The United States faces the critical need to prepare students and the future workforce for advances in Artificial Intelligence (AI). This project will develop curriculum that will engage middle-school students in learning science and basic AI concepts and in developing related career interests.
Projects
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.
Mathematics education research has emphasized instruction that asks teachers to use approaches that center students’ mathematical thinking. A significant part of this is how teachers notice, or focus on, analyze, and decide how to respond to, mathematics thinking. One common professional development method is to use videos of mathematics teaching to help teachers understand what is possible for students' learning. This exploratory project aims to understand how facilitators of video-based teacher professional development learn to help mathematics teachers of middle and high school students notice student mathematical thinking.
To provide equitable mathematics instruction to their students, middle grades mathematics teachers need easily accessible professional learning (PL), including opportunities to participate in discussions about both mathematics content and equity-based teaching practices. This project will help address this need by producing a refined version of the existing Video in the Middle design and development prototype. The team will also produce an asynchronous, collaborative online PL course comprising ten 2.5-hour sessions. These sessions interweave equitable mathematics teaching by incorporating the use of positioning into the classroom learning environment so that students' mathematical competence can be recognized and valued.
Exemplary teaching in STEM fields encourages students from diverse backgrounds to pursue further education and careers in science, technology, engineering and mathematics. Improving teaching, however, first requires an understanding of the current landscape of STEM instruction. The 2027 National Survey of Science and Mathematics Education (NSSME+), the seventh iteration of the study, will continue monitoring the status of science, mathematics, and computer science education in the U.S. The study will examine policies and practices related to STEM education, including the extent to which instruction currently models effective, evidence-based teaching practices, and factors that influence teachers’ decisions about content and pedagogy. It will also attend to factors that contribute to the underrepresentation of some groups in STEM, further adding to general knowledge about ways to broaden participation.
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.
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.
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.
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.
Young children thrive when strong relationships exist between their home and school environments. Early home and school experiences support the development of mathematical skills. Often, schools and teachers struggle to establish these strong relationships; therefore, Math Partners will work with teachers and teaching assistants in classroom design teams to help teachers establish healthy, positive relationships with families that center families’ knowledge and experiences in the context of mathematics.
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.
Across the nation, many school districts are experiencing rapid expansion in the enrollment of multilingual learners, yet many high school teachers do not have corresponding opportunities to learn how to effectively support these students’ engagement in scientific and engineering practices. This exploratory project will address this issue by developing and testing a model of professional learning for high school teachers in which they learn how to embed the Instructional Conversation pedagogy within standards-aligned scientific and engineering practices. Under this model, high school science teachers will collaborate with high school English for Speakers of Other Languages (ESOL) teachers to co-develop linguistically sustaining instructional materials that provide students with intentionally scaffolded opportunities to use scientific dialogue as they collaborate to explain natural phenomena or design solutions through engineering.
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.
Research has shown that the emotions elementary school teachers and their students experience when engaging in mathematics activities play an important role in mathematics teaching and learning. Yet, the field lacks mathematics-specific professional learning opportunities for elementary teachers that focus on the role of teachers’ and learners’ emotions in the way they experience mathematics in the classroom. This project will address these gaps by developing and testing the Orienting Positive Emotions in New Teachers for Mathematics (OPEN for Math) professional learning program.