‘If you can’t dance your program, you can’t write it’: Challenges and Implications for AI in Education

Key Points

The study critiques symbolic AI models in education, highlighting their limitations in cognitive processes.
It advocates for embodied AI approaches to enhance Human-Computer Interaction, stressing the importance of situationality.
Current GenAI systems exhibit cognitive limitations, including loss of proprioception and devaluation of embodied practices.
The work promotes a vision of AI in education that fosters critical and situated learning through embodied design principles.

Abstract

This article offers a critical analysis of the role of the body in the development of artificial intelligence (AI) in the field of education. It challenges the dominance of symbolic and disembodied AI models based on abstract information processing and advocates for a paradigm shift toward embodied AI grounded in situationality, emergence, and sensorimotor coupling. Drawing on post-cognitivist frameworks, the article highlights the cognitive and experiential limitations of current GenAI systems, such as the loss of proprioception, multimodal agency, and the devaluation of embodied practices. It proposes a redefinition of Human–Computer Interaction (HCI) centered on a perceptual–affective choreography. The article advances a more inclusive and emancipatory vision of AI in education, aimed at fostering creative, critical, and situated learning through a set of embodied design principles.

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