From recorded to AI‐generated instructional videos: A comparison of learning performance and experience

计算机科学 心理学 多媒体 数学教育
作者
Tao Xu,Yu Liu,Yaru Jin,Yuxiao Qu,Jie Bai,Wenlan Zhang,Yun Zhou
出处
期刊:British Journal of Educational Technology [Wiley]
被引量:1
标识
DOI:10.1111/bjet.13530
摘要

Abstract Generative AI (GAI) and AI‐generated content (AIGC) have been increasingly involved in our work and daily life, providing a new learning experience for students. This study examines whether AI‐generated instructional videos (AIIV) can facilitate learning as effectively as traditional recorded videos (RV). We propose an instructional video generation pipeline that includes customized GPT (Generative Pre‐trained Transformer), text‐to‐speech and lip synthesis techniques to generate videos from slides and a clip or a photo of a human instructor. Seventy‐six students were randomly assigned to learn English words using either AIIV or RV, with performance assessed by retention, transfer and subjective measures from cognitive, emotional, motivational and social perspectives. The findings indicate that the AIIV group performed as well as the RV group in facilitating learning, with AIIV showing higher retention but no significant differences in transfer. RV was found to offer a stronger sense of social presence. Although other subjective measures were similar between the two groups, AIIV was perceived as slightly less favourable. However, the AIIV was still found to be moderately to highly attractive, addressing concerns related to the uncanny valley effect. This research demonstrates that AIGC can be an effective tool for learning, offering valuable implications for the use of GAI in educational settings. Practitioner notes What is already known about this topic Instructional videos, especially those featuring a teacher's presence, have been widely used in second language learning to facilitate learning. Producing instructional videos is costly and burdensome. Generative AI has great potential for generating educational content. What this paper adds An AI‐generated instructional video (including generated lecture text, voice and appearance) demonstrated greater improvement in students' retention performance in English word learning than a traditional recorded video. Students perceived no significant differences between the AI‐generated instructional video and recorded video in satisfaction, motivation, trust, cognitive load, emotions and parasocial interaction dimensions, although the AI‐generated instructional video group reported slightly lower values. Despite AI‐generated instructional video eliciting a significantly lower value of social presence than recorded video, it led to a reduction in cognitive load and better performance. Implications for practice and/or policy We recommend using the AI‐generated instructional video in both physical and online classes for its positive effects on both learning achievement and learning experience. The findings indicate the equivalence principle in AI‐generated content, highlighting that the appearance, voice and lecture text generated by current AI technology have reached a certain level of quality.
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