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
To successfully understand and address complex and important questions in the field of environmental science, many kinds of communities’ knowledge about their local environment need to be engaged. This one-year partnership development project involves a collaboration to design an approach that would yield opportunities for K-12 students to learn about environmental science in ways that honor both traditional STEM knowledge and Native ways of knowing among the Pomo community in California.
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.
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.
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.
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.
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.
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.
High school and first-year college mathematics courses sometimes act as gatekeepers, ‘weeding out’ students who struggle with the subject matter and narrowing students’ opportunities for advanced STEM education and employment. Acknowledging opportunity gaps for students of color and those experiencing poverty, this partnership development project brings together Milwaukee Public Schools (MPS), Milwaukee Area Technical College (MATC), and WestEd to establish dual enrollment math courses that function as a lever for equity.
Tutoring programs that are jointly supported by schools and universities can offer benefits to both parties. The programs, however, are only helpful to the extent they respond to the needs and interests of the students and schools they serve. This project will establish a partnership between a large, urban university and a small, rural high school to collaboratively create a tutoring program to support the mathematics learning of students with learning disabilities.
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.
Although there is a push to integrate artificial intelligence (AI) in K-12 education, the novelty of AI means that little is known about what schools, teachers, students, and parents know, need, and expect regarding AI in classrooms. The lack of access to AI knowledge and training is especially significant in rural high-needs communities where schools are under-resourced. This year-long partnership development project will seek to strengthen and expand existing research-practice partnerships (RPPs) with East Tennessee teachers and school leaders, develop new RPPs with parents and students enrolled in East Tennessee middle and high schools, and co-construct a shared vision for AI that aligns with the needs and assets of the partner community.
Over the years, researchers and practitioners have created and tested different ways to support students who struggle with learning mathematics. These methods include directly teaching various mathematics skills and strategies that affect mathematics performance, such as alleviating mathematics anxiety and fostering motivation and engagement in mathematics learning. The idea is that teaching mathematics using a mix of these skills or strategies might help students learn better than teaching just one skill or strategy at a time. However, it remains unclear which skills or strategies should be taught together and if mixing different skills or strategies leads to differential effects across different students or contexts. Understanding this is vital because it can help researchers and practitioners determine the best ways to address the need of struggling students in mathematics. A network meta-analysis will allow the field to examine different combinations of instructional skills/strategies as well as their interaction effects, which can provide more optimal information about different instructional approaches.
Semiconductors are essential components of electronic devices, enabling advances in important applications and systems such as communication, healthcare, and national security. In order to sustain the U.S.'s global competitiveness in the semiconductor industry, there is a growing demand for a skilled semiconductor workforce. High schoolers are among the most frequent users of electronic devices. However, many do not know how these devices are designed and manufactured. To address the knowledge gaps and workforce needs equitably, this project will develop a semiconductor curriculum with high-school-aged students from diverse backgrounds, and with partners in higher education, K-12, and industries, enhanced with artificial intelligence (AI) and other innovative technologies.
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.
In the 21st century, the educational landscape is undergoing a seismic shift, with Artificial Intelligence (AI) emerging as a pivotal force reshaping the contours of teaching and learning, especially in the realm of science education. As educators, policymakers, and researchers grapple with the challenges and opportunities presented by this technological juggernaut, this project underscores the imperative to weave AI's transformative potential seamlessly with the foundational principles of Diversity, Equity, and Inclusion (DEI). The vision driving this initiative is twofold: harnessing the unparalleled capabilities of AI to revolutionize educational experiences while ensuring that these innovations are accessible, relevant, and beneficial to every student, irrespective of their background or circumstances.
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 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.
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 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.
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.
The project addresses the historic marginalization of women and minoritized racial/ethnic (MRE) groups in physics. The aim of the project is to co-design, test, and disseminate professional learning for high school physics teachers, specifically targeting the implementation of inclusive and equitable practices that support physics identity development and persistence of women and MRE groups.
This research synthesis systematically reviews and meta-analyzes the evidence on relationships between teacher support, student engagement, and mathematics achievement in the instructional–relational model framework. The researchers rigorously examine the consistency and variability of the relationships between the domains and constructs across studies.
This project investigates the STEM teacher pipeline and examine qualifications, from teacher candidates who express interest in teaching STEM through to the eventual career paths of teachers in the workforce. In doing so, the project examines how the supply of STEM teachers has changed over time, whether the supply is adequate in meeting the needs of a changing nation, the qualifications and credentials of STEM teachers, and the implications of the STEM teacher career paths for equity and serving high needs contexts and students.