Technostress and English Language Learning in the Age of Generative AI
Submitted: 05/01/2025
|Accepted: 11/06/2025
|Published: 12/26/2025
Copyright (c) 2025 Gilbert Dizon, Jason Gold, Ryan Barnes
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Keywords:
Generative Artificial Intelligence, intelligent CALL, technostress, Artificial Intelligenceliteracy
Supporting agencies:
Abstract:
The purpose of this study is to examine the effects of generative AI on technostress among second language (L2) English students at two Japanese universities. While the use of generative AI technologies in education is rapidly increasing, research on how these tools impact learners' psychological well-being—particularly in L2 learning contexts—remains limited. This study primarily aimed to explore students’ experiences of generative AI–related technostress. In addition, a secondary analysis examining whether technostress levels varied by students’ language proficiency was conducted, although no significant differences were observed. A total of 100 L2 English students, 60 beginner learners and 40 intermediate-advanced learners, fully completed the survey, which consisted of Likert-scale and open-ended written response items. While the quantitative results indicated that the participants did not exhibit high levels of technostress, the qualitative findings suggested a more nuanced picture of the impact of AI-related technostress on university L2 students. Namely, the students were concerned about the accuracy of AI output and thus desired explicit training and guidance. These results indicate that while generative AI may not cause significant levels of technostress, the emerging technology still presents specific challenges that must be addressed. The article concludes with practical suggestions for language teachers and institutions so that they can better support L2 students’ AI literacy and reduce the risks of technostress.
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