A Case Study of High School Music Convergence Project Class Using Artificial Intelligence(AI) based on Actor-Network Theory

Objectives The purpose of this study is to deeply understand the interactions between various actors in the course of the music convergence project using AI. To this end, we intend to present the practical direction of music education using AI by interpreting the relationship and changes between actors in the actual educational field based on the stage of ‘translation’ in the Actor-Network Theory. Methods A case study was conducted with 13 students from a special purpose high school S located in Sejong Special Self-Governing City. In order to reveal the actual situation of the music education field by looking closely at specific class cases, and to examine the process of how various actors relate and what changes they make, data such as observation of class participation, in-depth interviews, and local data were collected from various angles and interpreted according to the ‘translation’ of the Actor-Network Theory. Results ln the problematization, teacher as researcher, student, artience subject, and sustainable development goals as exist in the context of each actor, and they began to form an alliance by establishing a common point of passage called ‘a project to create radio public service advertisements using AI’. As an interessement, the process-type evaluation was emphasized by presenting opportunities to explore various AI programs with the interest-seeking strategy used by the main actor. In the enrollment, the student actor dynamically changed, revealing four types of AI satisfaction, self-giving, self-compromise, and AI dissatisfaction, and succeed in registering all of them. In the last mobilization, the advertisement creations created by the students themselves were formalized to the entire class, transforming them into strong beings representing the network. The results suggest that four types of students need different pedagogical approaches depending on how AI is used. Conclusions This study is significant in that it shows that AI can serve as another actor actively interacting with students, rather than just a tool for music education, and suggests practical directions for AI-enabled music education by identifying the different ways and degrees to which students accept AI and suggesting pedagogical strategies accordingly.