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Generative AI for Teaching-Learning-Assessment Integration in Primary and Secondary School Music Classrooms: Internal Logic, Risks, and Strategies

Li Jiaxin
Abstract
With the continuing digital transformation of education, generative AI (GenAI) is increasingly discussed as a possible means of supporting the integration of teaching, learning, and assessment in primary and secondary school music classrooms. This article uses GenAI as the main term rather than repeatedly using the full expression generative artificial intelligence; the related term AI-generated content (AIGC) is retained only when the discussion concerns AI-produced digital content. From the perspective of classroom alignment, GenAI can support music teaching in four ways: by helping teachers specify competency-oriented learning objectives, by expanding and reorganizing music learning content, by generating differentiated pedagogical options, and by providing timely evidence for formative assessment. At the same time, the use of GenAI in music classrooms may create new risks: the algorithmic blurring of learning objectives, the cultural flattening of diverse musical traditions, the over-standardization of artistic guidance, and the narrowing of assessment to measurable indicators. To address these risks, this article proposes four strategies: maintaining teachers’ pedagogical and ethical leadership, adapting GenAI-generated lesson plans through school-based curriculum development, developing music-specific large models and multimodal support tools, and building collaborative assessment mechanisms that combine quantitative analytics with professional artistic judgement. The study argues that GenAI should not replace teachers’ aesthetic, cultural, and educational agency. Its value lies in supporting a more responsive and evidence-informed music classroom while remaining subordinate to the aims of aesthetic education.
Keywords
Generative AI, Genai, AI-Generated Content, AIGC; Music Education, Teaching-learning-assessment Integration, Formative Assessment.
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