Navigating Generative AI in English Language Education: Competencies of Novice and Experienced Vietnamese EFL Teachers
Keywords:
generative artificial intelligence; GenAI competencies; Vietnamese EFL teachers; English language education; teacher professional developmentAbstract
This study has investigated the generative artificial intelligence (GenAI) competencies of Vietnamese in-service EFL teachers across different teaching experience levels. Employing an explanatory sequential mixed-methods design, the study collected quantitative data from 581 novice and experienced EFL teachers using the Teachers’ Generative AI Competencies (T-GAIC) instrument and qualitative data from semi-structured interviews with 14 participants. Quantitative data were analysed using descriptive statistics and independent-sample t-tests, while qualitative data were examined through thematic analysis. The findings indicated that both novice and experienced teachers perceived themselves as having relatively high levels of GenAI competencies, despite the rapid emergence of AI technologies in Vietnamese higher education. Independent-sample t-tests revealed statistically significant but small differences in technological proficiency, with novice teachers reporting higher levels than experienced teachers (t = 3.29, p <.05, d =.27), and in risk and ethical awareness, with experienced teachers reporting higher levels than novice teachers (t = ?3.48, p <.05, d =.30). No significant differences were found in pedagogical compatibility, preparing students for effective GenAI use, or professional development and communication. Overall, the limited magnitude of the group differences suggested that GenAI competencies might extend beyond technological familiarity or teaching experience alone. More importantly, the qualitative findings revealed that teachers’ GenAI competencies were negotiated through institutional ambiguity, professional identity concerns, informal learning networks, and the hidden evaluative labour associated with AI-generated content. The study refines current understandings of teachers’ AI competencies by highlighting their multidimensional, socially situated, and context-dependent nature in AI-mediated language education.
https://doi.org/10.26803/ijlter.25.8.13
References
Al-Khresheh, M. H. (2024). Bridging technology and pedagogy from a global lens: Teachers’ perspectives on integrating ChatGPT in English language teaching. Computers and Education: Artificial Intelligence, 6, 100218. https://doi.org/10.1016/j.caeai.2024.100218
Adiyono, A., Suwartono, T., Nurhayati, S., Dalimarta, F. F., & Wijayanti, O. (2025). Impact of artificial intelligence on student reliance for exam answers: A case study in IRCT Indonesia. International Journal of Learning, Teaching and Educational Research, 24(3), 455–479. https://doi.org/10.26803/ijlter.24.3.22
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Creswell, J. W., & Creswell, J. D. (2023). Research design: Qualitative, quantitative, and mixed methods approach (6th ed.). Sage.
Chiu, T., Ahmad, Z., & Çoban, M. (2024). Development and validation of teacher artificial intelligence (AI) competence self-efficacy (TAICS) scale. Education and Information Technologies, 29, 1–19. https://doi.org/10.1007/s10639-024-13094-z
Cong-Lem, N., Nguyen, T. T., Nguyen, K. N. H., & Nguyen, Q. N. H. (2026). Critical thinking in Vietnamese EFL students’ use of generative AI tools for academic learning: Qualitative insights from a brief intervention. English Teaching & Learning. https://doi.org/10.1007/s42321-025-00217-z
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Dai, K., Liu, Y., & Zhang, X. (2026). Generative AI in higher education: A bibliometric review of emerging trends, power dynamics, and global research landscapes. Computers and Education: Artificial Intelligence, 10, 100544. https://doi.org/10.1016/j.caeai.2026.100544
European Commission. (2022). Ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for educators. Publications Office of the European Union. https://education.ec.europa.eu/focus-topics/digital-education/actions/plan/ethical-guidelines-for-educators-on-using-artificial-intelligence
Floris, F. (2025). Exploring shared repertoire in virtual communities of practice: Integration of artificial intelligence in English language teaching. The JALT CALL Journal, 21(2). https://doi.org/10.29140/jaltcall.v21n2.102420
Grani?, A. (2022). Educational technology adoption: A systematic review. Education and Information Technologies, 27, 9725–9744. https://doi.org/10.1007/s10639-022-10951-7
Hoang, V. H., & Bui, M. H. (2026). Exploring AI-aided language assessment: Perspectives from EFL teachers. Journal of Foreign Language Studies, 85. https://doi.org/10.56844/tckhnn.85.1001
Holmes, W., & Porayska-Pomsta, K. (2023). The ethics of artificial intelligence in education. Routledge.
