ChatGPT,a cutting-edge AI-powered Chatbot,can quickly generate responses on
given commands. While it was reported that ChatGPT had the capacity to deliver
useful feedback, it is still unclear about its effectiveness compared with
conventional feedback approaches,such as teacher feedback (TF) and
self-feedback (SF). To address this issue, this study compared the revised
Chinese to English translation texts produced by Chinese Master of Translation
and Interpretation (MTI) students,who learned English as a Second/Foreign
Language (ESL/EFL), based on three feedback types (i.e., ChatGPT-based
feedback, TF and SF). The data was analyzed using BLEU score to gauge the
overall translation quality as well as Coh-Metrix to examine linguistic
features across three dimensions: lexicon, syntax, and cohesion.The findings
revealed that TF- and SF-guided translation texts surpassed those with
ChatGPT-based feedback, as indicated by the BLEU score. In terms of linguistic
features,ChatGPT-based feedback demonstrated superiority, particularly in
enhancing lexical capability and referential cohesion in the translation texts.
However, TF and SF proved more effective in developing syntax-related skills,as
it addressed instances of incorrect usage of the passive voice. These diverse
outcomes indicate ChatGPT's potential as a supplementary resource,
complementing traditional teacher-led methods in translation practice.

通过对聊天机器人 ChatGPT、教师反馈和自我反馈这三种不同反馈方法的比较研究，发现教师反馈和自我反馈在整体翻译质量和语言特征方面均优于 ChatGPT 反馈，但 ChatGPT 反馈在提高词汇能力和修辞连贯性方面表现出优势。因此，ChatGPT 作为辅助资源可有效补充传统教师指导下的翻译实践。