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.
Projects
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.
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.
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.
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.
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.
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 and study approaches to equip 4th and 5th grade general and special education teachers to teach computer science (CS) to a broad range of learners with disabilities through professional development. The project will aim to improve accessibility, accommodations, and highlight the role of paraeducators to increase participation and learning in CS for students with disabilities, and it will investigate the impact of the professional development on teachers’ instruction and the influence of the professional development model on student learning, ability beliefs, and attitudes about CS.
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.
Cybersecurity is becoming an increased concern among young technology users; however, elementary school teachers often have limited preparation to teach students about cybersecurity. This project is designed to iteratively develop, refine, and test an innovative professional development program that supports teachers to infuse cybersecurity into 4th-5th grade mathematics and science instruction. The project will synergistically merge cybersecurity with mathematics and science content in authentic, real-world contexts to teach topics such as cyberbullying, digital security, encryption/decryption, digital privacy, and digital footprint.
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.
This project will develop and study approaches to equip 4th and 5th grade general and special education teachers to teach computer science (CS) to a broad range of learners with disabilities through professional development. The project will aim to improve accessibility, accommodations, and highlight the role of paraeducators to increase participation and learning in CS for students with disabilities, and it will investigate the impact of the professional development on teachers’ instruction and the influence of the professional development model on student learning, ability beliefs, and attitudes about CS.
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.
This project aims to create and test an innovative educational approach for bringing STEM learning experiences to underserved youth. It will co-create and study an outdoor robotic-augmented playground called the “Smart Playground” and a corresponding series of classroom lessons. The Smart Playground will be co-designed with Latinx families and educators to engage children in developing computational thinking skills and learning about robotics in a physical environment using a culturally sustaining approach. Research and evaluation will examine whether exposure to the Smart Playground and corresponding classroom activities have an impact on the development of computational thinking in young children.
This project aims to create and test an innovative educational approach for bringing STEM learning experiences to underserved youth. It will co-create and study an outdoor robotic-augmented playground called the “Smart Playground” and a corresponding series of classroom lessons. The Smart Playground will be co-designed with Latinx families and educators to engage children in developing computational thinking skills and learning about robotics in a physical environment using a culturally sustaining approach. Research and evaluation will examine whether exposure to the Smart Playground and corresponding classroom activities have an impact on the development of computational thinking in young children.
This project aims to create and test an innovative educational approach for bringing STEM learning experiences to underserved youth. It will co-create and study an outdoor robotic-augmented playground called the “Smart Playground” and a corresponding series of classroom lessons. The Smart Playground will be co-designed with Latinx families and educators to engage children in developing computational thinking skills and learning about robotics in a physical environment using a culturally sustaining approach. Research and evaluation will examine whether exposure to the Smart Playground and corresponding classroom activities have an impact on the development of computational thinking in young children.
Despite growing interest in supporting the integration of computational thinking (CT) in elementary education, there is not an agreed-upon definition of CT that is developmentally appropriate for early childhood, nor is there a clear understanding of how young children’s CT develops and which kinds of instructional approaches and practices truly support the development of CT. Early elementary educators need feasible research-based, developmentally appropriate CT curricula. This project will contribute to this critical STEM educational need by working with a design team of 5 elementary teachers to develop a research-based integrated mathematics and CT curriculum.
The goal of this project is to investigate the integration of computational thinking (CT) into elementary school curricula by studying how teachers develop expertise in integrating CT activities that align with interdisciplinary standards and existing curricula. Leveraging an asset-based approach, the project will provide opportunities to broaden participation in computer science education through building a community of practice for teachers and designing CT-infused curricula.
The goal of this project is to investigate the integration of computational thinking (CT) into elementary school curricula by studying how teachers develop expertise in integrating CT activities that align with interdisciplinary standards and existing curricula. Leveraging an asset-based approach, the project will provide opportunities to broaden participation in computer science education through building a community of practice for teachers and designing CT-infused curricula.
Through this project, the North Carolina State University Data Science Academy will identify the key success components of a model for the recruitment and mentoring of a diverse cohort of postdoctoral fellows who will enter their professions with expertise in data science education research. This model is intended to train and support scholars who have differing levels of experience and strengths in STEM, STEM education, education research, or data science.
The focus of this project is the design of learning experiences in different high school science courses to help students gain experience in computational thinking. The project uses a partnership between two universities and school district to develop and refine the units as a collaboration between researchers, teachers, and school leaders. The goal is to help all students have opportunities to learn about computational thinking in multiple science courses.
The focus of this project is the design of learning experiences in different high school science courses to help students gain experience in computational thinking. The project uses a partnership between two universities and school district to develop and refine the units as a collaboration between researchers, teachers, and school leaders. The goal is to help all students have opportunities to learn about computational thinking in multiple science courses.