Projects

Socio-environmental issues are both a key to secondary student interest in science and a difficult terrain for teachers to navigate. Problems like climate change have not only scientific but also social, political, and ethical aspects. In order to prepare students for fully understanding such issues, attention needs to be given to how teachers can be supported and learn for effective instruction. This four-year project enacts and researches a teacher professional development program, “Teaching for the Anthropocene,” with middle and high school science teachers that brings a concept of "critical systems thinking." The project investigates how critical systems thinking may enhance teachers’ understanding of socio-environmental issues and support them to integrate those understandings into their curriculum and teaching. The project also identifies potential challenges educators may face as well as what local conditions and program supports help them practically apply critical systems thinking in their classrooms.

Socio-environmental issues are both a key to secondary student interest in science and a difficult terrain for teachers to navigate. Problems like climate change have not only scientific but also social, political, and ethical aspects. In order to prepare students for fully understanding such issues, attention needs to be given to how teachers can be supported and learn for effective instruction. This four-year project enacts and researches a teacher professional development program, “Teaching for the Anthropocene,” with middle and high school science teachers that brings a concept of "critical systems thinking." The project investigates how critical systems thinking may enhance teachers’ understanding of socio-environmental issues and support them to integrate those understandings into their curriculum and teaching. The project also identifies potential challenges educators may face as well as what local conditions and program supports help them practically apply critical systems thinking in their classrooms.

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.

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.

Progress in science is motivated and directed by uncertainties. Yet even though uncertainty is a crucial fulcrum for scientific thought, school students are taught science within an overarching assumption that scientific knowledge is certain. This project explores the intellectual leverage of enabling middle school students to experience how scientific work grapples with uncertainty. The overall goal of this project is to understand how teachers can create equitable learning environments for culturally and linguistically diverse learners using Student Uncertainty for Productive Struggle as a pedagogical model in middle school science classrooms.

Providing computer science (CS) education to students prior to high school is critical for catalyzing their interest in CS and closing achievement and development gaps. However, the retention rate for underrepresented group participants in middle school CS teacher preparation programs is lower than that for their peers. The resulting lack of diversity in CS teachers contributes to students’ inequitable access to quality middle school CS education. In this project will investigate effective design and implementation strategies of CS teacher preparation programs aimed to increase the number of middle school CS teachers from underrepresented groups.

With recent advances in artificial intelligence (AI), the United States needs to develop a diverse workforce with strong computational skills and the knowledge and capability to work with AI. Recent studies have raised questions about the extent to which youth are aware of AI and its application in industries of the future that may limit their interest in pursuing learning that lead toward careers in these industries. To address this challenge, learning trajectories (LTs) will be developed and researched for AI concepts that are challenging for middle and high school students. The project will design and pilot test learning activities and assessments targeting these concepts based on the LTs, offer teacher professional development on the LTs and related activities, and research the effectiveness of the LT-based activities when implemented by teachers during the regular school day.

Professional learning communities (PLCs) are one common model for teachers to collaborate and learn from one another. The goal of this study is to understand how teachers' expertise is positioned in a PLC and the larger system of the school and district to inform mathematics teaching and learning. This should help schools and districts understand the features of PLCs that are important for supporting teachers as they collaborate and learn.

To position students as mathematically competent, middle grades mathematics teachers need easily accessible professional learning (PL), including opportunities to participate in discussions about both mathematics content and teaching practices. A Video in the Middle (VIM) based learning series, the Coherent Asynchronous Online Mathematics Teacher Professional Learning (PL) project will help address this need by producing (1) a refined version of the existing VIM design and development prototype and (2) an asynchronous, collaborative online learning series comprising ten 2.5-hour sessions that focus on positioning students as mathematically competent in representing and conceptualizing transformations-based similarity, slope, or linear functions.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.