中国电化教育

在当今人工智能蓬勃发展的时代,以ChatGPT、 Sora、 DeepSeek等为代表的生成式人工智能(AIGC)正赋能艺术教育的系统化变革。该文深入剖析AIGC赋能艺术教育的现实图景、学理逻辑、作用机制与实践路径。研究发现, AIGC在艺术教育中的应用图景主要体现为“实证+实践”的教学模式革新、人机协同的主体性重构以及价值取向从共性育人向多元生成的嬗变。从学理层面看, AIGC作为认知工具与关系中介,推动学生艺术认知从经验性积累向创造性升维的跃迁,借助“拟主体”身份介入促进主体间性转向,必然会引发规则、分工与共同体互动的其他要素的连锁变革与重构,并最终导向复合型的艺术教育培养价值取向。在此基础上,构建以艺术教育课程三阶段为载体的动态作用模型,揭示AIGC在课程实施过程中持续优化与自我演进的运行逻辑。并据此提出了重构跨学科融合的复合型教学场景、推进人机协同的师生角色转型、完善艺术人才培养的多维评价体系的实践路径。

In the era of rapid AI advancement, generative artificial intelligence(AIGC), exemplified by platforms like Chat GPT, Sora, and DeepSeek, is driving a systematic transformation in art education. This study provides an in-depth analysis of the practical context, theoretical underpinnings, mechanisms, and implementation pathways of AIGC in art education. The results reveal that AIGC application primarily innovates through an “ empirical-practice integrated teaching model” teaching model, fosters human-machine collaborative subjectivity, and shifts value orientations from standardized cultivation towards diversified creation. Theoretically, AIGC serves as both a cognitive instrument and a relational medium, facilitating a shift in students' artistic cognition from experiential accumulation to creative transcendence. By intervening as a quasisubject, AIGC instigates an intersubjective turn. This shift necessarily entails the restructuring of rules, role differentiation, and other communal dynamics, thereby steering art education toward a generative and holistic value orientation. Building on this, we construct a dynamic mechanism model grounded in the three-phase art education curriculum to elucidate how AIGC continuously self-optimizes and evolves during instructional implementation. Accordingly, we propose practical pathways: designing interdisciplinary teaching ecologies, advancing teacher-student role transformation within human-machine collaborative, and refining multidimensional evaluation systems for artistic talent development.