Projects

This project builds on a prior study that demonstrated increases in students' knowledge of argumentation and their performance on mathematics assessments. The project will extend the use of the argumentation intervention into all eighth grade content areas, with a specific focus on students' learning of reasoning and proof, and contribute to understanding how students' learning about mathematical practices that can help them learn mathematics better.

This project examines relationships among pre-service teachers' developing understanding of learning in mathematics and science, the enactment of these understandings as they begin teaching. The objectives are (1) to inform the design of teacher preparation programs, and (2) to support the development of appropriate tools to assess the impact of teacher preparation program features on elementary- and middle-school student learning.

EDC is developing a high school capstone course in linear algebra. Student resources contain a core semester that develops two- and three-dimensional geometry using vectors and that treats matrix algebra and its applications to geometry; a semester of material that completes a typical undergraduate course (exploring bases, determinants and eigentheory); and 5 stand-alone modules that develop applications of this core to mathematics, engineering, science, and other STEM fields.

This project aims to support the mathematics learning of students with disabilities through the development and use of mixed reality simulations for elementary mathematics teacher preparation. These simulations represent low-stakes opportunities for preservice teachers to practice research-based instructional strategies to support mathematics learning, and to receive feedback on their practices.

This project aims to support the mathematics learning of students with disabilities through the development and use of mixed reality simulations for elementary mathematics teacher preparation. These simulations represent low-stakes opportunities for preservice teachers to practice research-based instructional strategies to support mathematics learning, and to receive feedback on their practices.

The core research questions of the project are: (1) What is the nature of high-leverage student thinking that teachers have available to them in their classrooms? (2) How do teachers use student thinking during instruction and what goals, orientations and resources underlie that use? (3) What is the learning trajectory for the teaching practice of productively using student thinking? and (4) What supports can be provided to move teachers along that learning trajectory?

The core research questions of the project are: (1) What is the nature of high-leverage student thinking that teachers have available to them in their classrooms? (2) How do teachers use student thinking during instruction and what goals, orientations and resources underlie that use? (3) What is the learning trajectory for the teaching practice of productively using student thinking? and (4) What supports can be provided to move teachers along that learning trajectory?

The core research questions of the project are: (1) What is the nature of high-leverage student thinking that teachers have available to them in their classrooms? (2) How do teachers use student thinking during instruction and what goals, orientations and resources underlie that use? (3) What is the learning trajectory for the teaching practice of productively using student thinking? and (4) What supports can be provided to move teachers along that learning trajectory?

LOCUS (Levels of Conceptual Understanding in Statistics) is an NSF Funded DRK12 project (NSF#118618) focused on developing assessments of statistical understanding. These assessments will measure students’ understanding across levels of development as identified in the Guidelines for Assessment and Instruction in Statistics Education (GAISE). The intent of these assessments is to provide teachers and researchers with a valid and reliable assessment of conceptual understanding in statistics consistent with the Common Core State Standards (CCSS).

This project is studying measurement practices from pre-K to Grade 8, as a coordination of the STEM disciplines of mathematics and science. This research project tests, revises and extends learning trajectories for children's knowledge of geometric measurement across a ten-year span of human development. The goal will be to validate all components of each learning trajectory, goal, developmental progression, and instruction tasks, as well as revising each LT to reflect the outcomes of the experiments.

This project will use classroom-based research to teach children about important algebraic concepts and to carefully explore how children come to understand these concepts. The primary goal is to identify levels of sophistication in children's thinking as it develops through instruction. Understanding how children's thinking develops will provide a critical foundation for designing curricula, developing content standards, and informing educational policies.

The purpose of this project is to test the efficacy of the Learning and Teaching with Learning Trajectories (LT2) program with the goal of improving mathematics teaching and thereby increasing young students' math learning. LT2 is a professional development tool and a curriculum resource intended for teachers to be used to support early math instruction and includes the mathematical learning goal, the developmental progression, and relevant instructional activities.

The COVID-19 pandemic has significantly disrupted the ability of teacher education programs to place their teacher candidates in typical K-12 teaching settings as a part of learning to teach. This project examines how simulated classroom field experiences for preservice teachers can be implemented in online and emergency remote teacher education courses.

