SSRScientific and Social Research2661-43322981-9946Bio-Byword Scientific Publishing Pty. Ltd.10.26689/ssr.v8i10.15937ArticleAcceptance of Artificial Intelligence-Assisted Chinese Learning Among International Students in China: A Study Based on the Unified Theory of Acceptance and Use of Technology (UTAUT)https://artdesignp.com/journal/SSR/8/10/10.26689/ssr.v8i10.15937ShaoBin,ZhouQin,ZhaoYazhu20268102026-11-03Based on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study investigates the acceptance of artificial intelligence-assisted Chinese learning among 310 international students in China and constructs a theoretical model that influences their behavioral intention to adopt such learning approaches. The theoretical model encompasses four core variables: performance expectancy, effort expectancy, social influence, and facilitating conditions. The results reveal that: (1) Performance expectancy and facilitating conditions exert a significantly positive effect on behavioral intention; (2) Effort expectancy has a negative impact on behavioral intention; (3) Social influence shows no significant effect. The findings provide valuable implications for teachers and developers of artificial intelligence-assisted Chinese learning technologies. To better promote the application of artificial intelligence in learning scenarios, this study proposes four optimization strategies: enhancing the practicality and efficiency of AI learning tools, reducing users’ learning costs and optimizing interactive design, strengthening the positive guidance of social norms and cultural context, and perfecting relevant technical support and supporting infrastructure.Unified Theory of Acceptance and Use of Technology (UTAUT), Artificial intelligence, International Chinese language education, International students in China

[1] China.com, 2026, In-depth Analysis of Musk’s Interview: Stunning Predictions on AI and Future Society. https://news.china.com/socialgd/10000169/20260120/49179867.html [2] People’s Education, 2025, Expert Advisory Committee for Teacher Development, Ministry of Education. Guidelines for Teachers’ Application of Generative Artificial Intelligence (1st Edition). https://mp.weixin.qq.com/s/cvQOYRSXn2DnRVYGwebDiA [3] Ministry of Education, National Development and Reform Commission, Ministry of Science and Technology, et al., 2025, Opinions on Accelerating the Digitalization of Education. http://www.moe.gov.cn/srcsite/A01/s7048/202504/t20250416_1187476.html [4] The President of the CPC, 2025, Explanation on the Recommendations of the Central Committee of the Communist Party of China for Formulating the 15th Five-Year Plan for National Economic and Social Development. Qiushi Journal, 2025(21): 4–10. [5] Ministry of Education of the People’s Republic of China, 2025, Basic Education Teaching Steering Committee of the Ministry of Education. General Artificial Intelligence Education Guide for Primary and Secondary Schools (2025 Edition). https://mp.weixin.qq.com/s/o67cEFaf4QgtykB2smWz8Q [6] Ministry of Education of the People’s Republic of China, CCTV News Client, 2025, What Will the Future Classroom Be Like? Find Answers at the 2025 World Digital Education Conference. http://www.moe.gov.cn/jyb_xwfb/xw_zt/moe_357/2025/2025_zt06/mtbd/202505/t20250515_1190632.html [7] Shen Y, Ji HL, Ye XY, et al., 2023, Research on Human-Computer Interaction Technology in Virtual Reality Immersive Learning: Taking K12 Physics Experiment Teaching as an Example. E-education Research, 44(10): 87–94 + 120. [8] Chinese Alliance, 2025, Notice on Holding the Workshop on Innovation in International Chinese Language Teaching Driven by AI Agents. https://mp.weixin.qq.com/s/U1Kwk4WWJlAFZL-qFjO3Dg [9] Xu S, Tian XX, 2020, Research on Influencing Factors of Users’ Willingness to Use Online Learning Platforms Based on TAM. China Education Informatization, 2020(8): 78–85. [10] Wu HJ, Ge WS, He JH, 2020, A Study on the Influence of Teacher Support on Learners’ Continuous Learning Intention in MOOCs: From the Perspective of S-O-R and TAM. Modern Distance Education, 2020(3): 89–96. [11] Cai Y, Wang Z, 2022, A Study on Chinese Learners’ Willingness to Learn in Live Streaming Courses Based on Technology Acceptance Model. Language Teaching and Linguistic Studies, 2022(5): 35–46. [12] Xu JF, Deng QL, 2024, College English Learners’ Acceptance of Live Streaming Teaching Platforms: A Study Based on the Technology Acceptance Model. Foreign Language Teaching and Research, 56(2): 262–273 + 320–321. [13] Wei W, Xu Y, Wang Z, 2026, CSL Learners’ Acceptance and Use of ChatGPT: An Extended Technology Readiness and Technology Acceptance Model. Humanities and Social Sciences Communications, 13(1): 1–13. https://doi.org/10.1057/s41599-025-06452-w [14] Venkatesh V, Thong JYL, Xu X, 2012, Consumer Acceptance and Use of Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1): 157–178. [15] Venkatesh V, Morris M, Davis GB et al., 1997, User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3): 425–478. [16] Straub DW, Keil M, Brenner W, 1997, Testing the Technology Acceptance Model Across Cultures: A Three Country Study. Information & Management, 33(1): 1–11.