Using AI-Generated Animations to Support Emotional and Visual Learning of Classical Chinese Poetry: An Exploratory Document Analysis of the Qian Qiu Shi Song Project

Abstract

Artificial intelligence is reshaping education by creating new opportunities for more creative, engaging, and meaningful learning. In classical Chinese poetry, AI offers ways to modernise lessons that were once limited to memorisation and translation. This study examines how AI can support teachers in designing learning experiences that help students appreciate poetry in deeper and more personal ways. A qualitative case study was used to investigate the “Qian Qiu Shi Song” (Everlasting Songs) project, China’s first AI-generated animation series based on more than 200 classical poems. Document analysis was guided by three analytic dimensions which are scene creation, layered learning progression, and emotional connection. The analysis identified five themes: AI-driven poetic scene creation, layered learning progression, emotional connection through scenario restoration, the changing role of teachers, and increased cultural engagement among students. The findings show that AI can visualise poetic imagery, structure learning in clearer stages, and rebuild the emotional and historical settings of poems. These contributions make poetry learning more interactive, engaging, and personalised. AI also supports teachers in shifting from information delivery to guiding exploration and helps students form stronger emotional and cultural connections with classical poetry. Overall, AI functions not only as a technological tool but also as a learning partner that enriches cultural understanding and supports the preservation of literary heritage.