Mathematics teacher education faces an unprecedented challenge: how to bridge embodied, body-grounded mathematical reasoning and the disembodied outputs of generative artificial intelligence. This paper proposes a principled theoretical extension of Mathematical Working Space framework integrating embodied cognition as a distinct genesis dimension. Building on this foundation, we investigate how this mode of work and a distant AI-enhanced one can operate as sequential and complementary extensions: embodied work provides the pre-rigorous intuition-building phase that enables quality critical engagement with AI-generated solutions. Empirical validation draws from a preservice teacher course structured progressing from bodily engagement to AI dialogue. The study reveals that a complete circulation, from embodied intuition to formal abstraction, is a necessary precondition for the critical, metacognitive stance required for quality teacher-AI interaction.

From ‘embodied genesis’ to AI dialogue: Defining the MWS-E framework for mathematics teacher education

Annamaria Miranda
2026

Abstract

Mathematics teacher education faces an unprecedented challenge: how to bridge embodied, body-grounded mathematical reasoning and the disembodied outputs of generative artificial intelligence. This paper proposes a principled theoretical extension of Mathematical Working Space framework integrating embodied cognition as a distinct genesis dimension. Building on this foundation, we investigate how this mode of work and a distant AI-enhanced one can operate as sequential and complementary extensions: embodied work provides the pre-rigorous intuition-building phase that enables quality critical engagement with AI-generated solutions. Empirical validation draws from a preservice teacher course structured progressing from bodily engagement to AI dialogue. The study reveals that a complete circulation, from embodied intuition to formal abstraction, is a necessary precondition for the critical, metacognitive stance required for quality teacher-AI interaction.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4953755
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