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.
Projects
While research has identified some features of professional development that impact teacher and student outcomes, there is still much mathematics education researchers do not know regarding which design features are most impactful to learning and how specific features of professional development connect to teacher learning. This project will investigate six prior NSF-funded professional development projects looking for features of the professional development associated with teacher uptake and learning, such as how the establishment of community or norms of collaboration support teachers’ long-term classroom practice.
Expectations and opportunities for student learning in science are expanding to involve students in making sense of and addressing real questions and problems in the world around them. At the same time, school districts are seeking innovative ways to support teachers to provide instruction that takes into account students’ perspectives and uses those perspectives to teach science. This project seeks to understand how a large, urban school district implements a practice-based professional learning program for teachers that employs performance assessments as a lever for instructional improvement by eliciting, centering, and advancing students’ thinking in middle school science classrooms.
Scientific literacy is an important educational goal, and the way scientists communicate is key to how science, as an institution, succeeds in its work. Conveniently, the recent and rapid rise of preprint publication platforms means that the public now has greater access to scientific communication and dialogue that occurs through open peer review. This is driving the need to educate students on, and engage them in, the evolving ways in which scientists construct and communicate knowledge. The goal of this project is to engage students in authentic science communication innovations through the implementation of a preprint and peer-review platform specifically designed for high school students.
Society has grown to rely on smart, embedded, and interconnected systems. This has created a great need for well-qualified and motivated engineers, scientists, and technicians who can design, develop, and deploy innovative microelectronics and Artificial Intelligence (AI) technologies, which drive these systems. This project will address the need for a more robust computer science and engineering workforce by broadening access to microelectronics and AI education leveraging the cutting-edge technologies of Tiny Machine Learning and low-cost microcontroller systems in diverse high schools. The goal of this project is to engage high-school students and teachers from underresourced communities in the design and creative application of AI-enabled smart, embedded technologies, while supporting their engineering identity development and preparing them for the STEM jobs of tomorrow.
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.
High-quality early educational experiences, particularly in mathematics, are crucial for students’ success in K-12 schooling. To create these foundational experiences for young children, early childhood educators need opportunities to enhance their mathematics teaching through job-embedded, sustained professional learning. This partnership development project establish a collaboration among early childhood mathematics educators, school and district leaders, the state department of education, and university faculty in Delaware that aims to enhance children’s early mathematics learning by collaboratively designing support systems for strengthening their teachers’ professional learning.
Research has shown that when teachers have strong content and pedagogical content knowledge that they can provide better quality mathematics instruction to their students and improve student outcomes. The goal of this project is to enhance elementary school teachers’ capacity to improve students’ mathematics learning through a scaled professional development program that uses artificial intelligence (AI) to create a personalized, active learning environment for teachers.
This project will support a conference series, including an in-person gathering and virtual follow-up meetings, that will bring together teachers, researchers, education leaders, and instructional material designers to build a shared understanding of how to integrate the use of high-quality instructional materials with the benefits of localizing these materials to better address students’ contexts and backgrounds. By fostering dialogue, sharing models, and setting priorities for future research and design, the project seeks to build knowledge about inclusive, effective, and culturally responsive approaches to science instruction that will advance equitable science education in K–12 classrooms.
This project will examine middle school students’ learning of earth and physical sciences and their functional understanding of engineering design as they engage in newly developed environmental justice-oriented curriculum units in community-based service projects. In collaboration with middle school teachers and their students, two STEM units that integrate science inquiry, engineering design, and community-based service projects will be co-designed, implemented, and refined while examining students’ science and engineering learning and their development of science/STEM interest and agency.
This project will develop a technology platform that can streamline lesson planning and allow teachers to adapt resources to their students' needs. The project will design and investigate an AI-powered lesson plan tool for middle-grades mathematics teaching called Colleague. Using existing, open-access lesson plans that have been vetted in prior work, the project would refine the tool for generating math lesson plans and supporting teachers to iteratively improve their instruction. Streamlining lesson planning would open more time for teacher creativity and reduce job stress. The study would explore how teachers use Colleague to plan and adapt lessons, the influence on teaching, and the students' learning.
This project will examine middle school students’ learning of earth and physical sciences and their functional understanding of engineering design as they engage in newly developed environmental justice-oriented curriculum units in community-based service projects. In collaboration with middle school teachers and their students, two STEM units that integrate science inquiry, engineering design, and community-based service projects will be co-designed, implemented, and refined while examining students’ science and engineering learning and their development of science/STEM interest and agency.
Artificial intelligence (AI) is transforming numerous industries and catalyzing scientific discoveries and engineering innovations. To prepare for an AI-ready workforce, young people must be introduced to core AI concepts and practices early to develop fundamental understandings and productive attitudes. Neural networks, a key approach in AI development, have been introduced to secondary students using various approaches. However, more work is needed to address the interpretability of neural networks and human-machine collaboration in the development process. This exploratory project will develop and test a digital learning tool for secondary students to learn how to interpret neural networks and collaborate with the algorithm to improve AI systems. The learning tool will allow students to interact with complex concepts visually and dynamically. It will also leverage students’ knowledge and intuition of natural languages by contextualizing neural networks in natural language processing systems.
