Understanding the Adoption of Generative Artificial Intelligence in English Language Teaching: A UTAUT2 Perspective in Turkish Higher Education
DOI:
https://doi.org/10.59045/nalans.2026.92Keywords:
Generative artificial intelligence (GenAI), UTAUT2, technology acceptance, English language teaching (ELT), higher educationAbstract
This study examined whether the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) could predict English language instructors’ acceptance and use of generative artificial intelligence (GenAI) technologies in Turkish higher education. An explanatory sequential mixed-methods design was employed. Quantitative data were collected from 80 instructors through a structured questionnaire and analyzed using multiple regression, followed by qualitative data from semi-structured interviews and classroom observations. The findings showed that none of the UTAUT2 constructs significantly predicted behavioral intention or actual usage behavior. Although performance expectancy and hedonic motivation showed relatively high descriptive values, they did not reach statistical significance, with hedonic motivation only approaching significance. These results suggest that UTAUT2 demonstrated limited explanatory adequacy for GenAI adoption in this sample and context. Qualitative findings indicated that instructors recognized benefits such as time savings and enhanced student engagement but also expressed concerns about academic integrity, the reliability of AI-generated content, and possible negative effects on critical thinking and language learning. Institutional support, professional identity, and pedagogical beliefs also shaped adoption decisions. Overall, GenAI adoption appears to be a complex, multidimensional process that may require broader explanatory frameworks incorporating trust, perceived risk, and pedagogical considerations. Quantitative findings should, however, be interpreted cautiously given the sample size and model complexity.
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