Advancing AI Learning through a Movement-Based After-School Program for Upper Elementary Youth

Artificial intelligence (AI) is increasingly shaping how people learn, work, communicate, and make decisions, making it essential for young learners to develop a foundational understanding of how AI works and how it affects society. However, there is limited research on how to teach core AI concepts to elementary school students in ways that are developmentally appropriate, engaging, and personally meaningful. This project addresses that need by investigating how upper elementary students can learn about AI through embodied movement and physical activity in an after-school setting. By connecting AI concepts to learners' own movements and experiences, the project aims to make abstract ideas more concrete while broadening participation in AI education at an early age. The project supports the national interest by advancing research on effective AI education, preparing the next generation with foundational AI literacy, and fostering a more informed citizenry capable of understanding the opportunities and challenges presented by AI technologies. This project will design, iteratively refine, and study AI-PLAY, an after-school program that teaches three foundational AI concepts: how computers perceive the world through sensors, how AI systems learn from data, and how AI can impact society. The team will examine the following research question: In what ways can upper elementary AI learning be supported through learner-driven investigation of data generated from learners’ own embodied movement within an after-school program? Across three years of implementations serving approximately 360 upper elementary students, the research team will collect evidence on student learning, self-efficacy, and program effectiveness to guide ongoing refinement of the learning experiences. The interdisciplinary team combines expertise in computer science, educational technology, and biomechanics. Project outcomes will include new knowledge about effective approaches to elementary AI education, a freely available AI-PLAY curriculum and instructional materials, and a publicly available educational movement dataset to support future research and broader adoption by educators and researchers. This project was funded by the STEM K-12 program, which supports fundamental, applied, and translational research on STEM learning in both formal K-12 education and informal learning environments. 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.