Revolutionising Faculty Development and Continuing Medical Education Through AI-Generated Videos.

Journal of CME Pub Date : 2024-12-06 eCollection Date: 2024-01-01 DOI:10.1080/28338073.2024.2434322
Irene Contreras, Samia Hossfeld, Katharine de Boer, Jane Thorley Wiedler, Monica Ghidinelli
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Abstract

Producing high-quality and engaging educational videos for continuing medical education (CME) is traditionally time-consuming and costly. Generative AI tools have shown promise in creating synthetic videos that mimic traditional lecture videos. We conducted a comparative analysis of four AI video generation platforms HeyGen, Synthesia, Colossyan, and HourOne using the Kano model. Our analysis revealed that HeyGen met most of our requirements. We created two videos and collected feedback from 25 learners. The feedback indicated that the videos were of good quality, engaging, and well-paced for learning. Only 32% recognised the videos as AI-generated, citing limited facial expressions, hand gestures and monotone vocal expression. Importantly, only 24% considered disclosure of AI-generated content necessary. This research indicates that AI-generated videos can be a viable alternative to traditionally produced educational videos. It offers an efficient, cost-effective solution for producing educational content. Ethical considerations regarding AI content disclosure should be addressed to maintain transparency.

传统上,为继续医学教育(CME)制作高质量、引人入胜的教育视频既费时又费钱。人工智能生成工具在制作模仿传统讲座视频的合成视频方面大有可为。我们使用卡诺模型对四种人工智能视频生成平台 HeyGen、Synthesia、Colossyan 和 HourOne 进行了比较分析。分析结果显示,HeyGen 满足了我们的大部分要求。我们制作了两个视频,并收集了 25 名学习者的反馈。反馈显示,视频质量上乘,引人入胜,学习节奏明快。只有 32% 的人认为视频是人工智能生成的,理由是面部表情、手势和单调的声音表达有限。重要的是,只有 24% 的人认为有必要披露人工智能生成的内容。这项研究表明,人工智能生成的视频可以替代传统制作的教育视频。它为制作教育内容提供了一种高效、经济的解决方案。有关人工智能内容披露的伦理考虑因素应予以解决,以保持透明度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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