated routines and data visualizations, to support the implementation of instructional improvement strategies (e.g., coaching) in middle-grades mathematics teaching. Classroom and professional learning measures assess students’ and teachers’ perspectives of key aspects of the learning environment, respectively. We will highlight the contributions they have made to our partner districts’ improvement efforts; and our attention to validity in the design and use of practical measures.

The Researching Order of Teaching project provides structured scaffolds for teachers to implement two sets of research-based teaching strategies hypothesized to positively impact mathematics achievement in mathematical modeling and problem solving. The poster summarizes the teaching strategies and associated research.

The aim of this project is to develop and test the efficacy of a play-based numeracy intervention for preschool classrooms. Classrooms were randomly assigned to two experimental conditions (representing different pedagogical guidance approaches) and a business-as-usual control condition. Teachers in experimental classrooms were trained to incorporate a set of numeracy games. The intervention was assessed by pre- and post-test measures of teachers and children, 11 structured observations, and focus group data.

The Deep Structure Modeling (DSM) project addresses the pressing need to more effectively organize science teaching and learning around “big ideas” that run through disciplines. The project focus on developing knowledge around how centering science instruction on big ideas can position students in epistemically meaningful scientific evaluation, through synthesizing big ideas from phenomena and using big ideas as tools to analyze phenomena.

The rock cycle is rarely taught in conjunction with plate tectonics. The method of studying images of rock outcrops is not enough to explain how rocks are formed and transformed over time. This project has developed a simulation for students to investigate the formation and evolution of rock sequences created under specific tectonic conditions. By bridging the tectonic system and the rock genesis system, students engage in scientific practices that are authentic to how geoscientists’ work.

Computational thinking (CT) is critical in all STEM fields, but it is typically not integrated in STEM courses beyond computer science. To address this gap, our project team is developing a month-long CT-intensive biology unit, where students learn to program a robotic gripper to respond to changes in their electrical muscle activity. This provides a novel, interdisciplinary, and real-world context for students to develop their CT.

The project aims to build foundational knowledge about teacher learning to notice teaching and student thinking in new ways by using video clips of science instruction within a professional development context. Professional development is centered around the analysis of video clips depicting the implementation of three-dimensional performance assessments in science classrooms, and draws on cognitive science to enhance teacher learning from video (these include contrasting cases and self-explanation principles).

This project examines the efficacy of the Model-Based Educational Resource (MBER) for high-school biology teachers and students. Previous work on MBER has found that the materials support teachers in providing opportunities for engaging student sensemaking and modeling, are feasible to implement in diverse classroom contexts, and show promise of efficacy in increasing student achievement. With this project we are generating causal evidence investigating how this approach to teaching and learning supports Next Generation Science learning.

This project examines the efficacy of the Model-Based Educational Resource (MBER) for high-school biology teachers and students. Previous work on MBER has found that the materials support teachers in providing opportunities for engaging student sensemaking and modeling, are feasible to implement in diverse classroom contexts, and show promise of efficacy in increasing student achievement. With this project we are generating causal evidence investigating how this approach to teaching and learning supports Next Generation Science learning.

This project explores how children in grades K-2 understand visual representations of algebraic concepts. For instance, children create tables or graphs to organize information about the relationship between two quantities. They might use graphs and diagrams to explain their mathematical thinking and develop their understanding of relationships in numbers and operations. The project uses data gathered in K-2 classrooms and via interviews with children to describe their use of the visual representations.