Projects

This collaborative project is developing instruments to assess secondary teachers' Mathematical Habits of Mind (MHoM). These habits bring parsimony, focus, and coherence to teachers' mathematical thinking and, in turn, to their work with students. This work fits into a larger research agenda with the ultimate goal of understanding the connections between secondary teachers' mathematical knowledge for teaching and secondary students' mathematical understanding and achievement.

The American Museum of Natural History in New York City, in partnership with New York University, and in collaboration with five high-needs schools, is developing, implementing, and researching a five-year pilot Master of Arts in Teaching (MAT) program in Earth Science. The program is delivered by the Museum's scientific and education teams and its evaluation covers aspects of the program from recruitment to first year of teaching.

This project will study the activities of a Networked Improvement Community (NIC) as a vehicle to bridge gaps across four identified steps along the science teacher training and development pathways within local contexts of 8 participating universities. The overarching goal of the project is to strengthen the capacity of universities and school districts to reliably produce teachers of science who are knowledgeable about and can effectively enact the Next Generation Science Standards (NGSS), although prepared in varied organizational contexts.

The Framework for K-12 Science Education has set forth an ambitious vision for science learning by integrating disciplinary science ideas, scientific and engineering practices, and crosscutting concepts, so that students could develop competence to meet the STEM challenges of the 21st century. Achieving this vision requires transformation of assessment practices from relying on multiple-choice items to performance-based knowledge-in-use tasks. However, these performance-based constructed-response items often prohibit timely feedback, which, in turn, has hindered science teachers from using these assessments. Artificial Intelligence (AI) has demonstrated great potential to meet this assessment challenge. To tackle this challenge, experts in assessment, AI, and science education will gather for a two-day conference at University of Georgia to generate knowledge of integrating AI in science assessment.

Data science is fast becoming a dominant part of scientific, economic, and social scientific reasoning, as well as a necessary perspective for making life decisions that rely on data. But there is little work in either research or development with students younger than 2nd grade, and even less focusing on children not yet in kindergarten. By expanding knowledge in an emergent content area where young children are currently underserved, this set of three workshops will build capacity to create rigorous, equitable, inclusive, and culturally responsive data science teaching resources, a necessity for school readiness in the early childhood years.

This project will examine how partnerships among state science leaders, education researchers and education practitioners cultivate vertical coherence and equity in state science education.

This project will synthesize existing literature on modeling-based instruction (MBI) in K-12 science education over the last three decades. It will rigorously code and examine the literature to conceptualize the landscape of the theoretical frameworks of MBI approaches, identify the effective design features of modeling-based learning environments with an emphasis on technology-enhanced ones, and identify the most effective MBI practices that are associated with successful student learning through a meta-analysis.

Today’s schools are experiencing increasing cultural and linguistic diversity and facing the challenge of creating meaningful connections between school science and student lived experiences outside of school. Middle school is a critical time to provide fundamental knowledge and encourage interest in STEM careers. In order to best impact learners during this critical period, science teachers need improved models to support the development and delivery of relevant curriculum materials to better serve all students in their classrooms. Highly supported design teams consisting of researchers, teachers, and both school and district science specialists will co-adapt existing district-generated science units to integrate socially and culturally relevant science practices and draw on students' diverse cultural and language practices as strengths.

The Elementary Mathematical Writing (EMW) Task Force was made up of educators with unique perspectives about elementary mathematical writing and with the goal to reach a consensus about and priorities for the types of and purposes for elementary mathematical writing. The EMW Task Force met in October 2015, analyzed elementary writing prompts and samples, standards documents, and recommendations, and identified four types of mathematical writing and their associated purposes: Exploratory, Informative/Explanatory, Argumentative, and Mathematically Creative.

This project brings together education researchers, high school science teachers, research scientists, and community-based organizations as co-design teams to modify science curriculum materials to be justice- and community-oriented. Building on existing partnerships between education researchers and 11 science teachers in two districts in Illinois, project teams will engage in cycles of curriculum analysis and adaptation over the course of 3 years. These professional learning cycles will develop pedagogically relevant content expertise, such as deepened understanding of locally relevant science phenomena, as well as infrastructure for community-engaged science instruction.