Adapting AI-Assisted Translation Didactics for Chinese–English Political Translation

This paper explores the adaptation of the AI-assisted translation teaching methodology proposed by Linder (2025) for a specialized course on translating Chinese political texts into English. Linder’s experimental didactic approach centers on student-led AI tool experimentation, collaborative learning and critical evaluation of AI translation outputs. By analysing the unique linguistic, cultural and ideological characteristics of Chinese political texts, this paper modifies Linder’s framework to address the specific challenges of translating political material from Chinese to English, including Chinese characteristic political terms, syntactic complexity and the transmission of cultural-ideological connotations. The adapted model integrates authoritative Chinese political terminology, prompt engineering for AI tools, and a triangulation approach comparing student-AI collaborative translations with official authoritative versions. It also incorporates ethical considerations for AI in cross-linguistic political communication. This paper argues that the adapted methodology not only cultivates students’ technical translation skills, but also enhances their cross-cultural critical thinking and human-AI negotiation capabilities, which are essential for promoting accurate and effective international dissemination of Chinese political discourse.