There have been prominent and widespread calls for high school science students to work with data in more complex ways that better align with and support the work of professional scientists and engineers. However, high school students' analysis and interpretation of scientific data is often limited in scope, complexity, and authentic purpose. This project aims to support and advance students' work with ecological data in high school biology classrooms by embracing a new approach: Bayesian data analysis methods. Such methods involve expressing initial ideas or beliefs and updating them quantitatively with data that students access or record. This project will empower 20 high school teachers and their approximately 1,200 students to make sense of data within and beyond classroom contexts. It also will involve sharing research findings, an educational technology tool for Bayesian data analysis, and curricular resources in open and accessible ways.
Projects
This project will study learning associated with elementary teachers' engagement in professional learning and elementary students' learning related to quantum science, quantum thinking, and careers. The knowledge base required for elementary teachers and students to learn quantum will be identified in order to explore and compare how elementary students and teachers conceptualize and make sense of quantum science concepts.
This exploratory study aims to design, implement, and test climate science and history professional learning materials and experiences for high school teachers. By leveraging existing science and history/social science materials, the program will develop curricular planning tools and lessons to help teachers integrate climate literacy into their instructional units. The goal is to provide students with the knowledge to understand and respond to the social and environmental issues associated with the climate crisis.
Early childhood educators (ECEs) understand that effective science teaching and learning requires content knowledge related to science concepts and practices and pedagogical knowledge. However, ECEs, especially in rural communities, express a lack of science content knowledge and confidence in incorporating science-related conversations in their early care and education settings, and they believe this might be a result of limited professional training relevant to science content. This project aims to strengthen key capabilities in ECEs, including the ability to (1) build science content knowledge and confidence in guiding young children's scientific investigation, (2) closely observe children's interactions with science materials, and (3) use those observations in the reflection, planning, and practice of science teaching.
This research study examines the potential of integrating student-driven descriptive investigations of complex multivariate civic datasets into middle school social studies classrooms. It uses a collaborative co-design process to develop data-rich experiences for the social studies classroom crafted to 1) deepen students' data literacy, 2) develop students' sense of efficacy in working with civic data sets, and 3) create learning experiences that connect data to local problems that have meaning for students and their communities.
High-quality early educational experiences, particularly in mathematics, are crucial for students’ success in K-12 schooling. To create these foundational experiences for young children, early childhood educators need opportunities to enhance their mathematics teaching through job-embedded, sustained professional learning. This partnership development project establish a collaboration among early childhood mathematics educators, school and district leaders, the state department of education, and university faculty in Delaware that aims to enhance children’s early mathematics learning by collaboratively designing support systems for strengthening their teachers’ professional learning.
Research has shown that when teachers have strong content and pedagogical content knowledge that they can provide better quality mathematics instruction to their students and improve student outcomes. The goal of this project is to enhance elementary school teachers’ capacity to improve students’ mathematics learning through a scaled professional development program that uses artificial intelligence (AI) to create a personalized, active learning environment for teachers.