responsible-ai
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- PaperEdArXiv (OSF Preprints)21 Jul 2026
Toward Responsible AI Implementation in K–12 Music Education: A Human-Centered Conceptual Framework Informed by Emerging U.S. Educational Priorities
Jose Gregorio Reinoso Yepez
A conceptual framework for responsible AI implementation in K-12 music education is proposed, drawing on U.S. educational priorities and international governance. The framework centers on pedagogy, teacher leadership, AI literacy, and ethical governance, positioning AI as a support tool that preserves teacher agency. While focused on music education, the principles may apply to other K-12 subjects.
Original abstract
Artificial intelligence (AI) is increasingly reshaping K–12 education, influencing curriculum design, instructional practice, and educational governance. Emerging U.S. priorities emphasize not only technological innovation but also responsible implementation, AI literacy, data privacy, and equitable access. These priorities are especially relevant to K–12 music education, where learning depends on cognitive, artistic, emotional, and social dimensions requiring sustained teacher guidance. Although AI-supported tools offer promising applications for adaptive practice, automated feedback, and AI-assisted composition, their value depends on implementation conditions that preserve pedagogical integrity and teacher agency. This conceptual article develops a Human-Centered Conceptual Framework for Responsible AI Implementation in K–12 Music Education, drawing on U.S. priorities, international governance frameworks, and contemporary scholarship. The framework positions AI as a support system within an educational ecosystem shaped by pedagogy, educator leadership, AI literacy, ethical governance, professional capacity building, and continuous improvement, offering a conceptual foundation for future research, policy, and practice in music education and other K–12 settings.