ABSTRACT

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 project will integrate the previously separate domains of paleontology and computer science via ML. Middle school students will develop ML models to classify shark teeth by their form and function to test authentic research questions. Students will learn fundamental concepts about ML, increase awareness of 21st century careers, and gain access to diverse scientist role models. The project will document and address misconceptions about fossil sharks, paleontology, and ML. Focused on middle school teaching and learning in urban and rural Title I schools throughout Florida, the project team aims to address educational disparities in STEM to encourage students from underrepresented groups to consider the sciences and computational technology as a career path. The Scientist in Every Florida School infrastructure will facilitate recruitment, mentoring, and best practices, such as ensuring that the science and ML content is integrated into the scope and sequence of existing curricula. Additionally, participants will have access to thousands of digital fossil shark specimens in museum and global biodiversity databases. This project will advance the progress of science and promote innovative learning. This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers.

The researchers will investigate a set of interrelated questions focused on how middle schoolers and their teachers learn about ML, including: (1) What instructional components promote effective and feasible integrated learning of science, computational thinking, and ML? (2) What are teachers' perspectives on the value and usability of the new curriculum in their classrooms? (3) What learning scaffolds are needed, and to what extent will students learn AI knowledge? (4) How do misconceptions impact students' and teachers' comprehension of AI and science? (5) How does the curriculum impact interest, self-efficacy, and identity in science and 21st-century careers? A total of 76 teachers will be recruited within three successive year-long cohorts. Each year, the teachers will participate in professional development to acquire the necessary disciplinary knowledge and skills to co-develop curricula along with scientists and then implement the activities in their classrooms. Teachers will partner with scientists and join a large growing learning community, with over 1,000 teachers and 750 scientists statewide. Scientists will conduct visits to classrooms, either virtually or in-person, to facilitate curriculum implementation and provide personal examples of role models. Middle school teachers will be recruited primarily from Title I schools throughout Florida. Project data will be collected and analyzed using mixed methods including surveys, interviews, observations, knowledge tests, projects, and focus groups. This project will provide an innovative and under-explored context for advancing understanding of STEM integration with an emphasis on student and teacher learning about ML as they engage in paleontology investigations. The goal is to serve as a generalizable model for engaging students in K-12 AI education and enhancing students? understanding and interest in relevant careers. Deliverables will include annual professional development for the teachers, year-round scientist classroom visits, vetted curricula and lesson plans that will be freely shared and promoted online, presentations at professional conferences, and research articles published in peer-reviewed literature.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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