Who is most likely to accept AI chatbots? A sequential explanatory mixed-methods study of personality and ChatGPT acceptance for language learning

This study examines the role of personality traits in university students' acceptance of ChatGPT for language learning, using a sequential explanatory mixed-methods approach. Structural equation modelling based on responses from 233 students in China showed that perceived ease of use significantly predicted perceived usefulness, which in turn influenced attitude and behavioural intention. Among the Big Five traits, conscientiousness positively predicted both perceived usefulness and ease of use; openness and agreeableness positively influenced perceived usefulness; while extraversion and neuroticism significantly affected perceived ease of use in positive and negative directions respectively. The qualitative phase, based on interviews with 15 students, explored how and why these personality traits shaped learners' perceptions and behaviours. Thematic analysis identified key mechanisms such as goal-directed routines (conscientiousness), exploratory curiosity (openness), emotional reassurance (agreeableness), and uncertainty sensitivity (neuroticism). These findings highlight the importance of considering personality in the design and implementation of AI-assisted language learning.