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The University of Utah will develop a plan for a model curriculum and associated assessments project that integrates science practices, crosscutting concepts, and core disciplinary ideas through the integration of mathematics and science and the application of appropriate educational technologies. The unit plan and prototype lessons will model ways in which quantitative literacy and the Common Core Standards of Mathematics can be addressed in the biology curriculum.

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.

The goal of this planning grant is to explicitly focus on broadening participation in the K-12 STEM teaching workforce, with the theory of action that diversifying the K-12 STEM teaching workforce would in the long term help more students see STEM as accessible to them and then be more likely to choose a STEM degree or career.

This project will convene two workshops, held in 2015 and 2016, which will focus on developmental mathematics and other critical issues in mathematics education. The workshop will frame critical issues; draw attention to issues of diverse participation and success in mathematics; and provide images of productive engagement for participants to draw upon as they return to their professional communities.

This project will focus on a networked improvement community (NIC) model of professional learning that shifts K-5 science instruction from traditional approaches to a three-dimensional design as outlined in the Next Generation Science Standards. The project will feature a multi-level model involving university educators and researchers and school district practitioners in an effort to co-defined problems of practice valuable to both parties. A mixed methods research design will examine how the NIC model develops professional capital through changes in implementation over multiple iteration.

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.

This grant is also known as The Responsive Math Teaching Project: Developing Instructional Leadership in a Network of Elementary Schools.

The goal of this project is to build instructional leadership capacity in teachers and school-based leaders in a network of underperforming elementary schools with limited resources. Through design-based improvement research, the project is designed to enhance the knowledge, skills, and competencies of elementary teacher leaders and principals to develop a shared vision and provide ongoing support of high-quality math instruction.

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.

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 will develop a sustainable Research-Practice Partnership (RPP) model between the Worcester Public Schools (WPS) and the Learning Sciences Lab at Worcester Polytechnic Institute (WPI). Together, WPI and WPS will build the collaborative infrastructure for conducting impactful STEM education research within WPS. Specifically, the RPP will establish and document shared infrastructural systematic processes and materials, brainstorm and facilitate research ideas that address pressing issues in mathematics education, and build a community of trust among researchers, administrators, teachers, and families to make future research and implementation, innovation, and collaboration more impactful, accessible, and efficient.

Teachers are extraordinarily important to student learning, but researchers have surprisingly little data about what teachers do moment-to-moment with students. What are the instructional moves and improvisational responses that characterize highly effective practice? To better understand and support U.S. K-12 STEM teachers, this Incubator project will develop a network of "tutor observatories." Tutor observatories are learning environments that record teacher engagements with students along with information about the context of the interaction. From these data, researchers will be able to gain a deeper understanding of STEM teacher practice, identify highly effective practices, and develop training data that can inform a new generation of artificially intelligent tools to support teachers and student learning.

Teachers are extraordinarily important to student learning, but researchers have surprisingly little data about what teachers do moment-to-moment with students. What are the instructional moves and improvisational responses that characterize highly effective practice? To better understand and support U.S. K-12 STEM teachers, this Incubator project will develop a network of "tutor observatories." Tutor observatories are learning environments that record teacher engagements with students along with information about the context of the interaction. From these data, researchers will be able to gain a deeper understanding of STEM teacher practice, identify highly effective practices, and develop training data that can inform a new generation of artificially intelligent tools to support teachers and student learning.

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.