Singing Syllabi with Virtual Avatars: Enhancing Student Engagement Through AI-Generated Music and Digital Embodiment

Wu, Xinxing

arXiv.org Artificial Intelligence 

In practical teaching, we observe that few students thoroughly read or fully comprehend the information provided in traditional, text-based course syllabi. As a result, essential details, such as course policies and learning outcomes, are frequently overlooked. To address this challenge, in this paper, we propose a novel approach leveraging AI-generated singing and virtual avatars to present syllabi in a format that is more visually appealing, engaging, and memorable. Especially, we leveraged the open-source tool, HeyGem, to transform textual syllabi into audiovisual presentations, in which digital avatars perform the syllabus content as songs. The proposed approach aims to stimulate students' curiosity, foster emotional connection, and enhance retention of critical course information. Student feedback indicated that AI-sung syllabi significantly improved awareness and recall of key course information.