Personality Traits and the Intention to Use Artificial Intelligence Tools in English Language Learning: A Mixed-Methods Extension of the UTAUT Framework
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Abstract
Current understanding of AI use by undergraduate English as a Foreign Language (EFL) students is limited. The role of personality in their acceptance of AI also remains underexplored. Therefore, the purpose of the current study is to investigate EFL students’ use of AI outside of the classroom, the factors behind their AI use, and the impact of personality traits on their patterns of use. We adapt and extend the Unified Theory of Acceptance and Use of Technology (UTAUT) in an explanatory sequential research model to examine these areas. We collected survey data from 238 undergraduates enrolled in English classes at a Thai university. The data were analyzed with partial least squares structural equation modeling (PLS-SEM). We also conducted focus group interviews with 29 survey respondents. A hybrid deductive–inductive thematic process was used to extract themes from the focus group data. Survey results highlight almost universal use of AI among our sample, with Performance Expectancy being the strongest predictor of EFL students’ intention to use AI. Social Influence also plays a significant role, although the influence of personality traits is limited. Focus group findings confirm the normalization of students’ AI use outside of the classroom, largely due to perceived efficiency gains. In addition, students frequently reported using simple risk management strategies. Based on our findings, we discuss implications for EFL teachers and the UTAUT framework. Specifically, we point to the potential redundancy of certain core UTAUT constructs and suggest model extensions that capture the influence of social media.
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