Projects

This project will build on prior funding to design a next generation diagnostic assessment using learning progressions and other learning sciences research to support middle grades mathematics teaching and learning. The project will contribute to the nationally supported move to create, use, and apply research based open educational resources at scale.

Understanding Science provides an accurate portrayal of the nature of science and tools for teaching associated concepts. This project has at its heart a public re-engagement with science that begins with teacher preparation. To this end, its immediate goals are (1) improve teacher understanding of the nature of the scientific enterprise and (2) provide resources and strategies that encourage and enable K-16 teachers to incorporate and reinforce the nature of science throughout their science teaching.

Building Base Line Objectives for Children’s Knowledge Skills for Science (BLOCKS)is a 4-year project that integrates research and applied teaching to take a close look inside prekindergarten classrooms. The overall research project includes extensive classroom observation by teachers and researchers of children’s ability to learn science processes and content; intensive professional development and mentoring support for teachers to learn science; and multiple qualitative, as well as, quantitative assessment strategies.

The growing importance of data, data science and artificial intelligence (AI) in education, work, and personal and civic life has increased the need for all U.S. students to develop data literacy, statistical reasoning, and computational thinking skills. However, most middle school students—especially those with learning disabilities (SLD)—receive limited or no instruction in these areas. Data science and AI instruction is often limited to high school settings, narrowly framed within mathematics or science, and rarely designed with the flexibility to support learner variability. The purpose of this project is to develop and refine Data Adventures, a series of open-access, modular, and instructional experiences units designed to introduce middle school students to data literacy, computational thinking, and digital storytelling, while also promoting critical understanding of AI and its role in education, work technology, and everyday life.

This project will use visualizations from an easily accessible tool from NOAA, Science On a Sphere, to help students develop critical thinking skills and practices required to effectively make meaning from authentic scientific data. The project will use arts-based pedagogies for observing, analyzing, and critiquing visual features of data visualizations to build an understanding of what the data reveal. The project will work with middle school science teachers to develop tools for STEM educators to use these data visualizations effectively.

This project will develop and test the impact of heredity and evolution curriculum units for middle school grades that are aligned with the Next Generation Science Standards (NGSS). The project will advance science teaching by investigating the ways in which two curriculum units can be designed to incorporate science and engineering practices, cross-cutting concepts, and disciplinary core ideas, the three dimensions of science learning described by the NGSS. The project will also develop resources to support teachers in implementation of the new modules.

This project augments an NCES data collection effort for the High School Longitudinal Study by including 150 additional schools in up to 10 selected states to create state representative samples of at least 40 schools in each state. The purpose of this augmentation is to provide support for additional schools to create state samples. NSF will also be involved in planning for future surveys of these students as they reach college age.

This project aims to enact and study the co-design of classroom activities by mathematics and visual arts teachers to promote middle school students' data literacy.

The aim of this project is to enact and study a process in which middle school teachers of mathematics and visual arts co-design and teach activities that combine math and art to teach data science.

The aim of this project is to enact and study a process in which middle school teachers of mathematics and visual arts co-design and teach activities that combine math and art to teach data science.

Transdisciplinary science integrates knowledge across STEM disciplines to research complex challenges such as climate science, genetic engineering, or ecology. In this project, teachers and students will design smart greenhouses by connecting electronic sensors that can detect light or other environmental data to microcontrollers that can activate devices that water plants and regulate other environmental factors such as temperature or light. This activity brings together engineering, computer science, and horticulture. Working across urban and rural contexts, the project will engage teachers in professional development as they adopt and adapt instructional materials to support their students in learning across disciplines as they build smart greenhouses.

Transdisciplinary science integrates knowledge across STEM disciplines to research complex challenges such as climate science, genetic engineering, or ecology. In this project, teachers and students will design smart greenhouses by connecting electronic sensors that can detect light or other environmental data to microcontrollers that can activate devices that water plants and regulate other environmental factors such as temperature or light. This activity brings together engineering, computer science, and horticulture. Working across urban and rural contexts, the project will engage teachers in professional development as they adopt and adapt instructional materials to support their students in learning across disciplines as they build smart greenhouses.

Rapid changes in computing, especially with advances in artificial intelligence, are reshaping the future needs of society and the demands on the STEM workforce. More than ever, computer science (CS) education is critical for all children. Many schools are looking for ways to introduce CS skills and thinking in the elementary grades. Whereas some initiatives have focused on coding as its own endeavor, not integrated with subjects like mathematics, science, or literacy, developers and researchers are increasingly exploring ways that programming and computational thinking (CT) can be integrated into core content. This project will design and study resources that build teacher capacity to integrate CS/CT into mathematics by building on the investigators' prior work developing integrated Math+CS modules in grades 2-5.

