Examining the effect of generative AI on students’ motivation and writing self-efficacy
Jerry Huang, Atsushi Mizumoto · Digital Applied Linguistics · 2024
The present study explores the effects of generative AI, specifically ChatGPT, in EFL classrooms on student motivation and writing efficacy. Motivation was measured through three components: Ideal L2 Self (IL2), Ought-to L2 Self (OL2), and L2 Learning Experience (L2LE). Participants (n = 327) were first and second-year undergraduate students at a Japanese university, enrolled in mandatory English classes focused on reading/writing or speaking/listening. The control group (n = 164) received peer feedback, whereas the treatment group (n = 163) utilized ChatGPT with specially crafted prompts for feedback. Both groups completed pre- and post-questionnaires to assess motivation and writing self-efficacy. Results affirmed that ChatGPT positively affected students’ motivation related to Ideal L2 Self and L2 Learning Experience. ChatGPT also significantly enhanced writing self-efficacy, which was found to correlate with all three motivational factors. However, there was no impact on Ought-to L2 Self motivation. The study highlights that ChatGPT’s integration can improve intrinsic motivation and writing self-efficacy, provided structured guidance is available to manage issues such as plagiarism. Future research should examine diverse samples, long-term effects, and ChatGPT’s impact on other language skills.