Leveraging A Large Language Model for Precision Enhancement in EFL Email Writing: A Quasi-Experimental Study

Abstract

Writing formal emails requires clarity, conciseness, and accuracy. Many English as a Foreign Language (EFL) learners find these skills challenging. Large Language Models (LLMs), such as ChatGPT, represent a significant advancement in natural language processing. However, their effectiveness in structured, task-specific language tasks for education is not well studied. This study investigates whether the GPT-3.5 model can assist EFL students in writing formal emails with greater precision and structural accuracy. The research treats the classroom as a real-world test case for the model’s abilities. It applied a quasi-experimental method. Data were collected from control and experimental groups (N = 60). The study used a test and semi-structured interviews. The results show ChatGPT improved formal email writing among EFL students. Qualitative findings highlight the tool’s ease of use and time-saving nature. ChatGPT also boosts clarity and confidence. Some concerns about overreliance on ChatGPT emerge. The tool sometimes struggled with subject lines, sign-offs, and signatures. This suggests that human intervention is needed. Contributing to AI-assisted pedagogy, this study shows how ChatGPT can improve EFL students' formal email writing skills.

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