The progressive integration of technology into language-based professions has stoked concerns about job displacement. Nevertheless, empirical research exploring how technology acceptance interacts with job-related anxiety among English major students remains scarce. To bridge this research gap, this mixed-methods study delves into the survey data from 523 Chinese English majors. Utilizing latent profile analysis (LPA), it identifies diverse technology-acceptance profiles, and subsequently executes ANOVA and post-hoc analyses to examine how these profiles are linked to job anxiety. Three distinct profiles surfaced: the low-technology-acceptance profile (11.9%), the moderate-acceptance profile (67.5%), and the high-technology-acceptance profile (20.6%). ANOVA results revealed that the profiles varied significantly in terms of job anxiety: the low- acceptance group reported the most intense anxiety, while the high-acceptance group exhibited the least. The moderate-acceptance group displayed unique challenges, including heightened self-doubt despite maintaining a balanced perspective on technology. The qualitative analysis further illuminated these trends within a broader context. It uncovered the coexistence of an optimistic outlook on technology’s role in skill augmentation and concerns about job security. These research findings emphasize the need for integrating technology literacy into the curriculum and tailoring customised guidance to mitigate anxiety and boost students’ job adaptability. Moreover, this study may equipe educators with actionable strategies to prepare English majors for AI-dominated labour market.
Wang et al. (Mon,) studied this question.
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