University students’ readiness for ChatGPT-assisted English learning: an explanatory mixed-methods study

Abstract

The growing integration of generative artificial intelligence (AI), particularly ChatGPT, in English as a Foreign Language (EFL) learning has raised increasing interest in learners' readiness to engage with such tools effectively. However, existing research has largely focused on isolated constructs such as technology acceptance and AI literacy, providing limited insight into learners' overall preparedness in authentic learning contexts. This study therefore investigates university students' readiness for ChatGPT-assisted English learning from a multidimensional perspective. An explanatory sequential mixed-methods design was employed. Quantitative data were collected from 586 undergraduate students using the Learners’ Readiness for ChatGPT-Assisted English Learning (LRCEL) scale developed and validated by Luo and Zou (2024b), followed by semi-structured interviews with 12 participants to explain the quantitative findings. The results indicate that students demonstrated relatively high levels of operational readiness, particularly in perceived behavioral control, attitude, and enjoyment. However, readiness was not stable, as intention to use ChatGPT remained moderate and highly dependent on task conditions. In addition, a clear gap was identified between students’ ability to use ChatGPT and their capacity to critically evaluate its outputs. The findings further reveal that readiness is socially constructed, with peer networks playing a more influential role than teachers in shaping students’ engagement with ChatGPT. These findings suggest that learner readiness is dynamic, uneven, and context-dependent, highlighting the need to reconceptualize readiness beyond purely cognitive or technical dimensions in AI-assisted language learning.