Abstract :

The iterative upgrading of generative artificial intelligence (AI) has profoundly reshaped the pedagogical forms and developmental models of international Chinese language education. As a core country for Chinese learning in Southeast Asia, Vietnam witnesses robust and growing demands for Chinese language education, yet it has long confronted structural dilemmas including insufficient teacher supply, inadequate localized teaching resources, and difficulties in implementing personalized instruction. To explore the adaptability and practical value of AI technology in Vietnamese Chinese teaching, this study adopts a mixed‑method research design. Based on questionnaires, semi‑structured interviews, and an eight‑week classroom action research involving 221 teachers and learners from universities, primary and secondary schools, and training institutions in Hanoi and Ho Chi Minh City, this paper systematically examines the application scenarios, practical effects, and localized challenges of generative AI in local Chinese pedagogy. The results indicate that generative AI functions as an effective digital pedagogical scaffold, alleviating shortages of teaching resources and professional teachers, reducing learners’ foreign language anxiety, and improving the efficiency of basic linguistic training. Nevertheless, current applications are constrained by insufficient Vietnamese‑Chinese bilingual corpus adaptation, inadequate teachers’ AI pedagogical literacy, learners’ technological dependence, and prominent regional digital divides. Grounded on the Technology Acceptance Model (TAM) and sociocultural constructivist theory, this study constructs a teacher‑led and AI‑assisted collaborative teaching paradigm and proposes targeted optimization pathways from four dimensions: localized resource development, teacher competency cultivation, classroom procedure reconstruction, and learner media literacy enhancement. This research fills the empirical research gap regarding intelligent Chinese language education in Vietnam and provides practical implications for the digital transformation of Chinese language education in ASEAN countries.

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Keywords :

Chinese language teaching in vietnam, Generative artificial intelligence, International Chinese language education, Second Language Acquisition, teacher AI collaboration.

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References :

1. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319‑340.
2. Chen, P., & Zhang, B. (2024). Action research on generative artificial intelligence‑supported international Chinese writing teaching. Applied Linguistics, 2, 103‑113.
3. Gu, X. (2025). Analysis of the digital divide in Southeast Asian Chinese language education. International Communications, 2, 67‑70.
4. Liu, S. (2025). Practical dilemmas and optimization paths of generative AI empowering overseas Chinese teaching. Research in International Chinese Language Teaching, 1, 56‑63.
5. Lu, Y., Yu, J., & Chen, P. (2023). Educational applications and prospects of generative artificial intelligence: Taking ChatGPT as an example. China Distance Education, 43(4), 24‑31, 51.
6. Pham, T. Q. (2021). Investigation and research on Chinese teaching in Vietnamese universities. Journal of Chinese Language Teaching and Research, 4, 78‑85.
7. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
8. Wang, H. (2022). Development status, challenges and paths of Chinese language education in ASEAN. International Chinese Language Education, 2, 34‑43.
9. Wu, M. (2024). Current situation and reflections on the digital transformation of Chinese language education in Vietnam. Crossroads of Southeast Asian Studies, 3, 112‑120.
10. Wu, Y. (2010). A review of research on Chinese acquisition by Vietnamese learners. Journal of Yunnan Normal University (Teaching and Research Edition of Chinese as a Foreign Language), 8(3), 45‑51.
11. Zhang, J. (2024). Teacher‑AI collaboration: A new paradigm for international Chinese language education. Chinese Language Learning, 4, 87‑96.
12. Zhang, W., & Li, H. (2024). Opportunities, risks and countermeasures of generative artificial intelligence in international Chinese language education. Language Teaching and Linguistic Studies, 2, 1‑12.
13. Zhao, Y. (2023). Implications of large language models for second language teaching. World Chinese Language Teaching, 37(3), 289‑298.
14. World Chinese Conference Secretariat. (2024). World Chinese Conference report (2024). Center for Language Education and Cooperation, Ministry of Education of China.