Designing AI Sandboxes for Human-Machine Pedagogies

Abstract

This chapter investigates the multifaceted potentials of artificial intelligence (AI) in music education through two case studies that examine how generative AI tools can be meaningfully integrated into teaching, learning, and creative processes for preservice music teachers and undergraduate students in the arts. Grounded in design-based research and focused on reimagining educational processes, these case studies cover how human–machine interactions might reshape the ontologies and pedagogies of music teachers and music teacher educators, while supporting relational ethics, multimodal fluency, and joint-inquiry with AI tools. The first case study involved a creative-production AI sandbox (i.e., an exploratory AI-rich learning environment) where undergraduates engaged in problem-first tool chaining (i.e., using a range of generative AI tools to create multimodal responses to personally relevant social and cultural issues). The second included a teaching-rehearsal sandbox featuring Classroom Coach, a GPT-powered simulation in which preservice music teachers interacted with responsive AI-driven student avatars to navigate classroom dilemmas, relational ethics, and pedagogical decision-making in real time. Across both cases, students learned to approach generative AI interfaces as manipulable environments for training, design, inquiry, and reflection. Together, these studies illustrate how AI might be integrated into music teacher education to support new forms of professional development, creative engagement, and ethical practice in AI-mediated contexts. The chapter concludes by offering insights to inform future sandbox design, advocating for AI literacy, the integration of AI in both creative and relational practices, and sustained interdisciplinary collaboration across music education, musicology, cognitive science, computer science, and human-computer interaction.