Embodied inquiry with AI as facilitator: an exploratory case study
Abstract
Generative AI is entering science education at a time when the embodied education community is asking what such systems cannot do.
Rather than asking whether AI can understand the body, this exploratory case study asks where a language-based AI can stand within an inquiry activity without displacing embodied experience.
University students in a Master's course in physics education investigated the statics of fluids following the ISLE approach (Investigative Science Learning Environment) in a two-phase design: students first built the buoyancy model with their own hands, without AI; a purpose-configured AI assistant then facilitated the application of the model to a new phenomenon.
We discuss what a language-based facilitator cannot reach and the value of a design in which AI complements embodied inquiry rather than replacing it.
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