Technostress and English Language Learning in the Age of Generative AI
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| Title: | Technostress and English Language Learning in the Age of Generative AI |
|---|---|
| Language: | English |
| Authors: | Gilbert Dizon (ORCID |
| Source: | The EUROCALL Review. 2025 32(2):88-101. |
| Availability: | European Association for Computer-Assisted Language Learning (EUROCALL). EUROCALL Headquarters, School of Modern Languages, University of Ulster, Cromore Road, Coleraine BT52 1SA, Northern Ireland, UK. Tel: +34-67-943-1283; Web site: http://www.eurocall-languages.org/ |
| Peer Reviewed: | Y |
| Page Count: | 14 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research Tests/Questionnaires |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Artificial Intelligence, Stress Variables, Second Language Learning, English (Second Language), Foreign Countries, Student Experience, College Students, Language Proficiency, Stress Management, Universities, Student Attitudes, Technology Uses in Education, College Role |
| Geographic Terms: | Japan |
| ISSN: | 1695-2618 |
| 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. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1494471 |
| Database: | ERIC |
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