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.
Projects
As the nation tackles the challenges of energy transition, K-12 education must prepare a future STEM workforce that can not only apply STEM skills but also address reasoning through complex sociotechnical problems involving social justice. Aligned with the principles of socially transformative engineering and focused on students of color, this project involves the design and implementation of a novel STEM education curriculum that will support the development of secondary students’ abilities to reason through ambiguous and ethical challenges through design projects and to transfer these competencies to everyday life and future workplaces.
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.
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.
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.
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.
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.
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 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.
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.
High school counselors play an integral role in supporting students’ trajectories toward science, technology, engineering, and mathematics (STEM) careers. Many professional learning experiences for counselors have not focused specifically on developing awareness of a broad array of STEM careers and the corresponding high school activities and coursework that can establish students’ trajectories toward these careers. This project addresses this gap in practice by developing year-long professional learning experiences focused on engineering-related careers, with and for high school counselors.
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.
Partnership development between universities and school districts requires an understanding that each organization has a distinct institutional point of view that must be considered in defining and shaping collaborative work. The goals and objectives of each organization may not always align, and at times may compete or conflict with each other. With the understanding that successful partnerships are those where practitioners and researchers achieve high levels of trust, commitment, transparency, interdependence, and mutual benefit, this project centers on building a partnership between a university that serves a largely Hispanic student population and a rural school district that also serves a community that has long been underrepresented in STEM education and career opportunities. The partners will jointly focus on how to respond to three negative impacts of the COVID-19 pandemic: 1) limited access to quality learning opportunities, 2) increased student learning gaps in STEM subjects, and 3) a local teacher shortage.
Science and engineering teaching and curriculum have begun to engage learners’ knowledge of themselves, their communities, and their experiences of science and engineering. This knowledge can make the experience of learning science and engineering more meaningful and impactful as learners can see greater connections between the content and how their own experiences and communities. However, assessment approaches for documenting and presenting what learners’ know have typically not been able to sufficiently represent the new approaches to teaching and learning. This conference brings together researchers, school leaders, and teachers to develop frameworks and resources for making culturally sustaining approaches to teaching and learning science and engineering.
The Inter-university Consortium for Political and Social Research (ICPSR) will host a workshop that brings together NSF-funded teams working on midscale research infrastructure incubator projects for STEM education research with a focus on education equity. ICPSR will share information, resources, and support incubator teams in developing and managing mid-scale infrastructure projects. These incubator projects have identified research infrastructure gaps related to assessments, teacher practices, and digital tools to support student learning and have proposed pilot tools, cyberinfrastructure, large-scale datasets, etc., for filling these gaps. To scale these pilots, the teams will need to successfully develop proposals to create mid-scale research infrastructure (Midscale RI). However, Midscale RI proposals require specialized knowledge that is not common within the STEM education research community and thus may limit the community’s ability to develop competitive Midscale RI proposals.
K-12 teachers are a critical resource for promoting equitable STEM achievement and attainment. Experimental research, however, rarely identifies specific, transferable STEM instructional practices, because STEM education research has typically implemented student-level randomization far more than it has implemented teacher-level randomization. A major barrier limiting scientific progress is the lack of a large-scale trialing infrastructure that can support teacher-level randomization and experimentation, given the logistical constraints of recruiting multiple sites and successfully randomizing at the teacher or classroom level. This Midscale Research Infrastructure Incubator will launch a two-year, accelerated process to address these challenges and develop a consensus plan for a STEM-teacher-focused trialing platform.
This project envisions a future of work where advanced technologies provide automated, job-embedded, individualized feedback to drive professional learning of the future worker. To achieve this goal, it addresses a fundamental question: Are evaluative or non-evaluative feedback systems more effective in driving professional learning? This question will be tested on professionals where objective, fine-grained feedback is especially critical to improvement--the teaching professions. This research will be situated within English and language arts (ELA) instruction in middle and high school classrooms, where underperformance and inequality in literacy outcomes are persistent problems facing the U.S. Current methods of supporting teacher learning through feedback are sparse, cumbersome, subjective, and evaluative. Thus, a major reconceptualization is needed to provide feedback mechanisms that- meaningfully affect teacher practice and are accessible to all. In partnership with TeachFX, an industry leader in technology-enabled instructional feedback, this project will work with teachers to design and test systems of automated feedback. Insights from the study will lead to feedback systems that empower teaching professionals, generate continued professional learning, and ultimately, increase student achievement.
This project examines how Latine, bilingual teachers' dispositions to teach science and engineering to bilingual learners change as they enter the teaching profession. Specifically, it explores bilingual teachers' transition from a period of strong social support to one of scarce social support, i.e., from being Bilingual Teacher Candidates to Novice Bilingual Teachers (NBTs) as they plan and teach bilingual science and engineering lessons.
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.
This project is an innovative exploratory research study focused on developing a high school environmental engineering curriculum that addresses the challenges posed by climate change. The curriculum follows a model-validate-iterate design paradigm, where students model dynamic real-world systems, validate their models using data, and create multiple iterations to explore changes in the system over time. The project aims to cultivate a new generation of environmental engineers who possess the necessary skills to analyze complex systems, collaborate with diverse communities, and develop creative solutions.
Online STEM credit courses have become attractive to school leaders as a way to support students who fail STEM courses in face-to-face school year settings. However, there is little research about the processes involved in how schools make decisions regarding student credit recovery. The available research focuses solely on student results and is not definitive enough to support important policy decisions at the district level. This research brings redress to this policy dilemma.