Generative AI in EFL writing instruction for lower-intermediate learners: Do perceived affective gains translate to improved performance?

Abstract

This mixed-methods study examined the impact of integrating generative artificial intelligence (GenAI) into English as a foreign language (EFL) writing classes on students’ writing performance and affective responses. Nearly 100 Chinese students from four parallel International English Language Testing System (IELTS) writing classes in a university foundation program participated in a 9-week trial, with half assigned to an experimental group and half to a control group. Both groups received theme-based instructions on IELTS Writing Task 2 through a three-stage writing process, while the experimental group also engaged with Kimi, a widely used GenAI chatbot in China, during and after class. Unlike previous studies, this research targeted lower-intermediate learners and aimed to offer a more nuanced understanding of GenAI’s role by employing natural language processing (NLP)-based evaluations and linear mixed-effect models in the quantitative analysis. The pretest and posttest results showed that GenAI-assisted instruction did not significantly improve students’ writing performance except in syntactic complexity. The questionnaire and interview data, however, indicated that this approach positively influenced learners’ motivation, engagement, and self-efficacy. Further analysis suggested that the discrepancy between students’ improvements in writing performance and their reported affective gains may be attributed to limited learner agency, a lack of teacher support outside class, and misalignment between their English proficiency levels, cognitive readiness, and GenAI’s affordances. The study concludes with implications for second-language writing instruction and directions for future research.