Wu He

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.

This project will bring locally relevant virtual reality (VR) experiences to teachers and students in areas where there is historically low participation of women and underrepresented minorities in STEM. This exploratory project will support the professional growth and development of current middle and high school STEM teachers by providing multiyear summer training and school year support around environmental sciences themed content, implementing VR in the classroom, and development of a support community for the teachers.

This project will develop a professional development model that allows rural secondary teachers to learn and develop computational thinking related teaching skills with long-term support and scaffolds in place to both build their knowledge and the long-term capacity of their school districts.

This project will study the effect of integrating computing into preservice teacher programs. The project will use design-based research to explore how to connect computing concepts and integration activities to teachers' subject area knowledge and teaching practice, and which computing concepts are most valuable for general computational literacy.

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.

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.

This project investigates how to support sustained engagement in computational modeling in middle school classrooms in two ways: 1) Design and develop an accessible modeling toolkit and accompanying thematically linked curricular units; and, 2) Examine how this toolkit and curriculum enable students to become sophisticated modelers and integrate modeling with other scientific practices such as physical experimentation and argumentation.

The project will create opportunities for teachers to develop programming content knowledge and new understandings of the creative possibilities in computer science education, thereby increasing opportunities for students to develop conceptual and creative fluency with programming.

This project aims to develop, implement, and evaluate an Internet of Things (IoT) based educational curriculum and technology that provides grades 9-12 students with Computer Science (CS) and Software Engineering (SE) education.

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.

Understanding probability is essential for daily life. Probabilistic reasoning is critical in decision making not only for people but also for artificial intelligence (AI). AI sets a modern context to connect probability concepts to real-life situations. It also provides unique opportunities for reciprocal learning that can advance student understanding of both AI systems and probabilistic reasoning. This project aims to improve the current practice of high school probability education and to design AI problem-solving to connect probability and AI concepts. Set in a game-based environment, students learn and practice applying probability theory while exploring the world of probability-based AI algorithms to solve problems that are meaningful and relevant to them.

Understanding probability is essential for daily life. Probabilistic reasoning is critical in decision making not only for people but also for artificial intelligence (AI). AI sets a modern context to connect probability concepts to real-life situations. It also provides unique opportunities for reciprocal learning that can advance student understanding of both AI systems and probabilistic reasoning. This project aims to improve the current practice of high school probability education and to design AI problem-solving to connect probability and AI concepts. Set in a game-based environment, students learn and practice applying probability theory while exploring the world of probability-based AI algorithms to solve problems that are meaningful and relevant to them.

This project will synthesize research on computer-supported collaborative learning (CSCL). The science of CSCL achieved advances in the past decade, including producing a research handbook—however, practitioners do not have easy access to research journals, nor time to sift through the latest findings to guide their practice. Further, conventional forms of research synthesis, such as research handbooks or long synthesis papers, serve narrow audiences and are rarely read by practitioners. The research team will investigate and develop a novel synthesis approach to provide educators and researchers with a novel form of synthesis organized around an interactive map of topics and subtopics.

This project will study learning associated with elementary teachers' engagement in professional learning and elementary students' learning related to quantum science, quantum thinking, and careers. The knowledge base required for elementary teachers and students to learn quantum will be identified in order to explore and compare how elementary students and teachers conceptualize and make sense of quantum science concepts.

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.