This project has pioneered simulation-based assessments of model-based science learning and inquiry practices for middle school physical and life science systems. The assessment suites include curriculum-embedded, formative assessments that provide  immediate, individualized feedback and graduated coaching with supporting reflection activities as well as summative end-of-unit benchmark assessments. The project has documented the instructional benefits, feasibility, utility, and technical quality of the assessments with over 7,000 students and 80 teachers in four states.

STEM learning is a function of both student level and classroom level characteristics. Though research efforts often focus on the impacts of classrooms level features, much of the variation in student outcomes is at the student level. Hence it is critical to consider individual students and how their developmental systems (e.g., emotion, cognition, relational, attention, language) interact to influence learning in classroom settings. This is particularly important in developing effective models for personalized learning. To date, efforts to individualize curricula, differentiate instruction, or leverage formative assessment lack an evidence base to support innovation and impact. Tools are needed to describe individual-level learning processes and contexts that support them. The proposed network will incubate and pilot a laboratory classroom to produce real-time metrics on behavioral, neurological, physiological, cognitive, and physical data at individual student and teacher levels, reflecting the diverse dynamics of classroom experiences that co-regulate learning for all students.

Advancing Reasoning addresses the lack of materials for teacher education by investigating pre-service secondary mathematics teachers' quantitative reasoning in the context of secondary mathematics concepts including function and algebra. The project extends prior research in quantitative reasoning to develop differentiated instructional experiences and curriculum that support prospective teachers' quantitative reasoning and produce shifts in their knowledge.

This project is developing an 8th-grade assessment for proportional reasoning from a cognitive diagnosis model (CDM) framework. CDMs are psychometric models developed specifically for diagnosing the presence or absence of fine-grained skills or processes required in solving problems on a test. Assessments based on CDMs can provide information deemed more diagnostic and descriptive, and therefore, more relevant in applied instructional settings.

This project will investigate whether six urban middle schools are implementing highly effective science, technology, engineering and mathematics (STEM) programs based on factors identified through relevant research and national reports on what constitutes exemplary practices in 21st century-focused schools.

Three-dimensional figures can now be represented as diagrams that appear to extend into space in ways that are free of material or physical constraints. They can be rendered at any size, in any orientation, and at any position in space, and can thereby realize a far more varied set of mathematical concepts than what is possible with physical models. The goal of this project is to investigate the transformative educational potential of these representations and to generate a knowledge base that teachers, teacher educators, and researchers can use to reimagine the learning and teaching of geometry.

This project seeks to investigate the possibilities and challenges of using a participatory approach to research and design, centering Black, Indigenous, Latinx, and Hmong students and their families in imagining and creating change. The project will generate new knowledge about the possibilities and limitations of participatory design research (PDR) as a method for advancing equity in mathematics education through PDR cycles at three middle schools over the five years of the project. This approach has the potential to disrupt inequitable practices of mathematics education as well as undemocratic processes for making decisions about mathematics education. Further, it will be a catalyst for developing racially just practices and processes in mathematics education.

This project will contribute new knowledge on two aspects of participation in mathematics education. First, this research aims to understand how perceptions of race influence how teachers, future teachers, and researchers assess how bilingual children use their languages and movement to participate in mathematical activity. Second, it will explore ways to counter deficit views that influence teachers’, preservice teachers’, and researchers’ perceptions of these multiple ways of participating as inferior to what is traditionally considered as meaningful participation.

The goal of this CAREER program of research is to identify, from a cross-cultural perspective, essential Algebraic Knowledge for Teaching (AKT) that will enable elementary teachers to better develop students' algebraic thinking. This study explores AKT based on integrated insights of the U.S. and Chinese expert teachers' classroom performance.

This study seeks to describe trajectories that describe the ways in which Black learners develop as particular kinds of mathematical learners. The study takes place in the context of an established, multi-year college bridge program that has as its goals to increase the representation of historically marginalized groups in the university community.

This project studies teaching practices in a year-long high school algebra course that integrates hand-held and other electronic devices. Of particular interest is how these technologies can support learners' capacity to efficiently and effectively draw on the distributed intelligences that technical and social networks make available. The investigation focuses on collaborative learning tasks centered on collective mathematical objects, such as functions, expressions, and coordinates that participants in a group must jointly manipulate through networked computers.

Covariational reasoning, or the ability to reason about relationships as quantities change together, is one way of thinking that can provide a foundation for students to build their more abstract algebraic knowledge. This research builds a foundation for integrating education and research at the intersection of students’ developing algebraic knowledge, covariational reasoning, and new educational technologies to create a new path into algebra. This path can help remove barriers that have historically restricted access to mathematics and STEM coursework and careers.