Enhancing Visual Art Appreciation through AI-Human Collaboration: A Case Study of Image-Literacy-Aided Instruction with Doubao

This study investigates the integration of AI-assisted dialogue and image-literate instruction in primary art education, grounded in neuroscience models of multisensory information processing. Drawing inspiration from the visual-auditory convergence in the lateral and medial geniculate nuclei, the instructional design leverages Doubao—a conversational AI with voice output—to iteratively engage students in decoding traditional Chinese artworks. Conducted over four weeks with 253 sixth-grade students across six classes, the curriculum focused on selected works from the painting Lady Guoguo's Spring Outing, a classic from the Tang Dynasty and one of the Top Ten Chinese Paintings. Students were guided to observe visual elements, inquire into unfamiliar cultural symbols, and refine their interpretations through voice-augmented AI dialogue. The system's responsive feedback loop encouraged successive questioning, style transfer-based imaginative tasks, and repeated information verification. This process enhanced students’ curiosity and strengthened their ability to evaluate information reliability by layering and comparing contextual cues. Results indicate that combining image and sound through human-AI collaboration fosters deeper engagement, cultural literacy, and metacognitive awareness in visual art learning.