Embodied Inquiry with AI as Facilitator: An Exploratory Case Study

Synthesis: Tufino & Damiani (2026) explore where a language-based AI can stand within an inquiry activity without displacing embodied experience, using a Master's-level physics education course investigating the statics of fluids via the ISLE approach. In a two-phase design, students first built the buoyancy model with their own hands without AI; a purpose-configured AI assistant then facilitated applying the model to a new phenomenon. The paper discusses what a language-based facilitator cannot reach and the value of a design in which AI complements embodied inquiry rather than replacing it. The work connects to Physics Education, Socratic Method, and Pedagogical Agent theory.

Where AI Cannot Reach in Embodied Inquiry

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 case study asks where a language-based AI can stand within an inquiry activity without displacing embodied experience.

Two-Phase ISLE Design

University students in a Master's course in physics education investigated the statics of fluids following the ISLE (Investigative Science Learning Environment) approach 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.

Findings

The paper discusses what a language-based facilitator cannot reach and the value of a design in which AI complements embodied inquiry rather than replacing it — a nuanced contribution to Pedagogical Agent and constructivist learning theory.

Connected Concepts

Connected Articles

Citation

Tufino, E., & Damiani, P. (2026). Embodied inquiry with AI as facilitator: An exploratory case study. arXiv:2607.21349.