People’s body movements can reveal a lot about students’ mathematical reasoning. Examples such as using one’s whole body to explore properties of geometric shapes and raising eyebrows during mathematical insight illustrate ways people’s movements are closely linked to how they think. Despite the value of these nonverbal indicators of students’ learning experiences, this body-mind connection remains understudied. In this project various data sources are gathered from learners playing a video game designed to improve mathematical reasoning through movement and speech. While learning, students occasionally use their bodies to express mathematical insights and trouble spots. These events are important enough that they can influence students’ learning and attitudes toward mathematics, but subtle enough that teachers may miss them in the buzzing dynamics of the classroom. AI will help the research team select when to interview students about these rare but significant moments in their learning, combining the speed and pattern recognition of computers with the depth and insight of humans' natural conversation. This approach creates a rich dataset for analysis and to develop design principles that support mathematics learning through movement. The findings will advance a deeper understanding of how people learn using nonverbal and verbal thought processes and ways to better support these thought processes. The broader impacts include improving mathematics learning for everyone, espe