Integrating Artificial Intelligence in Higher Education Language Teaching: Insights from Academic Discourse
DOI:
https://doi.org/10.48161/qaj.v6n2a2527Keywords:
Artificial intelligence, Higher education, Language teaching, Academic discourse, Qualitative research, Educational technologyAbstract
This study aims to examine the integration of artificial intelligence (AI) in foreign language education within the broader context of digital transformation in higher education. Adopting a qualitative research design, the study employs inductive thematic analysis to explore insights obtained from academic round table presentations and panel discussions involving educators and experts from higher education institutions. The data consist of contributions from four round table presenters and six panel participants, through which prevailing pedagogical trends, opportunities, and challenges related to the implementation of AI in language teaching were identified. The findings indicate that artificial intelligence is widely perceived as a transformative pedagogical tool in foreign language education, supporting personalized learning, enhancing student engagement, and facilitating the development of language skills through adaptive and interactive technologies. Participants highlighted the evolving role of teachers, who increasingly act as facilitators and designers of learning experiences. In this context, AI integration was considered effective when it promotes higher-order thinking, learner autonomy, and collaboration. At the same time, concerns were raised regarding potential overreliance on AI, issues of academic integrity, and the growing need to develop students’ critical digital literacy. Furthermore, the study emphasizes the importance of aligning AI use with established pedagogical frameworks that prioritize knowledge construction and authentic learning. Importantly, it proposes an integrated perspective that connects AI-supported pedagogy with constructivist learning theory and ICT-based frameworks such as 21st Century Learning Design (21CLD), highlighting how AI can support knowledge construction in language education. Overall, the study offers discourse-based, context-specific insights and provides practical implications for educators and policymakers seeking to implement responsible and human-centered approaches to language teaching in higher education.
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References
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education—Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39.
Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020). Application and theory gaps during the rise of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100002.
Almulla, B. (2025). Harnessing artificial intelligence to advance art education goals: A study from Kuwait. Qubahan Academic Journal, 5(4), 332–348.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
Kukulska-Hulme, A. (2020). Mobile-assisted language learning. In C. A. Chapelle (Ed.), The concise encyclopedia of applied linguistics. Wiley.
Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239.
Aliyeva, G. B., Saktaganov, B., Meljnyk, K., Stepanets, N., & Vasiuta, V. (2026). Analysis of the evolution of artificial intelligence as a key tool in digital education. Periodicals of Engineering and Natural Sciences, 14(1), 123–140.
Ahmadova, G., & Oksanen, L. (2026). The role of artificial intelligence in shaping communication culture in the teaching process: Transforming educational interactions. Linguiverse, 2(1), 27–33.
Chapelle, C. A. (2003). English language learning and technology. John Benjamins.
Li, S., & Jiang, X. (2020). Artificial intelligence in language learning: Applications and implications. Computer Assisted Language Learning, 33(7), 1–23.
Fryer, L. K., & Carpenter, R. (2006). Bots as language learning tools. Language Learning & Technology, 10(3), 8–14.
Godwin-Jones, R. (2022). Partnering with AI: Intelligent writing assistance and instructed language learning. Language Learning & Technology, 26(2), 5–24.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. RELC Journal, 54(2), 537–550.
Warschauer, M., & Healey, D. (1998). Computers and language learning: An overview. Language Teaching, 31(2), 57–71.
Bax, S. (2011). Normalisation revisited: The effective use of technology in language education. International Journal of Computer-Assisted Language Learning and Teaching, 1(2), 1–15.
Microsoft. (2012). 21CLD learning design rubrics. Microsoft Partners in Learning.
Fullan, M., & Langworthy, M. (2014). A rich seam: How new pedagogies find deep learning. Pearson.
Puentedura, R. R. (2014). SAMR and TPCK: Models for educational transformation. Hippasus.
Dede, C. (2014). The role of digital technologies in deeper learning. In Students at the center: Deeper learning research series. Jobs for the Future.
Denzin, N. K., & Lincoln, Y. S. (Eds.). (2018). The SAGE handbook of qualitative research (5th ed.). SAGE.
Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). SAGE.
Morgan, D. L. (1997). Focus groups as qualitative research (2nd ed.). SAGE.
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic analysis: Striving to meet the trustworthiness criteria. International Journal of Qualitative Methods, 16(1), 1–13.
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. SAGE.
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