Metacognitive and Self-Directed Learning in AI-Mediated Art Education: A Systematic Literature Review

This systematic literature review examines the intersection of metacognition, self-directed learning (SDL), and artificial intelligence (AI) in art education contexts. Synthesizing evidence from 17 empirical and theoretical studies published between 2018 and 2025, this review spans museum education, music performance, visual arts, dance, architecture, film/animation, and general creativity research to elucidate how metacognitive strategies and self-regulated learning (SRL) frameworks function within technology-mediated and AI-enhanced creative learning environments. The analysis reveals four core thematic clusters: (1) metacognitive scaffolding through reflective tools and structured protocols in artistic domains; (2) self-regulated learning cycles (forethought-performance-self-reflection) adapted for creative practices; (3) creative self-beliefs and domain specificity across art forms; and (4) emerging AI-mediated personalization and human-AI collaborative creativity. Key findings indicate that metacognitive awareness—encompassing planning, monitoring, and evaluation—serves as the critical bridge between creative potential and creative performance across diverse artistic disciplines. Physical and digital reflective tools (e.g., structured portfolios, video-stimulated recall, appreciation skills cards, and museum thinking routines) consistently enhance learners' strategic self-regulation. Evidence from cross-domain studies, including mobile-assisted learning and cross-cultural cognition research, confirms that metacognitive scaffolding mechanisms are transferable across creative contexts, though domain-specific adaptations remain essential. In AI-mediated contexts, generative AI tools (DALL-E, Midjourney, Stable Diffusion) function as "creative partners" rather than replacements, necessitating new forms of metacognitive oversight to manage algorithmic bias, originality assessment, and human-AI co-creation dynamics. The review identifies significant gaps: limited empirical research on AI-specific metacognitive interventions in art education; underexplored cross-cultural validity of metacognitive instruments in artistic contexts; and insufficient longitudinal designs tracking SRL development from novice to expert levels in creative domains. The paper proposes an integrated theoretical framework—**Metacognitive-AI Art Education (MAAI-E)**—positioning metacognition as the "belt holding all tools together" in AI-augmented creative pedagogy, with implications for curriculum design, assessment innovation, and teacher professional development in the digital age.

metacognition, self-directed learning, art education, artificial intelligence, creative performance

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