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.

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.

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.

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.

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.

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.

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.

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.

Science education integrates the study of and practices from the Next Generation Science Standards (NGSS). At the fundamental level, the pedagogy involves teaching and learning that emphasizes the use of scientific inquiry and the engineering design process to develop students’ problem-solving, critical thinking, and collaboration skills. Unfortunately, funding and professional development for teachers, which is essential to assure successful implementation of science lessons to increase the potential for student achievement, is lacking.

Therefore, this NSF-funded science-education research project explored the development of a model that deepens the existing partnerships among grass-roots, non-profit community education organizations, K-12 public schools, and local university partners. Together, they worked collaboratively to develop a model where teachers could work together with community partners to implement high-quality, place-based, NGSS-aligned science learning opportunities that actively engage students in their classrooms during the school day.

This research project has led to the development of a full PreK-12 DRK proposal for high-quality professional development for teachers, using the newly developed Teacher-Plus-Community Partners (T+CP) model, with the goals of increasing science efficacy for teachers and impacting student achievement in science.

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 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.

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.

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.

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.

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.

Environmental issues like wildfires can serve as effective science learning contexts to promote scientific literacy and citizenship. This project will partner with teachers, teacher educators, and disciplinary experts in data science, fire ecology, public health, and environmental communication to co-design a data-driven, justice-oriented, and issue-based unit on wildfires. In the unit, student will engage in various data practices to gain insights into the issue of wildfires and how it affects their lives and communities. The project seeks to theorize how learners can leverage disciplinary knowledge and practices in environmental and data science as a foundation for making data-informed actions towards a more just and sustainable society.

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.

The purpose of this project is to develop a home mathematics environment (HME) intervention for preschool-aged children with developmental delays (DD). The project includes caregivers of children with DD as collaborators in the iterative design process to develop feasible and sustainable HME intervention activities.

Understanding of algebra concepts is necessary for students to gain access to STEM pathways. However, recent efforts in education have failed to improve algebra outcomes for many students, especially those with learning disabilities and persistent difficulties in mathematics. The primary goal of this project is to develop a supplemental intervention that intentionally develops students' concept of variable as they learn to (a) interpret and evaluate expressions, (b) represent real-life mathematical word problems using algebraic notation, and (c) solve linear equations. A focus on clarifying common misconceptions about variables will be interwoven throughout the program.

This research study examines the potential of integrating student-driven descriptive investigations of complex multivariate civic datasets into middle school social studies classrooms. It uses a collaborative co-design process to develop data-rich experiences for the social studies classroom crafted to 1) deepen students' data literacy, 2) develop students' sense of efficacy in working with civic data sets, and 3) create learning experiences that connect data to local problems that have meaning for students and their communities.