Despite the importance of addressing climate change, existing K-12 curricula struggle to make the urgency of the situation personally relevant to students. This project seeks to address this challenge in climate change education by making the abstract, global, and seemingly intractable problem of climate change concrete, local, and actionable for young people. The goal of this project is to develop and test actLocal, an online platform for K–12 teachers, students, and the public to easily create localized climate change adaptation simulations for any location in the contiguous United States. These simulations will enable high school students and others to implement and evaluate strategies to address the impacts of climate change in their own communities.
Navigating complex societal issues such as water shortages, forest fires, and other phenomena-based problems requires understanding the social, technological, and scientific dimensions surrounding the issues and they ways these dimensions interact, shift, and change. Despite its importance, however, developing students’ socioscientific literacy has received limited attention in elementary science teaching and learning contexts. This project begins to address this problem of practice by focusing first on developing elementary teachers’ socioscientific literacy and their capacity to integrate socioscientific issues and local phenomena in their science teaching practice.
One of the best ways to help K-12 students learn science is by having them engage in the scientific inquiry and engineering design processes used by STEM professionals. Unfortunately, support for the development of high-quality, place-based, and NGSS-aligned learning experiences that actively engage students has not been forthcoming in all school districts. This gap is particularly true for rural schools and communities. Further, continuing education for teachers, which is essential to assure successful implementation of high-quality science lessons that are grounded in students' local community experiences, is lacking as well. This partnership development project addresses these gaps in science teaching and learning by deepening an existing partnership among local non-profit community education organizations, K-12 public schools, and local university partners. In consultation with new education technology industry partners, the project team will work collaboratively to develop high-quality NGSS-aligned science learning opportunities that actively engage students in lessons relevant to their local environment.
Research has shown that educational games can increase student motivation, support critical thinking, problem-solving, and communication skills. This project will explore what approaches to the design of virtual labs, games, and bridging curriculum can most effectively support middle-school student development of interest and learning of scientific practices and contribute to the development of a science identity.
Despite years of research and interventions to address inequities that are largely related to race, science education continues to perpetuate these inequities in both participation and outcomes in science. This CAREER project will address the need to provide science teachers with a framework for considering race and racial dynamics in science teaching as well as exemplars in science teaching and professional development to support teachers’ teaching identities and praxis.
National frameworks for science education in the United States advocate for bringing science, technology, engineering, mathematics, and computer science (STEM+CS) disciplines together in K-12 classrooms. Although curricular materials are emerging to support STEM+CS integration, research demonstrates that teachers need support to engage students in authentic STEM+CS practices that leverage and sustain student and community assets. This project aims to support middle school teachers in their enactment of an integrated science, engineering, and computational modeling curriculum unit and understand how teachers customize computationally rich, Next Generation Science Standards (NGSS)-aligned curricular materials to their own schools and classrooms.
Although science is increasingly recognized as a key dimension of early learning, findings to date indicate that young children, especially those enrolled in public preschool programs serving historically excluded communities, have limited opportunities to engage in high quality science investigations. The lack of professional learning resources available to teachers makes it challenging for them to feasibly and effectively promote science in their classrooms. To address this need, this four-year design and development project brings together public preschool teachers, families from culturally and linguistically diverse communities, early learning and STEM researchers, and designers of media to co-design a Professional Learning Hub for Early Science.
Providing students with exposure to high quality computational thinking (CT) activities within science classes has the possibility to create transformative educational experiences that will prepare students to harness the power of CT for authentic problems. By building upon foundational research in human-AI partnership for classroom support and effective practices for integrating CT in science, this collaborative research project will advance understanding of how to empower teachers to lead computationally enriched science activities with adaptive pedagogical tools.
This partnership development project deepens an existing partnership between the researcher and leadership of an elementary school in central Texas that serves predominantly Black and Latine students. The project focuses on engaging community members, teachers, and learners at the school in conversation about how mathematics teaching and learning might be improved. This partnering is important because the relationship between schools and communities is often marked by one-way communication and decision-making without dialogue. By promoting dialogue, all members of this partnership can learn more about the mathematical storylines embedded into the community, that is, the stories that community members, teachers, and learners share about their personal relationship to mathematics teaching and learning.
National frameworks for science education in the United States advocate for bringing science, technology, engineering, mathematics, and computer science (STEM+CS) disciplines together in K-12 classrooms. Although curricular materials are emerging to support STEM+CS integration, research demonstrates that teachers need support to engage students in authentic STEM+CS practices that leverage and sustain student and community assets. This project aims to support middle school teachers in their enactment of an integrated science, engineering, and computational modeling curriculum unit and understand how teachers customize computationally rich, Next Generation Science Standards (NGSS)-aligned curricular materials to their own schools and classrooms.
Writing instruction in math and science is an essential area of research to ensure equitable K-12 and college experiences and to better prepare all students in ways that provide opportunities to pursue STEM career pathways. This project is a meta-analysis in the area of secondary (grades 6-12) math and science writing instruction.
This project will develop and study approaches to equip 4th and 5th grade general and special education teachers to teach computer science (CS) to a broad range of learners with disabilities through professional development. The project will aim to improve accessibility, accommodations, and highlight the role of paraeducators to increase participation and learning in CS for students with disabilities, and it will investigate the impact of the professional development on teachers’ instruction and the influence of the professional development model on student learning, ability beliefs, and attitudes about CS.