Generative AI Empowering Chinese Language Teaching in Vietnam: Current Applications, Empirical Investigations, and Practical Pathways

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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Publication Details

Journal
International Journal of Current Science Research and Review
Published
2026-08-27
DOI
https://doi.org/10.5281/zenodo.22125846
Primary Topic
Technology-Enhanced Education Studies
Type
article
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article

Generative AI Empowering Chinese Language Teaching in Vietnam: Current Applications, Empirical Investigations, and Practical Pathways

Phuong Do Minh
International Journal of Current Science Research and Review
Technology-Enhanced Education Studies
article

Generative AI Empowering Chinese Language Teaching in Vietnam: Current Applications, Empirical Investigations, and Practical Pathways

Phuong Do Minh
article en

Abstract

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.

International Journal of Current Science Research and Review
Trường ĐH Nguyễn Tất Thành (VN)
Quality Education
Openalex Percentile: Top 2%
Technology-Enhanced Education Studies
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