<![CDATA[Against the backdrop of rapid development in generative artificial intelligence technology, the definition, process, and evaluation standards of artistic creation are undergoing a profound transformation. This study takes “The Era of Prompts—A Challenge Letter from AI to Humanity” exhibition at Tainan Art Museum as the research field, employing mixed research methods to explore the multiple impacts and educational implications triggered by AI intervention in artistic creation. The research integrates exhibition ethnography, procedural scaffolding experimental design, and computational grounded theory analysis, conducting a three-stage learning journey experiment with 206 university students in southern Taiwan. The primary objective was to understand how university students perceive and engage with AI in the context of art creation, and to identify the core themes that emerge from their learning experiences. The main findings reveal five grounded themes of AI art learning: computational writing practice, emotional expression mediation, imperfection value reconstruction, collaborative relationship dynamics, and literacy requirement identification. These five themes interact spirally to form the theoretical model of “Adaptive Development of Art Learning in the AI Era.” The research concludes that art education in the AI era needs to construct new pedagogical paradigms that embrace technological innovation while maintaining human subjectivity, criticality, and emotional depth in creation. This study provides important references for theoretical construction and educational practice of AI art, offering a nuanced understanding of the human-AI creative partnership. The findings suggest that rather than viewing AI as a mere tool, it should be approached as a collaborator, a mediator of emotional expression, and a catalyst for re-evaluating the very nature of creativity. This research contributes to the fields of art education, human-computer interaction, and digital humanities by providing an empirically grounded framework for designing and evaluating AI-integrated learning environments.]]>
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