Projects

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.

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.

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.

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.

Science education research shows that incorporating attention-grabbing concepts and experiences—phenomena—in science classes has the power to engage and inspire young learners. However, many elementary teachers, including those in small rural schools, may not have access to or the support to enact high-quality phenomenon-centered curriculum materials and resources in their science teaching practice. This project aims to address this problem of practice by designing, implementing, and investigating a professional learning approach that supports rural elementary teachers and administrators in incorporating local phenomena-driven science learning experiences in their classrooms.

Science education research shows that incorporating attention-grabbing concepts and experiences—phenomena—in science classes has the power to engage and inspire young learners. However, many elementary teachers, including those in small rural schools, may not have access to or the support to enact high-quality phenomenon-centered curriculum materials and resources in their science teaching practice. This project aims to address this problem of practice by designing, implementing, and investigating a professional learning approach that supports rural elementary teachers and administrators in incorporating local phenomena-driven science learning experiences in their classrooms.

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.

Science education research shows that incorporating attention-grabbing concepts and experiences—phenomena—in science classes has the power to engage and inspire young learners. However, many elementary teachers, including those in small rural schools, may not have access to or the support to enact high-quality phenomenon-centered curriculum materials and resources in their science teaching practice. This project aims to address this problem of practice by designing, implementing, and investigating a professional learning approach that supports rural elementary teachers and administrators in incorporating local phenomena-driven science learning experiences 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.