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From Craft Practice to Aesthetic Cognition Transmission: ...
[Submitted on 31 May 2026] · 2026-06-02 · via cs updates on arXiv.org

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Abstract:Intangible Cultural Heritage (ICH) education has traditionally relied on apprenticeship, embodied participation, and long-term engagement with masters, materials, and cultural environments. While these modes of transmission remain essential, they are difficult to scale. Existing digital heritage initiatives have expanded documentation and access, but often preserve artefacts, procedures, and representations of practice rather than the aesthetic and cognitive structures through which expertise operates. This paper argues that the future challenge of ICH education is not only the transmission of craft techniques, but the scalable transmission of aesthetic cognition: the perception, judgement, interpretation, and culturally situated meaning-making through which aesthetic expertise develops. Drawing on aesthetic education, tacit knowledge, cognitive apprenticeship, and expert cognition, we propose a shift from craft transmission to Aesthetic Cognition Transmission. To support this shift, we introduce Workflow Cognition as a model of how experts coordinate perception, judgement, decision-making, and action within evolving workflows. We then propose Workflow Cognition Translation as a methodological framework for transforming expert workflow cognition into computable educational representations for AI-native learning systems. The paper makes three contributions: it reframes ICH education around aesthetic cognition transmission; introduces Workflow Cognition Translation as a method for representing expert aesthetic cognition; and outlines an AI-native cognitive apprenticeship infrastructure involving AI Expert Twins, workflow-based tutoring, and progressive learner participation. Rather than replacing masters, workshops, or embodied practice, the framework positions AI as a cognition mediation infrastructure for expanding access to heritage expertise.

Submission history

From: Annie Yuan [view email]
[v1] Sun, 31 May 2026 12:37:51 UTC (13,345 KB)