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.
This project will develop a modified virtual world and accompanying curriculum for middle school students to help them learn to more deeply understand ecosystems patterns and the strengths and limitations of experimentation in ecosystems science. The project will build upon a computer world called EcoMUVE, a Multi-User Virtual Environment or MUVE, and will develop ways for students to conduct experiments within the virtual world and to see the results of those experiments.
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 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.
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.
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.
Data literacy is the ability to ask questions, analyze, interpret, and draw conclusions from data. As the world and the workplace become more data-driven, students need to have stronger data literacy across multiple disciplines, including science. This project uses an instructional framework, Data Puzzles, to investigate how to support middle grades teachers learning to include data literacy in their science teaching. Data Puzzles integrate mathematical and computational thinking with ambitious science teaching instructional practices and contemporary science topics. Students engaging with Data Puzzles resources can analyze real-world climate science data using web-based data analysis tools to make sense of science phenomena and develop data literacy.
Data literacy is the ability to ask questions, analyze, interpret, and draw conclusions from data. As the world and the workplace become more data-driven, students need to have stronger data literacy across multiple disciplines, including science. This project uses an instructional framework, Data Puzzles, to investigate how to support middle grades teachers learning to include data literacy in their science teaching. Data Puzzles integrate mathematical and computational thinking with ambitious science teaching instructional practices and contemporary science topics. Students engaging with Data Puzzles resources can analyze real-world climate science data using web-based data analysis tools to make sense of science phenomena and develop data literacy.
This project aims to develop an innovative field-based science learning approach that will support the capacity of culturally diverse students in Grades K-3 to engage in complex ecological reasoning and related problem solving. To provide rich learning environments, outdoor learning gardens will be created in which students, teachers, garden educators, and families participate in activities that facilitate the investigation of tangible ecological challenges such as water capture and food security.
This project aims to meet this need by developing PreK-5, equity-oriented, field-based, interdisciplinary curricular materials that support students' socioecological reasoning and sustainable decision making. The science learning experiences will be integrated across disciplines from literacy to civic and social studies lessons. The curricular materials will be part of a science education model that facilitates family engagement in ways that transform relations between educators, families, and students' science learning. The curricular activities will be co-designed with teachers while using local nature and culture as a resource.
This project aims to meet this need by developing PreK-5, equity-oriented, field-based, interdisciplinary curricular materials that support students' socioecological reasoning and sustainable decision making. The science learning experiences will be integrated across disciplines from literacy to civic and social studies lessons. The curricular materials will be part of a science education model that facilitates family engagement in ways that transform relations between educators, families, and students' science learning. The curricular activities will be co-designed with teachers while using local nature and culture as a resource.
This project aims to meet this need by developing PreK-5, equity-oriented, field-based, interdisciplinary curricular materials that support students' socioecological reasoning and sustainable decision making. The science learning experiences will be integrated across disciplines from literacy to civic and social studies lessons. The curricular materials will be part of a science education model that facilitates family engagement in ways that transform relations between educators, families, and students' science learning. The curricular activities will be co-designed with teachers while using local nature and culture as a resource.
This project aims to meet this need by developing PreK-5, equity-oriented, field-based, interdisciplinary curricular materials that support students' socioecological reasoning and sustainable decision making. The science learning experiences will be integrated across disciplines from literacy to civic and social studies lessons. The curricular materials will be part of a science education model that facilitates family engagement in ways that transform relations between educators, families, and students' science learning. The curricular activities will be co-designed with teachers while using local nature and culture as a resource.
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.
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.
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.
