ChatGPT and L2 Chinese writing: evaluating the impact of model version and prompt language on automated corrective feedback

Christine Ting Yu Yang, Howard Hao Jan Chen*

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

摘要

The rapid emergence of generative artificial intelligence (GAI) models like ChatGPT has sparked significant interest in their application for language learning, particularly for second language (L2) writing. Given the urgent need for effective tools in Chinese grammar checking to assist L2 learners, this study evaluated the impact of both model version (ChatGPT-3.5 vs 4.0) and prompt language (Chinese vs English) on the effectiveness of automated corrective feedback (ACF) for L2 Chinese writing. Utilizing a dataset of 153 erroneous single-sentence examples from a Routledge-published textbook on Chinese, we assessed error corrections and corrective feedback generated by both ChatGPT versions under different language prompts. Three experienced language teachers evaluated the output corrections for grammaticality, fluency, minimal alterations, and over-correction, and the output feedback for correctness, understandability, and detail. Findings revealed that although both model versions produced grammatically correct and fluent corrections, ChatGPT-4.0 demonstrated superior performance in generating more accurate, detailed, and understandable corrective feedback compared to ChatGPT 3.5. The results suggest that model version significantly influences ChatGPT’s effectiveness as a multilingual ACF tool, more so than prompt language. This study highlights the potential of advanced GAI, such as ChatGPT-4.0, in enhancing language instruction and error correction for languages beyond English. It advocates for further research on the application of such models in diverse linguistic and educational contexts.

原文英語
期刊Computer Assisted Language Learning
DOIs
出版狀態接受/付印 - 2025

ASJC Scopus subject areas

  • 語言與語言學
  • 語言和語言學
  • 電腦科學應用

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