Journal Paper Published

Abstract

English as a lingua franca plays a central role in international communication, yet it poses persistent challenges for non-native users, particularly in achieving textual cohesion, which is essential for clarity and communicative effectiveness. ESL (English as a second language) student translators often struggle to manage cohesion through the appropriate use of connectives when translating into English. The emergence of generative artificial intelligence (GenAI) has created new possibilities for supporting language learners and translators in producing cohesive texts. This study examines the potential and limitations of GenAI in generating cohesive Chinese-English translations by comparing its outputs with those produced by ESL learner translators, using sense-aware connective-based cohesion indices. The results show that, although the two groups display largely similar overall patterns in the use of discourse and non-discourse connectives, they differ substantially in specific connective categories. GenAIgenerated translations show a greater reliance on comparison and expansion connectives and a relative underuse of contingency connectives, whereas ESL learner translations tend to preserve source text discourse relations more closely. These findings provide insights into the cohesion characteristics of GenAI-generated translations and point to important considerations for language learning and translation pedagogy.

Keywords

Generative artificial intelligence, ESL learners, translation, cohesion