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This study aims to systematically review the evolution and thematic trends of AI in arts education.

Trends and topics in arts education and artificial intelligence: a systematic review using a human-in-the-loop model

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Systematic review maps thematic clusters in arts education and artificial intelligence, highlighting creative frameworks.

This study aims to systematically review the evolution and thematic trends of AI in arts education.
Analyzed 372 publications from Web of Science using latent Dirichlet allocation and computational grounded theory.
Identified five thematic clusters regarding the development of AIAEd frameworks.
Conducted a six-stage evolutionary analysis to trace the progression of AIAEd.
Five thematic clusters identified: design principles, interdisciplinary expansion, educational models, behavioural evaluation, and creative learning.
Revealed a shift from technology-centered to human-centered frameworks in arts education.
Noted the emergence of creativity-oriented AI tools and socio-health aspects in evaluation processes.

Yu et al. (2026) studied this question.

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