Projects

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.

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.

Research has shown that when teachers have strong content and pedagogical content knowledge that they can provide better quality mathematics instruction to their students and improve student outcomes. The goal of this project is to enhance elementary school teachers’ capacity to improve students’ mathematics learning through a scaled professional development program that uses artificial intelligence (AI) to create a personalized, active learning environment for teachers.

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.

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.

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.

Elementary school students' prolonged experiences with positive numbers and operations often lead to their overgeneralizations of rules (e.g., adding always makes larger numbers, subtracting always makes smaller numbers). These overgeneralizations can make learning algebra more difficult later, particularly when students must simultaneously learn algebra, negative numbers, and operations with negative numbers. The purpose of this project is to design and develop educational games centered on negative number concepts that target students before they learn algebra in middle school. Earlier exposure to and learning about negative numbers could increase students' motivation, understanding of connections between positive and negative numbers, and preparation for algebra.

Coding is a key part of computer science, and promoting opportunities that engage learners in coding is vital to the U.S. workforce development. This project builds upon prior research that created a free coding app, OctoStudio, which is widely available for use in elementary and secondary schools. The goals of the project are twofold: First, the team will develop and design features that broaden the technology so that it is more accessible for more users. Second, the team will explore the usability of these new features across potential users. The new features will have potential to allow blind and low vision users to meaningfully engage in coding, which ultimately benefits society by broadening the STEM workforce and bringing coding to a greater population of students.

Elementary school students' prolonged experiences with positive numbers and operations often lead to their overgeneralizations of rules (e.g., adding always makes larger numbers, subtracting always makes smaller numbers). These overgeneralizations can make learning algebra more difficult later, particularly when students must simultaneously learn algebra, negative numbers, and operations with negative numbers. The purpose of this project is to design and develop educational games centered on negative number concepts that target students before they learn algebra in middle school. Earlier exposure to and learning about negative numbers could increase students' motivation, understanding of connections between positive and negative numbers, and preparation for algebra.

Elementary school students' prolonged experiences with positive numbers and operations often lead to their overgeneralizations of rules (e.g., adding always makes larger numbers, subtracting always makes smaller numbers). These overgeneralizations can make learning algebra more difficult later, particularly when students must simultaneously learn algebra, negative numbers, and operations with negative numbers. The purpose of this project is to design and develop educational games centered on negative number concepts that target students before they learn algebra in middle school. Earlier exposure to and learning about negative numbers could increase students' motivation, understanding of connections between positive and negative numbers, and preparation for algebra.

The growing importance of data, data science and artificial intelligence (AI) in education, work, and personal and civic life has increased the need for all U.S. students to develop data literacy, statistical reasoning, and computational thinking skills. However, most middle school students—especially those with learning disabilities (SLD)—receive limited or no instruction in these areas. Data science and AI instruction is often limited to high school settings, narrowly framed within mathematics or science, and rarely designed with the flexibility to support learner variability. The purpose of this project is to develop and refine Data Adventures, a series of open-access, modular, and instructional experiences units designed to introduce middle school students to data literacy, computational thinking, and digital storytelling, while also promoting critical understanding of AI and its role in education, work technology, and everyday life.

This project will investigate how recent advances in artificial intelligence can support computational thinking development within an innovative biology curriculum in which students design and program a robotic arm controlled by their own muscle activity. Specifically, the project will focus on how AI tools can assist students in designing algorithms and translating them into computer programs.

While simulations are powerful tools for scientific inquiry, most students need scaffolding to engage productively in simulation-based inquiry. This project will develop and study an automated feedback system designed to support middle school students' simulation-based inquiry into wildfires, floods, and hurricanes. The system, called Hazbot, will leverage advanced artificial intelligence (AI) technologies—including machine learning and large language models (LLMs)—to provide timely, personalized feedback as students investigate the three different natural hazards.