比较人工制作和人工智能生成的教学视频:学习效果实验研究

IF 8.9 1区 教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Education Pub Date : 2024-09-21 DOI:10.1016/j.compedu.2024.105164
Torbjørn Netland, Oliver von Dzengelevski, Katalin Tesch, Daniel Kwasnitschka
{"title":"比较人工制作和人工智能生成的教学视频:学习效果实验研究","authors":"Torbjørn Netland,&nbsp;Oliver von Dzengelevski,&nbsp;Katalin Tesch,&nbsp;Daniel Kwasnitschka","doi":"10.1016/j.compedu.2024.105164","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"224 ","pages":"Article 105164"},"PeriodicalIF":8.9000,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparing human-made and AI-generated teaching videos: An experimental study on learning effects\",\"authors\":\"Torbjørn Netland,&nbsp;Oliver von Dzengelevski,&nbsp;Katalin Tesch,&nbsp;Daniel Kwasnitschka\",\"doi\":\"10.1016/j.compedu.2024.105164\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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.</div></div>\",\"PeriodicalId\":10568,\"journal\":{\"name\":\"Computers & Education\",\"volume\":\"224 \",\"pages\":\"Article 105164\"},\"PeriodicalIF\":8.9000,\"publicationDate\":\"2024-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Education\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0360131524001787\",\"RegionNum\":1,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Education","FirstCategoryId":"95","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360131524001787","RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

摘要

在生成式人工智能时代,大型语言模型能否高效生成教学视频?在这项研究中,作者使用生成式人工智能工具为一门管理课程制作了四个教学视频短片,然后在一项在线实验中将它们与人工生成的视频进行了比较。在跨受试者实验设计中,447 名参与者完成了两种处理条件,分别呈现了人工智能生成视频和人工制作视频的不同组合。参与者在观看完每段视频后都要对自己的学习体验进行评分,并在课程结束时进行选择题考试,测试他们的学习成果(N = 1788 次视频处理)。研究结果表明,人类生成的视频在学习体验方面给参与者带来了显著的统计学优势,但优势很小,这表明参与者仍然更喜欢由人类教师授课。不过,对各实验组考试成绩的比较表明,学员最终获得的内容知识程度相近。鉴于这些发现和人工智能生成教学视频的便捷性,本研究得出结论,人工智能生成的教学视频很可能会大量出现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Comparing human-made and AI-generated teaching videos: An experimental study on learning effects
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Computers & Education
Computers & Education 工程技术-计算机:跨学科应用
CiteScore
27.10
自引率
5.80%
发文量
204
审稿时长
42 days
期刊介绍: Computers & Education seeks to advance understanding of how digital technology can improve education by publishing high-quality research that expands both theory and practice. The journal welcomes research papers exploring the pedagogical applications of digital technology, with a focus broad enough to appeal to the wider education community.
期刊最新文献
Unpacking help-seeking process through multimodal learning analytics: A comparative study of ChatGPT vs Human expert A meta-analysis on the effect of technology on the achievement of less advantaged students Personalization in educational gamification: Learners with different trait competitiveness benefit differently from rankings on leaderboards Plugging in at school: Do schools nurture digital skills and narrow digital skills inequality? Reducing interpretative ambiguity in an educational environment with ChatGPT
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1