Understanding probability is essential for daily life. Probabilistic reasoning is critical in decision making not only for people but also for artificial intelligence (AI). AI sets a modern context to connect probability concepts to real-life situations. It also provides unique opportunities for reciprocal learning that can advance student understanding of both AI systems and probabilistic reasoning. This project aims to improve the current practice of high school probability education and to design AI problem-solving to connect probability and AI concepts. Set in a game-based environment, students learn and practice applying probability theory while exploring the world of probability-based AI algorithms to solve problems that are meaningful and relevant to them.

Understanding probability is essential for daily life. Probabilistic reasoning is critical in decision making not only for people but also for artificial intelligence (AI). AI sets a modern context to connect probability concepts to real-life situations. It also provides unique opportunities for reciprocal learning that can advance student understanding of both AI systems and probabilistic reasoning. This project aims to improve the current practice of high school probability education and to design AI problem-solving to connect probability and AI concepts. Set in a game-based environment, students learn and practice applying probability theory while exploring the world of probability-based AI algorithms to solve problems that are meaningful and relevant to them.

This project is developing teaching modules that engage high school students in learning and using mathematics. Using geo-spatial technologies, students explore their city with the purpose of collecting data they bring back to the formal classroom and use as part of their mathematics lessons. This place-based orientation helps students connect their everyday and school mathematical thinking. Researchers are investigating the impact of place-based learning on students' attitudes, beliefs, and self-concepts about mathematics in urban schools.

In this project, researchers will collaborate to enhance understanding of influences on learning, and improve teaching and learning in high school and middle school STEM classes. They will leverage the latest tools for data processing and many different streams of data that can be collected in technology-rich classrooms to (1) identify classroom factors that affect learning and (2) explore how to use that data to automatically track development of students' understanding and capabilities over time.

This project will develop and study two sets of instructional materials for K-2 teacher professional development in mathematics and science that are aligned with the CCSS and NGSS. Teachers will be able to review the materials online, watch video of exemplary teaching practice, and then upload their own examples and students' work to be critiqued by other teachers enrolled in professional learning communities as well as expert coaches.

This project is testing the effectiveness of the 'Learning Assistant Model' for recruiting, preparing, and retaining STEM K-12 teachers by developing a suite of survey instruments that can be used by researchers interested in testing the effectiveness of teacher preparation programs, course transformations, or conceptual or pedagogical knowledge. It focuses on teacher certification programs,K-12 contexts and students' experiences in STEM departments and the role of STEM research faculty in preparing future teachers.

This project is creating five video-case modules for use in professional development of middle school mathematics teachers. The materials are designed to develop teachers' understanding of mathematics knowledge for teaching similarity. In total, 18-24 video cases will be produced, which, taken together, form the curriculum of a 45- to 60-hour professional development course.

To prepare the country's youth more broadly for a globalized world, the U.S. National Commission on Mathematics Instruction (USNCMI) will engage with the international community and assist in improving the state of mathematics education in the country by implementing international education programs, participating in international benchmarking activities, and working closely with other countries and multilateral organizations. 

This project tests and refines a hypothetical learning trajectory and corresponding assessments, based on the collective work of 50 years of research in mathematics education and psychology, for improving students' ability to reason, prove, and argue mathematically in the context of algebra. The study produces an evidence-based learning trajectory and appropriate instruments for assessing it.

This project is evaluating existing knowledge about STEM teachers in professional learning communities (PLCs), both prospective teachers and classroom teachers across grades K-12. It will comprehensively synthesize peer-reviewed research but will also examine additional types of knowledge that influence the field. The project methods adapt those of Knowledge Management and Dissemination project, funded by NSF MSP and seeks to further advance the scope and rigor of knowledge synthesis.

This project aims to improve professional development programs for pre-service teachers (PSTs) as a way to improve student learning in mathematics and science. PSTs engage in a series of teaching cycles, and then engage in lesson study groups to develop, teach, and analyze a whole-class lesson. The cycle is completed by reexamining students' knowledge in teaching experiments with pairs of students. These teaching cycles are called Iterative Model Building (IMB).

The objective of this study is to examine the impact of ITEAMS intervention strategies on student persistence in high school STEM course-taking and career expectations, and the value that students place on STEM careers.