Comparing human and LLM proofreading in L2 writing: Impact on lexical and syntactic features
This addresses proofreading effectiveness for L2 learners, but it is incremental as it compares existing methods on new data.
The study compared human and LLM proofreading for second language writing, finding that both improved bigram lexical features, with LLMs showing more generative changes like diverse vocabulary and adjective modifiers, and outcomes were consistent across three LLM models.
This study examines the lexical and syntactic interventions of human and LLM proofreading aimed at improving overall intelligibility in identical second language writings, and evaluates the consistency of outcomes across three LLMs (ChatGPT-4o, Llama3.1-8b, Deepseek-r1-8b). Findings show that both human and LLM proofreading enhance bigram lexical features, which may contribute to better coherence and contextual connectedness between adjacent words. However, LLM proofreading exhibits a more generative approach, extensively reworking vocabulary and sentence structures, such as employing more diverse and sophisticated vocabulary and incorporating a greater number of adjective modifiers in noun phrases. The proofreading outcomes are highly consistent in major lexical and syntactic features across the three models.