Development of Music Content Elements and Performance Expectations to Cultivate AI Literacy

Objectives The purpose of this study was to develop content elements and performance expectations for integrating AI literacy with music, based on the emphasis on artificial intelligence utilization education in the revised 2022 curriculum. Methods Based on a literature review of AI literacy, this study extracted AI-related components from the “Elementary and Middle School Artificial Intelligence Education Content Standards” developed by the Ministry of Education. Subsequently, AI content elements relevant to music were identified and selected, and corresponding performance expectations for elementary and middle school levels were formulated. These content elements and performance expectations were categorized into principles and applications, aligned with the three domains of AI literacy: understanding, applying, and critiquing. Results In the “Understanding” domain, participants grasped principles related to ‘Collection and Exploration of Music Data’ and ‘Visualization and Prediction of Music Data,’ which were then applied to activities fostering an understanding of ‘Music Elements and Characteristics through AI Utilization.’ Within the “Applying” domain, principles grounded in ‘AI Advancements and Diverse Musical Applications’ were employed for activities involving ‘Performance, Creation, and Appreciation through AI-Driven Music Engagement.’ In the “Critiquing” domain, principles concerning ‘Understanding Bias and Promoting Diversity in Music Data’ and ‘Ethics and Responsible Usage of AI in Music’ were identified. This section further encapsulates content elements and performance expectations that can be utilized to comprehend broader aspects of life and careers coexisting with AI in music, extending to the ‘Copyright and Artistic Value of AI-Generated Music Works.’ Conclusions The AI literacy-enriched music content elements and performance expectations developed in this study are expected to offer insights into the future direction of curriculum development and instructional strategies within the context of AI education. These contributions are anticipated to guide the implementation of music curricula that can effectively integrate with the evolving AI education landscape, shaping the trajectory of teaching and learning.