Exploring Chinese college EFL learners' AI technology acceptance driven by computer self-efficacy

Computer self-efficacy plays a crucial role in users' AI usage, but the research on this aspect is inadequate in quantitative terms. This study, grounded in an extended version of Technology Acceptance Model (TAM), aims to explore college English as a Foreign Language (EFL) learners' acceptance of AI technologies driven by computer self-efficacy. Data were gathered via an online questionnaire from 776 Chinese EFL learners who were then studying at Chinese universities. The results, obtained through structural equation modeling (SEM), indicate that computer self-efficacy could positively influence the learners' behavioral intention to use AI. Moreover, perceived ease of use, perceived usefulness, and attitude mediated the relationship between computer self-efficacy and behavioral intention. These findings provide useful insights into promoting more effective application of AI technologies among Chinese college EFL learners.