The Journal of Emerging Investigators provides middle and high school students an opportunity to participate in a peer review and publication of their original manuscript.
This project will study the aspects of genetics instruction that affect students' beliefs in gender essentialism, which is implicated in lowering girls' sense of STEM abilities, feeling of belonging in STEM classes, and interest in pursuing further education in STEM fields. The goal of the project is to answer important questions about how to teach genetics at the high school level in a manner that is scientifically accurate but does not have these detrimental side effects.
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 builds on existing work on three-dimensional learning progressions in high school physical sciences to develop an artificial intelligence supported scoring system for student text and models. These tools will be used to support learning of electrical forces in an integrated curriculum with real-time feedback on formative assessment items. We report on early attempts to design coding rubrics for automatic scoring of explanations and modeling responses and outcomes of developing text classification models.
In this project, we are developing strengths-based formative assessment tools to support students’ use of the crosscutting concepts (CCCs) in phenomenon-based science learning. We have used the practice of Developing and Using Models as a window into student use of the CCCs, co-developing instructional supports with participating teachers. We are now connecting these supports to aspects of the formative assessment process (e.g., visualizing success, eliciting evidence of student thinking, providing feedback, and cultivating student self-assessment).
