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.
Projects
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.
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.
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.
An exit ticket is a recommended and widely used way to end a lesson. The most common purpose of exit tickets is to provide formative feedback to teachers about whether students have met the objectives of a given lesson. However, the psychology of learning literature suggests that there is an untapped potential for exit tickets to also benefit students’ learning directly. This project explores two potential enhancements to exit tickets, with the goal of improving high-school students’ mathematics knowledge and ability to regulate their own learning processes.
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.
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.
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.
Scientific argumentation is one of the eight essential practices in the Next Generation Science Standards. Over the past decade, various methods have been employed to help middle-school students develop argumentation skills in formal learning environments. Despite these efforts, teachers continue to face challenges in motivating and engaging students, particularly in addressing the increasingly varied needs of students. Additionally, districts and schools struggle to integrate these research-based methods into their curriculum in ways that gain buy-in from teachers, students, and stakeholders. To address these challenges, this partnership development project brings together the West Aurora School District in Illinois and Northern Illinois University to pursue two primary goals: (1) co-construct a research and development plan focusing on ways to enhance support and effectiveness in the teaching practice of scientific argumentation through technology, and (2) develop a model for building a design research partnership between a school district and a mid-size public university.
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.
This project will investigate how to design an after-school mathematics space within a school setting that can challenge and expand both students' and teachers' conceptions of what doing mathematics means and teach them to see participation in the discipline in increasingly nuanced and expansive ways. The study focuses on designing an after-school program to support recreational mathematics activities for elementary students. At the same time, teachers who are supporting the after-school program with students will have the opportunity to learn to notice different forms of mathematical participation and learning.
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.
Disengagement from mathematics during middle and high school is a widespread concern that contributes to lower academic achievement and diminished long-term participation in STEM fields. Research shows that students' beliefs about their ability to grow and improve—often referred to as growth mindsets—can significantly enhance motivation, persistence, and performance. However, classroom environments and teacher practices play a critical role in shaping these beliefs. This project evaluates a professional development program, Fellowship Using the Science of Engagement (FUSE), designed to help 6th through 9th grade math teachers adopt instructional practices that foster growth mindset-supportive learning environments. The program provides teachers with research-based insights into adolescent development, structured opportunities to revise their instructional language and feedback practices, and personalized guidance through AI-supported coaching. The study examines whether the FUSE program improves teacher mindsets, communication practices, and well-being, and whether these changes lead to increased student motivation, improved perceptions of classroom climate, and higher performance on state mathematics assessments.
Rapid changes in computing, especially with advances in artificial intelligence, are reshaping the future needs of society and the demands on the STEM workforce. More than ever, computer science (CS) education is critical for all children. Many schools are looking for ways to introduce CS skills and thinking in the elementary grades. Whereas some initiatives have focused on coding as its own endeavor, not integrated with subjects like mathematics, science, or literacy, developers and researchers are increasingly exploring ways that programming and computational thinking (CT) can be integrated into core content. This project will design and study resources that build teacher capacity to integrate CS/CT into mathematics by building on the investigators' prior work developing integrated Math+CS modules in grades 2-5.