Sharks have ruled the Earth’s oceans for 400 million years, leaving behind a widespread fossil record. Inspired by the extinct 65-foot-long predator Megalodon, fossil shark teeth can spark student interest and curiosity in STEM (Science, Technology, Engineering, and Mathematics). Machine Learning (ML), a branch of Artificial Intelligence (AI), is used in a variety of fields today and is broadly applicable for developing predictive models that drive research and development.

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.

Quantum information science (QIS) is imperative to economic and national security, commerce, and technology.  Development of a "quantum smart" workforce needs to begin before college. The logical venue for exposure to quantum might be a physics course, but numerous K-12 students attend schools where physics is not offered. Since most students will not major in physics, it is vital to expose K-12 students to quantum concepts that are relevant to everyday experiences with credit card security, phones, computers, and basic technology.

Over 2.5 million children in the US are medically homebound. They are socially isolated, physically segregated, and current educational practices largely exclude them from their school communities. Telepresence robots have emerged as a possible means to support these children to return to their local schools, however, it is not yet understood how homebound children can effectively use these robots for optimal learning and social development experiences.

The project will develop and research an after-school program that is designed to increase the STEM career interests and motivations of Native American middle-school students.  Students will use digital technologies, including virtual reality (VR), augmented reality (AR), and 3D printing, to solve spatial design problems presented through the project’s culturally responsive, problem-based learning education modules.

This project will advance efforts to better understand and promote practices that broaden access to and interest in regionally relevant science, technology, engineering, and math (STEM) occupations for underrepresented youth in the state of Maine. This project will engage students in investigations of local marine ecosystems through the construction and revision of computational models of those systems.

This project will advance efforts of the Innovative Technology Experiences for Students and Teachers (ITEST) program to better understand and promote practices that increase student motivations and capacities to pursue careers in fields of science, technology, engineering, or mathematics (STEM). For these students with visual impairments (VI), the possibility of a future in astronomy, or any science, technology, engineering, and mathematics (STEM) field, seems daunting.

This project will teach foundational computational thinking (CT) concepts to preschoolers by  creating a series of mobile apps to guide families through sequenced sets of videos and  hands-on activities.  To support families at home it would also develop a new library model to build librarians? computational thinking  content knowledge and self-efficacy so they can support parents? efforts with their children.

Augmented reality (AR) allows the real world to be enhanced, or augmented, by computer-generated objects that are “added” to the real world. For example, a clothing store may use AR to allow a customer to “see” how clothes would look on them before they are purchased. This project at University of California San Diego will use AR to create an environment in which students can practice pair programming in an AR environment. Pair programming is a software development technique in which two programmers work together at one workstation, on the same piece of code.