镜像过去：探索祖先数字自我如何影响历史学习
Mirroring the Past: Exploring How Ancestral Digital Self Influences History Learning
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中文总结 AI 辅助
该研究针对历史学习中学习者与自身的疏离问题，提出AI生成的“祖先数字自我”教学智能体，经被试内研究发现其可提升体验性指标，但未改善即时学习结果，为相关教育环境设计提供启示。
中文摘要 AI 辅助
学习者常觉得历史与自身遥远，这会限制历史学习中的沉浸感与同理心。为缩小这一差距，我们引入“祖先数字自我”，这是一种AI生成的教学智能体，以预录视频呈现，其面部特征和音色与学习者镜像，代表处于历史情境中的自我版本。我们开发了可复现的AI生成历史学习视频工作流，并开展了被试内研究（N=36），比较数字自我智能体与非自我教学智能体。数字自我智能体提升了体验性指标，包括叙事运输感、感知关联性、自我-他人包容度及智能体感知；但未改善即时学习结果：数字自我条件下的测验分数更低，且“记得/知道”判断无可靠差异。访谈进一步显示，自我相似性增加了熟悉感与动机，而新颖性与怪异感可能会分散对历史内容的注意力。这些发现为未来由教学智能体支持的教育环境提供了设计启示。
英文摘要
Learners often perceive history as distant from themselves, which limits immersion and empathy in history learning. To bridge this gap, we introduce the "Ancestral Digital Self," an AI-generated pedagogical agent presented in prerecorded videos that mirrors the learner's facial features and vocal timbre, representing a historically situated version of the self. We developed a reproducible workflow for creating AI-generated historical learning videos and conducted a within-subjects study (N=36) comparing a Digital Self agent with a non-self pedagogical agent. The Digital Self agent enhanced experiential measures, including narrative transportation, perceived relatedness, self-other inclusion, and agent perception. However, it did not improve immediate learning outcomes: quiz scores were lower in the Digital Self condition, and Remember/Know judgments showed no reliable differences. Interviews further suggested that self-similarity increased familiarity and motivation, while novelty and uncanniness could draw attention away from historical content. These findings offer design implications for future educational environments supported by pedagogical agents.
