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

Authors: Yue Yu; Ruolin Sun

Addresses: Qinhuangdao Vocational and Technical College, No. 90 Lianfeng North Road, Beidaihe District, Qinhuangdao City, 066000, Hebei Province, China ' Qinhuangdao Vocational and Technical College, No. 90 Lianfeng North Road, Beidaihe District, Qinhuangdao City, 066000, Hebei Province, China

Abstract: Artificial intelligence in arts education (AIAEd) has rapidly expanded, yet its conceptual evolution remains underexamined. This study systematically reviews 372 Web of Science publications using latent Dirichlet allocation and computational grounded theory to map the field's paradigmatic development. Five thematic clusters emerge: fundamental principle design, technological and interdisciplinary expansion, AI-driven educational models, intelligent behavioural evaluation, and personalised creative learning. A six-stage evolutionary analysis reveals a trajectory from early exploratory work to systematised design, discipline-specific applications, metaverse-supported visual pedagogies, and the recent shift toward generative AI and multidimensional learner modelling. The latest stage highlights creativity-oriented AI tools, affect-aware feedback, and socio-health dimensions of evaluation. Findings indicate a delayed but decisive transition from technology-centred experimentation to human-centred, creativity-enhancing AIAEd frameworks.

Keywords: Artificial intelligence in arts education; AIAEd; computational grounded theory; CGT; topic modelling; generative artificial intelligence; pedagogical design and evaluation.

DOI: 10.1504/IJART.2028.155022

International Journal of Arts and Technology, 2028 Vol.16 No.8, pp.1 - 36

Received: 07 Nov 2025
Accepted: 09 Feb 2026
Published online: 22 Jul 2026 *