THE USE OF CHATGPT IN VIETNAMESE LITERATURE TEACHING: TEACHERS’  READINESS, TASK-BASED ADOPTION, AND PERCEIVED RISK IN DA NANG

Le Thi Thanh Tinh; Nguyen Thi Nguyen Giang; Vo Phuong Uyen

Le Thi Thanh Tinh*	ltttinh@ued.udn.vn	University of Science and Education - The University of Danang 459 Ton Duc Thang street, Hoa Khanh ward, Da Nang City, Vietnam.
Vo Phuong Uyen	puyen24022003@gmail.com	University of Science and Education - The University of Danang 459 Ton Duc Thang street, Hoa Khanh ward, Da Nang City, Vietnam.
Nguyen Thi Nguyen Giang	nggiangnt912@gmail.com	Nguyen Van Thoai High school 132 Do Doc Lan road, Hoa Xuan ward, Da Nang, Vietnam

Summary:

The rapid development of generative artificial intelligence, particularly ChatGPT, is creating both opportunities and challenges for Vietnamese Literature teaching. However, empirical evidence remains limited regarding the relationships among teachers’ readiness, task based adoption, and perceived risk in this subject at the upper secondary level. Using a cross-sectional design, this study surveyed 269 upper secondary Literature teachers in Da Nang and tested a three-construct model (R–TA–PR) through path analysis with 5,000-iteration percentile bootstrap. Teachers reported a high level of readiness but only moderate task-based adoption; ChatGPT was used mainly for searching materials and lesson preparation, while its use in core pedagogical tasks remained low. Perceived risk was high, concentrating on academic dishonesty and student dependence. Readiness strongly predicted task-based adoption and had a direct inverse association with perceived risk; however, task based adoption did not significantly predict perceived risk and did not mediate the relationship between readiness and perceived risk. These findings suggest that increasing the frequency of ChatGPT use does not automatically change teachers’ risk perception.

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Keywords:

ChatGPT

generative AI

Vietnamese Literature teaching

teachers' readiness

task-based adoption

perceived risk.

Refers:

[1] Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), pp.179–211. https://doi.org/10.1016/0749-5978(91)90020-T.

[2] Alfarwan, A. (2025). Generative AI use in K-12 education: A systematic review. Frontiers in Education, 10, 1647573. https://doi.org/10.3389/ feduc.2025.1647573.

[3] Alyoussef, I. Y. (2023). Acceptance of e-learning in higher education: The role of task-technology fit with the information systems success model. Heliyon, 9(3), Article e13751. https://doi. org/10.1016/j.heliyon.2023.e13751.

[4] Asadi, M., Ebadi, S. & Mohammadi, L. (2025). The impact of integrating ChatGPT with teachers’ feedback on EFL writing skills. Thinking Skills and Creativity, 56, p.101766. https://doi.org/10.1016/j. tsc.2025.101766.

[5] Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.

[6] Bender, E. M., Gebru, T., McMillan-Major, A. & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, pp.610–623. https://doi.org/10.1145/3442188.3445922.

[7] Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), pp.351–370. https:// doi.org/10.2307/3250921.

[8] Compeau, D. R. & Higgins, C. A. (1995). Computer self efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), pp.189–211. https://doi. org/10.2307/249688.

[9] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), pp.319–340. https://doi.org/10.2307/249008.

[10] Featherman, M. S. & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human Computer Studies, 59(4), pp.451–474. https://doi. org/10.1016/S1071-5819(03)00111-3.

[11] Goodhue, D. L. & Thompson, R. L. (1995). Task technology fit and individual performance. MIS Quarterly, 19(2), pp.213–236. https://doi. org/10.2307/249689.

[12] Holmes, W., Bialik, M. & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.

[13] Koehler, M. J. & Mishra, P. (2009). What is technological pedagogical content knowledge (TPACK)? Contemporary Issues in Technology and Teacher Education, 9(1), pp.60–70.

[14] Kohnke, L., Moorhouse, B. L. & Zou, D. (2023). Exploring generative preparedness artificial intelligence among university language instructors: A case study. Computers and Education: Artificial Intelligence, 5, Article 100156. https://doi. org/10.1016/j.caeai.2023.100156.

[15] Nguyễn Thị Hảo. (2022). Thiết kế kế hoạch bài dạy trong dạy học kết hợp trực tuyến và trực tiếp môn Ngữ văn cấp trung học cơ sở trên địa bàn quận Thanh Xuân, Thành phố Hà Nội. Tạp chí Khoa học Giáo dục Việt Nam, 18(11), tr.47–53. https://doi. org/10.15625/2615-8957/12211108.

[16] Nguyễn Thị Thanh Nga. (2022). Phát triển năng lực số cho học sinh trung học qua môn Ngữ văn. Tạp chí Khoa học Giáo dục Việt Nam, 18(11), tr.6–12. https:// doi.org/10.15625/2615-8957/12211102.

[17] Parasuraman, A. (2000). Technology readiness index (TRI): A multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), pp.307–320. https://doi. org/10.1177/109467050024001.

[18] Phạm Thị Giao Liên. (2025). Vận dụng mô hình lớp học đảo ngược trong dạy học đọc hiểu văn bản kịch lớp 11. Tạp chí Khoa học Giáo dục Việt Nam, 21(S3), tr.81–89.

[19] Phan Thị Gấm & Nguyễn Quốc Dũng. (2026). Nghiên cứu thực trạng và đề xuất giải pháp ứng dụng trí tuệ nhân tạo tạo sinh trong dạy học lập trình tại một số trường đại học. Tạp chí Khoa học Giáo dục Việt Nam, 22(1), tr.37–46. https://doi. org/10.15625/2615-8957/12610105.

[20] Prilop, C. N., Mah, D.-K., Jacobsen, L. J., Hansen, R. R., Weber, K. E. & Hoya, F. (2025). Generative AI in teacher education: Educators’ perceptions of transformative potentials and the triadic nature of AI literacy explored through AI enhanced methods. Computers and Education: Artificial Intelligence, 9, Article 100471. https://doi. org/10.1016/j.caeai.2025.100471.

[21] Redecker, C. (2017). European framework for the digital competence of educators: DigCompEdu (Y. Punie, Ed.; EUR 28775 EN). Publications Office of the European Union. https://doi.org/10.2760/159770.

[22] UNESCO. (2023). Guidance for generative AI in education and research. United Nations Educational, Scientific and Cultural Organization.

[23] 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), pp.425–478. https://doi.org/10.2307/30036540.

Journal:

No. 8, August 2026

VIETNAM JOURNAL OF EDUCATIONAL SCIENCES

THE VIETNAM NATIONAL INSTITUTE OF EDUCATIONAL SCIENCES

THE USE OF CHATGPT IN VIETNAMESE LITERATURE TEACHING: TEACHERS’ READINESS, TASK-BASED ADOPTION, AND PERCEIVED RISK IN DA NANG