Nursing Students’ Acceptance of AI-Based Language Learning Tools in ESP Learning: A Technology Acceptance Model (TAM) Approach
Abstract
The urgency of this study lies in the increasing demand for English proficiency among nursing students in response to the globalization of healthcare services. This study aims to analyze nursing students’ acceptance of AI-based language learning tools using the Technology Acceptance Model (TAM). The research employed a quantitative approach with a descriptive and explanatory design. Data were collected through a Likert-scale questionnaire distributed to 180 nursing students and analyzed using validity, reliability, and multiple linear regression tests. The results indicate that 7 out of 8 questionnaire items are valid and reliable, with a Cronbach’s Alpha value of 0.715, showing good internal consistency. Furthermore, the regression analysis reveals that the independent variables, namely perceived usefulness and intention to use, significantly influence the dependent variable, namely students’ acceptance of AI-based learning tools (p-value < 0.05). These findings suggest that the higher the perceived benefits and the stronger the intention to use the technology, the higher the level of acceptance among students. This study implies that successful implementation of AI in ESP learning for nursing students depends on enhancing perceived usefulness and encouraging continuous usage through relevant content, training, and institutional support.
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References
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DOI: https://doi.org/10.31004/jele.v11i3.2568
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