This curriculum development and professional development program includes residential summer institutes with academic-year online communication for in-service teachers involved in professional development of their colleagues. During each summer institute, teachers will be introduced to sets of STEM Polar Connections Modules that will emphasize the process of scientific inquiry and will explore a variety of proven techniques for effective teaching, including inquiry-based teaching, cooperative learning, and methods for formative assessment of student learning.
Projects
This project is NSF's contribution to an interagency effort with NASA and NOAA to focus three symposia at the National Science Teachers Association annual meeting, not on particular agency efforts, but specifically on International Polar Year science through three themes: ice, life, and water and air. NSTA focuses on promoting innovation and excellence in science teaching and learning as well as the professional development of teachers to teach science.
The goal of this workshop is to advance the construction of new knowledge through international cooperation with Chinese counterparts in the teaching and learning of math and science at the elementary level in four areas: curriculum design and assessment; teacher preparation and professional development; effective use of the former; and reaching gifted and underserved populations. Approximately 120 people will attend, including 50 senior U.S. researchers, 25 early career researchers, 15 graduate students and 5 undergraduates.
This project aims to develop, implement, and evaluate an Internet of Things (IoT) based educational curriculum and technology that provides grades 9-12 students with Computer Science (CS) and Software Engineering (SE) education.
This Discovery Research K-12 Conference project brought together 30 key scholars and practitioners in the areas of discourse and equity to synthesize and disseminate research findings concerning the implementation of culturally relevant teaching approaches that promote equitable discourse practices in mathematics classroom. The conference convened in Rochester, NY, in June 2008. Conference outcomes include publications that synthesize and disseminate best practices in relation to equitable discourses and a research agenda that further supports teachers' efforts.
This project responds to the need for technology-enhanced assessments that promote the critical practice of scientific argumentation--making and explaining a claim from evidence about a scientific question and critically evaluating sources of uncertainty in the claim. It will investigate how to enhance this practice through automated scoring and immediate feedback in the context of two high school curriculum units--climate change and fresh-water availability--in schools with diverse student populations.
This project will study the design and development of PD that supports teacher development and student learning, and provide accumulation of evidence to inform teacher educators, administrators, teachers, and policymakers of factors associated with successful PD experiences and variation across teachers and types of PDs. The study will examine teachers' uptake of mathematics content, pedagogy and materials from different types of professional development in order to understand and unpack the factors that are associated with what teachers take up and use two-three years beyond their original PD experience.
This project focuses on the teaching practice of building on student thinking, a practice in which teachers engage students in making sense of their peers' mathematical ideas in ways that help the whole class move forward in their mathematical understanding. The study examines how teachers incorporate this practice into mathematics discussions in secondary classrooms by designing tasks that generate opportunities for teachers to build on students' thinking and by studying teachers' orchestration of whole class discussions around student responses to these tasks.
This project focuses on the teaching practice of building on student thinking, a practice in which teachers engage students in making sense of their peers' mathematical ideas in ways that help the whole class move forward in their mathematical understanding. The study examines how teachers incorporate this practice into mathematics discussions in secondary classrooms by designing tasks that generate opportunities for teachers to build on students' thinking and by studying teachers' orchestration of whole class discussions around student responses to these tasks.
This project focuses on the teaching practice of building on student thinking, a practice in which teachers engage students in making sense of their peers' mathematical ideas in ways that help the whole class move forward in their mathematical understanding. The study examines how teachers incorporate this practice into mathematics discussions in secondary classrooms by designing tasks that generate opportunities for teachers to build on students' thinking and by studying teachers' orchestration of whole class discussions around student responses to these tasks.
In this project, the team will address questions about how collaborative problem solving, learning progressions, and facilitation interact in the development of students’ mathematical learning. The work affords an opportunity to advance equitable access to high-quality education for all students by enhancing the quality of instruction for students lacking opportunities to learn key concepts of mathematics because of the inequitable structures of education in the country.
Investigations in Cyber-enabled Education (ICE) strives to provide a professional development design framework for enhancing teacher ability to provide science, technology, and math (STM) instruction for secondary students. Exploratory research will clarify ICE framework constructs and gather empirical evidence to form the basis of anticipated further research into the question: Under what circumstances can cyber-enabled collaboration between STM scientists and educators enhance teacher ability to provide STM education?
This project seeks to strengthen the teaching of statistics and data science in grades 6-12 through the design and implementation of an online professional learning environment for teachers. The professional learning environment aims to support in-service teachers in developing stronger content knowledge related to statistics, and knowledge of how to effectively teach statistics in their classrooms.
This is a quasi-experimental study of the effects of attending an inclusive STEM high school in three key geographic regions and comparing outcomes for students in these schools with those of their counterparts attending other types of schools in the same states. The study's focus is on the extent to which inclusive STEM high schools contribute to improved academic outcomes, interests in STEM careers, and expectations for post secondary study.
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.
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 provides a virtual environment in which high school physics students can engage in the cutting edge science of studying exoplanets. Using online telescopes and learning software, students gain a deeper understanding of science inquiry, including reasoning from models, gathering assessing, and interpreting authentic data, and drawing conclusions from multiple line of evidence. The research advances our understanding of ways to increase students' knowledge of data literacy.
This is a large-scale, cross-sectional, and longitudinal study aimed at understanding and supporting the teaching of science and engineering practices and academic language development of middle and high school students (grades 7-10) with a special emphasis on English language learners (ELLs) and a focus on biotechnology.
The COVID-19 pandemic has highlighted the need for supporting student learning about viral outbreaks and other complex societal issues. Given the complexity of issues like viral outbreaks, engaging learners with different types of models (e.g., mechanistic, computational and system models) is critical. However, there is little research available regarding how learners coordinate sense making across different models. This project will address the gap by studying student learning with different types of models and will use these findings to develop and study new curriculum materials that incorporate multiple models for teaching about viral epidemics in high school biology classes.
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.
The Learning by Evaluating (LbE) project will develop, refine, and test an educational innovation in which 9th grade students evaluate sample work as a starting point in engineering design cycles. Students will compare and discuss the quality and fit to context of completed design artifacts. Teachers will collaboratively review and refine the LbE approaches and map the LbE materials into the curriculum.
This project will develop and test two curriculum units on the topic of evolution for high school general biology courses, with one unit focusing primarily on human case studies to teach evolution and one unit focusing primarily on case studies of evolution in other species. The two units will be compared to examine how different approaches to teaching evolution affect students and teachers.
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 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.
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.