This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems.
Projects
The project will develop and research an innovative model for rural science teacher professional development via technology-mediated lesson study (TMLS). This approach supports translating professional learning into classroom practice by developing a technology-based, social support system among rural teachers.
This study will further the field's understanding of the role that science teachers play in adapting their instruction during a public health crisis, how they address emergent ideas throughout the unfolding of the pandemic, and the impacts that the pandemic has had on science teachers themselves.
The focus of this project is the design of learning experiences in different high school science courses to help students gain experience in computational thinking. The project uses a partnership between two universities and school district to develop and refine the units as a collaboration between researchers, teachers, and school leaders. The goal is to help all students have opportunities to learn about computational thinking in multiple science courses.
This project examines the effect of an assessment system that automatically generates feedback based on students’ open-ended assessment responses in chemistry and physics consistent with a previously-developed learning progression that describes the successively more complex understandings students can develop about electrical interactions. The scoring system will provide individualized feedback to students and class summaries to their teachers.
EarthX is a design-based research project that supports the integration of Earth science into high school biology, chemistry, and physics courses in Baltimore City Public Schools, while also supporting the district’s transition to three-dimensional (3D), ambitious and equitable science teaching aligned with the Next Generation Science Standards (NGSS). EarthX builds on the success of the Integrating Chemistry and Earth Science (ICE) DRK-12 project, which developed innovative chemistry course curriculum materials and PD strategies, to support Earth science integration into biology and physics course curriculum development and 3D teaching. EarthX will develop, test, and refine embedded and unit assessments for all three courses, along with providing an online system for assessment administration; real-time reporting to teachers and students; and provision of data to PD leaders, administrators, and researchers for multiple purposes. Assessments will be 3D, featuring core concepts from both Earth science and the course discipline combined with a science or engineering practice and a crosscutting concept.
This project aims to restructure middle school science education around Grand Challenges (GCs) such as pandemics, climate events, and diminishing biodiversity. Anchoring science education around grand challenges can motivate students learning and provide a meaningful context for science curriculum and assessment. By engaging in the units around GCs, middle school science teachers and students will have opportunities to work with real data, engage in argumentation based on evidence, and take part in solutions to the grand challenges.
This project will develop and test a learning progression for middle school physical science that incorporates the three dimensions identified in Next Generation of Science Standards (NGSS): the Disciplinary Core Ideas of matter, interaction, and energy; the Science and Engineering Practices of constructing explanations and developing and using models; and the Crosscutting Concepts of cause and effect and systems and system models. Bringing together all three NGSS dimensions is an innovation that allows for the project to explore the variety of learning pathways that students may follow as they apply scientific knowledge and practices to make sense of compelling phenomena or solve complex problems.
One crucial predictor of success in STEM disciplines is spatial reasoning ability, which involves mentally manipulating and representing objects in space. However, STEM courses often neglect the purposeful development of spatial reasoning skills, and limited knowledge exists on effective training methods. This project aims to address this gap by: 1) identifying neural and cognitive processes associated with successful mental rotation, a fundamental aspect of spatial reasoning; 2) assessing the responsiveness of these processes to training; and 3) measuring the transfer of training effects to real-world STEM problems, specifically focusing on introductory chemistry.