Adaptive Gen-AI Guidance in Virtual Reality: A Multimodal Exploration of Engagement in Neapolitan Pizza-Making

Abstract

Virtual reality (VR) offers promising opportunities for procedural learning, particularly in preserving intangible cultural heritage. Advances in generative artificial intelligence (Gen-AI) further enrich these experiences by enabling adaptive learning pathways. However, evaluating such adaptive systems using traditional temporal metrics remains challenging due to the inherent variability in Gen-AI response times. To address this, our study employs multimodal behavioural metrics, including visual attention, physical exploratory behaviour, and verbal interaction, to assess user engagement in an adaptive VR environment. In a controlled experiment with 54 participants, we compared three levels of adaptivity (high, moderate, and non-adaptive baseline) within a Neapolitan pizza-making VR experience. Results show that moderate adaptivity optimally enhances user engagement, significantly reducing unnecessary exploratory behaviour and increasing focused visual attention on the AI avatar. Our findings suggest that a balanced level of adaptive AI provides the most effective user support, offering practical design recommendations for future adaptive educational technologies.

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