Title: Immersion for AI: Immersive Learning with Artificial Intelligence Show Chinese title

Title: 人工智能的沉浸式学习：用人工智能进行沉浸式学习

Abstract: This work reflects upon what Immersion can mean from the perspective of an Artificial Intelligence (AI). Applying the lens of immersive learning theory, it seeks to understand whether this new perspective supports ways for AI participation in cognitive ecologies. By treating AI as a participant rather than a tool, it explores what other participants (humans and other AIs) need to consider in environments where AI can meaningfully engage and contribute to the cognitive ecology, and what the implications are for designing such learning environments. Drawing from the three conceptual dimensions of immersion - System, Narrative, and Agency - this work reinterprets AIs in immersive learning contexts. It outlines practical implications for designing learning environments where AIs are surrounded by external digital services, can interpret a narrative of origins, changes, and structural developments in data, and dynamically respond, making operational and tactical decisions that shape human-AI collaboration. Finally, this work suggests how these insights might influence the future of AI training, proposing that immersive learning theory can inform the development of AIs capable of evolving beyond static models. This paper paves the way for understanding AI as an immersive learner and participant in evolving human-AI cognitive ecosystems. Show Chinese abstract

Abstract: 这项工作从人工智能（AI）的角度反思了沉浸可能意味着什么。 通过应用沉浸学习理论的视角，它试图理解这种新视角是否支持人工智能参与认知生态的方式。 通过将人工智能视为参与者而非工具，它探讨了在人工智能能够有意义地参与并对认知生态做出贡献的环境中，其他参与者（人类和其他人工智能）需要考虑什么，以及设计此类学习环境的含义是什么。 基于沉浸的三个概念维度——系统、叙事和能动性——这项工作重新诠释了沉浸学习情境中的AIs。 它概述了设计学习环境的实际意义，在这些环境中，AIs被外部数字服务所包围，可以解读数据的起源、变化和结构发展，并动态响应，做出塑造人机协作的操作和战术决策。 最后，这项工作提出了这些见解可能如何影响人工智能培训的未来，建议沉浸学习理论可以为开发能够超越静态模型的人工智能提供信息。 本文为理解人工智能作为沉浸式学习者和不断发展的以人类为中心的人工智能认知生态系统中的参与者铺平了道路。