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ChatGPT,a cutting-edge AI-powered Chatbot,can quickly generate responses ongiven commands. While it was reported that ChatGPT had the capacity to deliveruseful feedback, it is still unclear about its effectiveness compared withconventional feedback approaches,such as teacher feedback (TF) andself-feedback (SF). To address this issue, this study compared the revisedChinese to English translation texts produced by Chinese Master of Translationand Interpretation (MTI) students,who learned English as a Second/ForeignLanguage (ESL/EFL), based on three feedback types (i.e., ChatGPT-basedfeedback, TF and SF). The data was analyzed using BLEU score to gauge theoverall translation quality as well as Coh-Metrix to examine linguisticfeatures across three dimensions: lexicon, syntax, and cohesion.The findingsrevealed that TF- and SF-guided translation texts surpassed those withChatGPT-based feedback, as indicated by the BLEU score. In terms of linguisticfeatures,ChatGPT-based feedback demonstrated superiority, particularly inenhancing lexical capability and referential cohesion in the translation texts.However, TF and SF proved more effective in developing syntax-related skills,asit addressed instances of incorrect usage of the passive voice. These diverseoutcomes indicate ChatGPT's potential as a supplementary resource,complementing traditional teacher-led methods in translation practice.

Exploring the effectiveness of ChatGPT-based feedback compared with teacher feedback and self-feedback: Evidence from Chinese to English translation