Investigating EFL Students’ Adoption of Generative Artificial Intelligence for English Learning through UTAUT2 and SDT: A Mixed-Methods Study

Generative artificial intelligence (GenAI) continues to transform English learning, but the influence of psychological needs on maintaining students’ engagement remains insufficiently studied. Therefore, the study used the unified theory of acceptance and use of technology (UTAUT2) and self-determination theory (SDT) within an explanatory sequential mixed-methods design to explore the factors affecting English as a foreign language (EFL) students’ intention and actual use of GenAI for English learning. Quantitative data were gathered from 462 EFL students and analyzed with PLS-SEM in SmartPLS 4, while the qualitative phase included 15 semi-structured interviews analyzed thematically. The findings showed that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit significantly influenced EFL students’ intention to use GenAI for English learning. Although SDT components-perceived autonomy, perceived competence, and perceived relatedness-did not significantly impact behavioral intention, both the SDT components and behavioral intention predicted actual usage. Thematic analysis of the interview data identified five key themes: perceived performance gains, ease of use and habitual use, social influence, motivational experiences, and supportive learning environments and efficiency. These findings offer valuable insights for educators, curriculum developers, and educational institutions aiming to promote the effective integration of GenAI into English learning.