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Article In: AILA Review: Online-First Articles

Generative artificial intelligence and foreign language learning

L2 teachers’ perceptions of utility and ethics

 | University of South Florida
 | University of South Florida
 | University of South Florida
 | University of South Florida
This content is being prepared for publication; it may be subject to changes.
Abstract
Prior studies exploring teachers’ perceptions of generative artificial intelligence (GenAI) tools such as ChatGPT, Copilot, and Gemini have signaled tensions between instructors’ perceptions of GenAI’s usefulness and their beliefs regarding its ethicality. The current study furthers this line of inquiry, examining issues of ethics and utility by focusing specifically on teachers of languages other than English. Using a sequential mixed-methods design, this study employed a survey to understand language instructors’ (N = 101) perceptions of the ethicality of GenAI tool use in higher education, along with their perceptions of the usefulness of GenAI for supporting second language (L2) learning. Semi-structured interviews were then conducted with six teachers to further understand participants’ survey responses, with some teachers sharing additional artifacts (e.g., course policies regarding GenAI). The findings suggest that most teachers (92.1%) believe GenAI tools are ethical if used for specific purposes. There also appears to be a connection between teachers’ ethical beliefs and their perceptions of GenAI’s utility, in terms of whether GenAI is used by students as a scaffold/support mechanism versus being used to produce content. The implications of this study provide a roadmap for developing discipline-specific guidelines that preserve L2 learning integrity while leveraging GenAI’s utility.
Article outline
  • 1.Introduction
  • 2.Literature review
    • 2.1Language teachers’ perceptions of GenAI tools
    • 2.2Ethical issues involving GenAI Tools in L2 education
    • 2.3The current study
  • 3.Methods
    • 3.1Instruments and data
      • 3.1.1Survey
      • 3.1.2Interviews and artifacts
    • 3.2Participants
    • 3.3Data analyses
  • 4.Findings
    • 4.1RQ1: Teachers’ beliefs on the ethicality of GenAI tools
    • 4.2RQ2: Teachers’ beliefs of the utility of GenAI for L2 learning
  • 5.Discussion
  • 6.Conclusion
  • Note
  • References
References (24)
References
Alharbi, W. (2024). Mind the gap, please! Addressing the mismatch between teacher awareness and student AI adoption in language education within higher education. International Journal of Computer-Assisted Language Learning and Teaching, 14(1), 1–28. Google Scholar logo with link to Google Scholar
Braun, V., & Clarke, V. (2013). Successful qualitative research: A practical guide for beginners. Sage.Google Scholar logo with link to Google Scholar
Casal, J. E., & Kessler, M. (2023). Can linguists distinguish between ChatGPT/AI and human writing?: A study of research ethics and academic publishing. Research Methods in Applied Linguistics, 2(3), 100068. Google Scholar logo with link to Google Scholar
Dakakni, D., & Safa, N. (2023). Artificial intelligence in the L2 classroom: Implications and challenges on ethics and equity in higher education: A 21st century Pandora’s box. Computers and Education: Artificial Intelligence, 5, 100179. Google Scholar logo with link to Google Scholar
Davis, F. D., & Granić, A. (2024). The technology acceptance model: 30 years of TAM. Springer. Google Scholar logo with link to Google Scholar
De Costa, P. I., Rabie-Ahmed, A., & Cinaglia, C. (Eds.). (2024). Ethical issues in applied linguistics scholarship. John Benjamins. Google Scholar logo with link to Google Scholar
Duff, P. (2008). Case study research in applied linguistics. Routledge.Google Scholar logo with link to Google Scholar
Gao, Y., Wang, Q., Wang, X. (2024). Exploring EFL university teachers’ beliefs in integrating ChatGPT and other large language models in language education: A study in China. Asia Pacific Journal of Education, 44(1), 29–44. Google Scholar logo with link to Google Scholar
Goulart, L., Matte, M. L., Mendoza, A., Alvarado, L., & Veloso, I. (2024). AI or student writing? Analyzing the situational and linguistic characteristics of undergraduate student writing and AI-generated assignments. Journal of Second Language Writing, 66, 101160. Google Scholar logo with link to Google Scholar
Kessler, M., Rostrán Valle, J. M., Çekmegeli, K., & Farrell, S. (2025). Generative AI for learning languages other than English: L2 writers’ current uses and perceptions of ethics. Foreign Language Annals. Google Scholar logo with link to Google Scholar
Kitchener, K. S. (2000). Foundations of ethical practice, research, and teaching psychology. Lawrence Erlbaum.Google Scholar logo with link to Google Scholar
Kohnke, L. (2024). Exploring EAP students’ perceptions of GenAI and traditional grammar-checking tools for language learning. Computers and Education: Artificial Intelligence, 7 100279. Google Scholar logo with link to Google Scholar
Kong, S. C., Yang, Y., & Hou, C. (2024). Examining teachers’ behavioural intention of using generative artificial intelligence tools for teaching and learning based on the extended technology acceptance model. Computers and Education: Artificial Intelligence, 7, 100328. Google Scholar logo with link to Google Scholar
Larsson, T., Plonsky, L., Sterling, S., Kytö, M., Yaw, K., & Wood, M. (2023). On the frequency, prevalence, and perceived severity of questionable research practices. Research Methods in Applied Linguistics, 2(3), 100064. Google Scholar logo with link to Google Scholar
Law, L. (2024). Application of generative artificial intelligence (GenAI) in language teaching and learning: A scoping literature review. Computers and Education Open, 6, 100174. Google Scholar logo with link to Google Scholar
Ma, Y. (2025). Modelling college students’ acceptance to use generative artificial intelligence for second language learning: A theory of planned behaviour perspective. European Journal of Education: Research, Development and Policy, 60(1), e12923. Google Scholar logo with link to Google Scholar
Moorhouse, B. L., & Kohnke, L. (2024). The effects of generative AI on initial language teacher education: The perceptions of teacher educators. System, 122, 103290. Google Scholar logo with link to Google Scholar
Moorhouse, B. L., Wan, Y., Ho, T. Y., & Lin, A. M. Y. (2024). Generative AI-assisted, evidence-informed use of L1 in L2 classrooms. ELT Journal, 78(4), 453–465. Google Scholar logo with link to Google Scholar
Muppalla, S., Vuppalapati, S., & Reddy Pulliahgaru, A. (2023). Effects of excessive screen time on child development: An updated review and strategies for management. Cureus, 15(6), e40608. Google Scholar logo with link to Google Scholar
Szabó, F., & Szoke, J. (2024). How does generative AI promote autonomy and inclusivity in language teaching? ELT Journal, 78(4), 478–488. Google Scholar logo with link to Google Scholar
Ulla, M. B., Advincula, M. J. C., Mombay, C. D. S., Mercullo, H. M. A., Nacionales, J. P., & Entino-Señorita, A. D. (2024). How can GenAI foster an inclusive language classroom? A critical language pedagogy perspective from Philippine university teachers. Computers and Education: Artificial Intelligence, 7, 100314. Google Scholar logo with link to Google Scholar
Xu, W. & Tan, X. (2024). Beyond words: L2 writing teachers’ visual conceptualizations of Chat GPT in teaching and learning. Journal of Second Language Writing, 64, 101110. Google Scholar logo with link to Google Scholar
Yaw, K., Plonsky, L., Larsson, T., Sterling, S., & Kytö, M. (2023). Research timeline: Research ethics in applied linguistics. Language Teaching, 56(4), 478–494. Google Scholar logo with link to Google Scholar
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