This project responds to the growing recognition that learners of all ages should have the opportunity to engage with and learn about artificial intelligence (AI). Of AI's many subfields, natural language processing (NLP) is one of the fastest growing. NLP focuses on how to automatically understand spoken or textual data, and billions of these textual or spoken exchanges are recorded online every day.

Exciting young children's interest in science, technology, engineering, and mathematics (STEM) is an essential way to attract more students to STEM course work and STEM careers. This project will use a variety of tools to engage four- to eight-year-old children and their families. First, the project will create a five-episode STEM media series for the Public Broadcasting System. The series will include diverse STEM professionals, including astronauts and engineers, reading STEM picture books from space, Earth, and sea.

The project will introduce and investigate an innovative model for using authentic community-relevant research to deepen students' STEM knowledge and skills, while building strong community connections between Maine's coastal school districts and their communities. The project will involve teachers and administrators, STEM and STEM education faculty, and business leaders and other community members in a research practice partnership.

This project will develop upper elementary school students’ abilities to work with Artificial intelligence (AI) in future careers. AI will be a critical tool for influencing and increasing productivity in the future of work. As such, it is increasingly important to introduce K-12 students to basic AI knowledge and skills, build familiarity with AI technologies, and train students to be competitive in the workforce. Through this project, a team of robotics and education researchers at Tufts University in Massachusetts and Maryville University in St.

Rehabilitation and assistive robots are becoming more prevalent as the population is aging. Healthcare technologies are rapidly evolving and becoming increasingly high-tech and reliant on sensors for biological data collection and human-robot interactions to augment human capabilities. Not only is the field changing, but the demand for a highly skilled workforce is growing rapidly.

This project will host a workshop in order to identify and synthesize research findings from NSF awards that addressed the unanticipated effects of the COVID-19 pandemic on STEM teaching and learning. The interruptions from the pandemic had dramatic, widespread effects in education. Across the nation, teachers, students, parents, staff, and school administrators experienced extended school closures and a rapid and unexpected shift to virtual instruction.