The study of puffins can provide a fascinating subject area for the integrated learning of data and ecosystems. Once hunted to local extinction, puffins have made a dramatic yet fragile comeback and been re-established to historic nesting islands in mid-coast Maine. This project combines a scientific adventure story about puffin restoration with student-directed data investigations about the relationships between puffin health and environmental factors.

Ubiquitous computing and new technologies are infusing fields that have not historically been identified as STEM-related, such as the humanities, with new tools and practices involving data. This data infusion is opening up new opportunities to use data literacy instruction to augment instruction already required for compulsory humanities subjects, such as English language arts. Additionally, the potential for improving students? data literacy through the analysis of textual data is directly relevant to increasing future participation and success in STEM fields and professions.

As the construction industry gears toward adopting data sensing technologies, there is a demand for creating and sustaining a workforce with skills for implementing the technologies and analyzing the resulting data to support decision-making. It is also essential to improve awareness of this Science, Technology, Engineering, and Mathematics (STEM) career option among all K-12 students, develop their understanding of the applications of data sensing technologies and improve their computational thinking skills in manipulating and using data.

This project addresses our nation's urgent need for an agile and diverse science and technology workforce by innovating cost-effective and scalable hands-on chemistry and biochemistry laboratory training using virtual reality (VR) and mixed reality (MR) educational technologies. Learning is optimized when theory and practice are seamlessly integrated and when multiple senses (sight, sound, and touch) reinforce each other to promote long-term knowledge retention.

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.

This Developing and Testing Innovations project will advance efforts of the Innovative Technology Experiences for Students and Teachers (ITEST) program to better understand and promote practices that increase students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers. Specifically, the project will increase the interest and improve achievement in mathematics of New York City Black and Latinx students in 1st - 3rd grades.

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.

Advances in artificial intelligence (AI) are fundamentally reshaping the workplace of the future and accelerating the demand for creating and sustaining an AI-literate workforce. This growing demand has highlighted the importance for all K-12 students to develop an understanding of AI to prepare them for future careers. Middle school years are crucial in shaping youth dispositions toward STEM.