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As an issue in how to acquire physical skills by watching videos of skillful models, if the motions of beginners and skillful models are very different, there is a possibility that the threshold for practicing is high because self-efficacy does not occur. In this study, we propose to improve video teaching materials by using video generative AI to replace the appearance of a skillful model with that of a beginner, and by adjusting the trajectory of motion using skeletal estimation technology.

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Proposal of Teaching Materials Using Video Generative AI to Lower the Threshold of Practice for Beginners

  • 会议论文

  • 发表日期：

    2025年

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  • Haruhito Kobayashi,
  • Ryota Tanaka,
  • Naka Gotoda,
  • Ryo Kanda

摘要

As an issue in how to acquire physical skills by watching videos of skillful models, if the motions of beginners and skillful models are very different, there is a possibility that the threshold for practicing is high because self-efficacy does not occur. In this study, we propose to improve video teaching materials by using video generative AI to replace the appearance of a skillful model with that of a beginner, and by adjusting the trajectory of motion using skeletal estimation technology.