Wu He

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.

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.