Understanding learner motivation and intention to use ChatGPT for English language learning

Abstract

The Integrated Model of Technology Acceptance (IMTA), building upon the Technology Acceptance Model (TAM), focuses on how intrinsic motivation (perceived enjoyment) and extrinsic motivation (perceived usefulness) jointly influence users’ behavioural intention (BI) to adopt emerging technologies. Although IMTA has been widely applied in technology adoption research, its empirical validation in the context of language learners’ acceptance of generative artificial intelligence (e.g., ChatGPT) remains limited. This study investigates university English as a Foreign Language (EFL) students’ acceptance of ChatGPT for language learning purposes. Adopting a mixed-methods design, data were collected through an IMTA-based questionnaire (n = 347) and semi-structured interviews (n = 10). Quantitative data were analysed using structural equation modelling, revealing that students generally perceive ChatGPT as both easy to use and beneficial for language acquisition, with perceived enjoyment significantly predicting perceived usefulness, perceived ease of use and BI. Qualitative data were examined through thematic analysis, further corroborating these findings and highlighting students’ positive attitudes towards integrating ChatGPT into academic writing and speaking tasks. These results contribute to the growing body of research on motivation-driven technology acceptance and offer practical implications for designing generative AI-supported language learning instruction.

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