In the age of generative AI, can teaching videos be efficiently and effectively generated by large language models? In this study, the authors used generative AI tools to develop four short teaching videos for a management course and then compared them with human-generated videos on the same subjects in an online experiment. In an across-subject experimental design, 447 participants completed two treatment conditions presenting different mixes of AI-generated and human-made videos. The participants were asked to rate their learning experiences after each video and had their learning outcomes tested in a multiple-choice exam at the end of the session (N = 1788 video treatments). The findings show that human-generated videos provided a statistically significant but small advantage to participants in terms of learning experience, indicating that the participants still prefer to be taught by human teachers. However, a comparison of exam results between the experimental groups implies that the participants eventually acquired knowledge about the content to a similar degree. Given these findings and the ease with which AI-generated teaching videos can be created, this study concludes that AI-generated teaching videos will likely proliferate.

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比较人工和 AI 生成的教学视频：学习效果的实验研究


在生成式 AI 时代，大型语言模型能否高效且有效地生成教学视频？在这项研究中，作者使用生成式 AI 工具为一门管理课程制作了四个简短的教学视频，然后在在线实验中将它们与相同主题的人工生成的视频进行了比较。在一项跨受试者实验设计中，447 名参与者完成了两种治疗条件，展示了 AI 生成和人工制作视频的不同组合。参与者被要求在每个视频后对他们的学习体验进行评分，并在课程结束时通过多项选择题测试他们的学习成果（N = 1788 个视频处理）。研究结果表明，人工生成的视频在学习体验方面为参与者提供了具有统计学意义但很小的优势，这表明参与者仍然更喜欢由人类教师授课。然而，实验组之间的考试结果比较意味着参与者最终获得了类似程度的有关内容的知识。鉴于这些发现以及 AI 生成的教学视频的创建便利性，本研究得出结论，AI 生成的教学视频可能会激增。