AI-assisted writing among Chinese EFL learners in a private higher education institution: A mixed-method study

Xu, Xiaoyan (2025) AI-assisted writing among Chinese EFL learners in a private higher education institution: A mixed-method study. Final Year Project, UTAR.

PDF Download (1316Kb)

Abstract

The advent of AI Tools has precipitated a paradigm shift in second language acquisition, offering new possibilities for academic writing support. This study empirically investigates the application of AI-assisted writing tools among Chinese English as a Foreign Language (EFL) learners in a private higher education institution. Despite the growing popularity of tools like ChatGPT, empirical evidence regarding how students in private educational settings engage with these technologies remains underexplored. This research aims to examine students’ frequency of use, perceived efficacy, and the ethical dilemmas they encounter. Utilizing a quantitative research design, a survey was administered to 61 participants from the Faculty of Arts and Social Science and Faculty of Education. The results indicate a high adoption rate, with students primarily utilizing AI for lexical resource expansion, translation, and grammatical correction. Significantly, findings suggest that while AI tools enhance writing efficiency and self-efficacy, they also trigger anxiety regarding plagiarism and a potential decline in critical thinking skills. The study concludes that integrating AI into EFL curriculum requires a balanced pedagogical approach, emphasizing critical AI literacy and clear ethical guidelines to foster independent writing competence.

Actions (login required)