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