FACTORS INFLUENCING INTENTION TO USE ARTIFICIAL INTELLIGENCE IN LEARNING LISTENING AND SPEAKING SKILLS: A STUDY OF CHINESE STUDIES STUDENTS AT THAI NGUYEN UNIVERSITY OF SCIENCES

نویسندگان

  • Mai Thi Ngoc Anh Thai Nguyen University of Sciences, Vietnam
  • Trieu Van Toan Thai Nguyen University of Sciences, Vietnam

DOI:

https://doi.org/10.46827/ejfl.v9i3.6095

کلمات کلیدی:

artificial intelligence, intention, listening skill, speaking skill, Chinese Studies

چکیده

This study examined the determinants of Chinese Studies students' intention to use artificial intelligence (AI) to learn listening and speaking skills at Thai Nguyen University of Sciences. Using the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT2), the study determined five primary factors: perceived usefulness, perceived ease of use, hedonic motivation, social influence, and trust. A quantitative study design was adopted, using survey data from 200 Chinese Studies major students. The results of multiple regression analysis indicated that all five variables significantly impact students' intent to use AI tools for learning listening and speaking skills. The implications are meaningful for instructors, developers, and policymakers who want to improve the effective application of AI in language learning. Future lines of inquiry were also outlined in the study, such as expanding the sample size and using mixed methods for enhancing the understanding of AI uptake in language learning.

 

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مراجع

Al-Abdullatif, A. M. (2024). Modeling teachers’ acceptance of generative artificial intelligence use in higher education: The role of AI literacy, intelligent TPACK, and perceived trust. Education Sciences, 14(11), 1209. https://doi.org/10.3390/e

ducsci14111209

Al-Azawei, A., & Alowayr, A. (2020). Predicting the intention to use and hedonic motivation for mobile learning: A comparative study in two Middle Eastern countries. Technology in Society, 62, 101325. https://doi.org/10.1016/j.tech

soc.2020.101325

Bahadur, S.G.C., Bhandari, P., Gurung, S.K., Srivastava, E., Ojha, D., & Dhungana, B. R. (2024). Examining the role of social influence, learning value and habit on students’ intention to use ChatGPT: the moderating effect of information accuracy in the UTAUT2 model. Cogent Education, 11(1), 2403287. https://doi.org/10.1080/2331186X.2024.2403287

Cai, S., Wang, X., & Zou, D. (2023). Generative AI-based speaking practice and learner engagement in higher education. Computers & Education: Artificial Intelligence, 4, 100147. https://doi.org/10.1016/j.caeai.2023.100147

Chai, C. S., Chiu, T. K. F., Wang, X., Jiang, F., & Lin, X.-F. (2023). Modeling Chinese Secondary School Students’ Behavioral Intentions to Learn Artificial Intelligence with the Theory of Planned Behavior and Self-Determination Theory. Sustainability, 15(1), 605. https://doi.org/10.3390/su15010605

Choung, H., David, P., & Ross, A. (2022). Trust in AI and its role in the acceptance of AI technologies. International Journal of Human–Computer Interaction, 39(9), 1727–1739. https://doi.org/10.1080/10447318.2022.2050543.

Chung, D. T., Thanh, N. C. M., Thu, N. V. A., Trinh, H. D., & Trinh, V. T. T. (2024). Factors affecting the behavior of using AI tools in learning of university students in Ho Chi Minh City. Journal of Financial-Marketing Research, 15(6), 112-125.

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

Godwin-Jones, R. (2023). Emerging spaces for language learning: AI bots, ambient intelligence, and the metaverse. Language Learning & Technology, 27(2), 6–27. https://hdl.handle.net/10125/73501

Huang, F., & Zou, B. (2024). English speaking with artificial intelligence (AI): The roles of enjoyment, willingness to communicate with AI, and innovativeness. Computers in Human Behavior, 159, Article 108355. https://doi.org/10.1016/j.chb.2024.108355

Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. RELC Journal, 54(2), 537–550. https://doi.org/10.1177/0033

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478. https://doi.org/10.2307/30036540

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412

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چاپ شده

2025-06-26

شماره

نوع مقاله

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