A Study on the Path and Practice of Chinese Cultural Dissemination in College English Classrooms Driven by AI

Abstract

Current college English teaching faces a persistent limitation in students’ ability to express Chinese culture in English, which weakens their capacity to explain Chinese cultural concepts accurately in international communication. To address this issue, this study constructs an AI-driven end-to-end teaching path for Chinese cultural dissemination in college English classrooms. First, natural language processing is used to build a bilingual corpus of Chinese culture and establish a structured knowledge base of core cultural terms. Second, generative AI is applied to dynamically generate personalized learning resources and virtual scenarios. Third, an intelligent interaction platform is constructed to provide real-time feedback and critical thinking guidance. Finally, learning analytics is used to build comprehensive competency profiles. Experimental results show that the experimental class significantly outperforms the control class in cultural accuracy and fluency, reaching 84.6 ± 6.3 and 81.9 ± 5.8, respectively. Students’ cross-cultural critical thinking scores increase by 13.6-18.0 points across dimensions, and 93.3% of students express willingness to actively promote Chinese culture. The proposed path improves cultural expression accuracy, learning engagement, and classroom dissemination effectiveness.