Jin, F., Peng, X., Sun, L., Song, Z., Zhou, K., & Lin, C.-H. (2025). Knowledge (co-) construction among artificial intelligence, novice teachers, and experienced teachers in an online professional learning community. Journal of Computer Assisted Learning, 41, Article e70004. https://doi.org/10.1111/jcal.70004
Jose, B., Cleetus, A., Joseph, B., Joseph, L., Jose, B., & John, A. K. (2025). Epistemic authority and generative AI in learning spaces: Rethinking knowledge in the algorithmic age. Frontiers in Education, 10, Article 1647687. https://doi.org/10.3389/feduc.2025.1647687
Koehler, M. J., & Mishra, P. (2009). What is technological pedagogical content knowledge? Contemporary Issues in Technology and Teacher Education, 9(1), 60–70. https://citejournal.org/volume-9/issue-1-09/general/what-is-technological-pedagogicalcontent-knowledge/
Kangwa, D., Msafiri, M. M., & Fute, A. (2025). Exploring the factors that promote a balance between academic integrity and the effective use of GenAI tools in higher education: A systematic review. Journal of Computer Assisted Learning, 41(5). https://doi.org/10.1111/jcal.70109
Lee, G., & Zhai, X. (2024). Using ChatGPT for science learning: A study on pre-service teachers’ lesson planning. IEEE Transactions on Learning Technologies, 1–14. https://doi.org/10.1109/TLT.2024.3401457
Lorenz, U., & Romeike, R. (2023). What is AI-PACK? Outline of AI competencies for teaching with DPACK. In International Conference on Informatics in Schools: Situation, Evolution, and Perspectives (pp. 15–28). Springer. https://doi.org/10.1007/978-3-031-44900-0_2
Moorhouse, B. L., & Wong, K. M. (2025). Generative artificial intelligence and language teaching. Cambridge University Press. https://doi.org/10.1017/9781009618823
Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W., & Chu, S. K. W. (2023). Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world. Educational Technology Research and Development, 71(1), 137–161. https://doi.org/10.1007/s11423-023-10203-6
Nguyen, P. T., & Nguyen, L. T. M. (2025). Emerging technology adoption and student learning in higher education. In Sustainable finance (pp. 399–411). https://doi.org/10.1007/978-3-032-03943-9_16
Pahi, K., Hawlader, S., Hicks, E., Zaman, A., & Phan, V. (2024). Enhancing active learning through collaboration between human teachers and generative AI. Computers and Education Open, 6, 100183. https://doi.org/10.1016/j.caeo.2024.100183
Qian, Y. (2025). Pedagogical applications of generative AI in higher education: A systematic review of the field. TechTrends, 69, 1105–1120. https://doi.org/10.1007/s11528-025-01100-1
Su, J., & Yang, W. (2023). Unlocking the power of ChatGPT: A framework for applying generative AI in education. ECNU Review of Education, 6(3), 355–366. https://doi.org/10.1177/20965311231168423
Shi, L. (2025). Assessing teachers’ generative artificial intelligence competencies: Instrument development and validation. Education and Information Technologies, 30, 23365–23384. https://doi.org/10.1007/s10639-025-13684-5
Taber, K. S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
UNESCO. (2022). AI competency framework for teachers. UNESCO Publishing. https://unesdoc.unesco.org/ark:/48223/pf0000391104
UNESCO. (2025). UNESCO survey: Two-thirds of higher education institutions have or are developing guidance on AI use. https://www.unesco.org/en/articles/unesco-survey-two-thirds-higher-education-institutions-have-or-are-developing-guidance-ai-use
Van den Berg, G., & Du Plessis, E. D. (2023). ChatGPT and generative AI: Possibilities for its contribution to lesson planning, critical thinking and openness in teacher education. Education Sciences, 13(10), Article 998. https://doi.org/10.3390/educsci13100998
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Nhung Thuy Thi Le
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All articles published by IJLTER are licensed under a Creative Commons Attribution Non-Commercial No-Derivatives 4.0 International License (CCBY-NC-ND4.0).
