Cultivating Innovative Modeling and Design Abilities in Art Curriculum Teaching That Integrates AI Technology

Artificial intelligence (AI) has become an important enabling technology for intelligent design, digital modeling, and human–computer collaborative innovation. To enhance students’ innovative modeling and design capabilities, this study investigates the integration of AI technology into art curriculum teaching through a human–AI collaborative framework that combines independent conceptualization, AI-assisted generation, critical evaluation, and iterative optimization. The proposed approach incorporates contextualized design practice and a diversified evaluation system supported by AI feedback mechanisms to promote creative thinking, design reasoning, and adaptive learning. By emphasizing student-centered interaction rather than automatic content generation, the framework effectively balances computational assistance with originality and aesthetic judgment. The proposed strategy improves design efficiency while encouraging iterative refinement and critical analysis throughout the creative process. Furthermore, the integration of multimodal AI technologies provides methodological references for intelligent visual information processing, digital modeling, and computer-aided engineering design. The resulting human–AI collaborative paradigm offers potential value for computational design optimization and intelligent decision support in engineering applications related to Electromagnetic Waves, Antennas and Propagation, where data-driven modeling, visual interpretation, and adaptive design workflows are increasingly important.