IJIET 2026 Vol.16(9): 2367-2377
doi: 10.18178/ijiet.2026.16.9.2695
doi: 10.18178/ijiet.2026.16.9.2695
Measuring the Impact of Generative AI on College Chinese Writing: A Structural Equation Modelling Approach
Zhiqin Li * and Tan Li Huan
Faculty of Social Sciences and Liberal Arts, UCSI University, Kuala Lumpur, Malaysia
Email: 1002060613@ucsiuniversity.edu.my (Z.L.); TanLH@ucsiuniversity.edu.my (T.L.H.)
*Corresponding author
Email: 1002060613@ucsiuniversity.edu.my (Z.L.); TanLH@ucsiuniversity.edu.my (T.L.H.)
*Corresponding author
Manuscript received August 10, 2025; revised November 21, 2025; accepted February 5, 2026; published September 10, 2026
Abstract—This study examines the impact of generative Artificial Intelligence (AI) on college Chinese writing instruction using Partial Least Squares Structural Equation Modelling (PLS-SEM). Drawing on an integrated framework combining the Technology Acceptance Model and Social Cognitive Theory, we investigate relationships between generative AI implementation strategies and learning outcomes through survey data from 376 undergraduate students across eight higher education institutions representing diverse institutional types and academic disciplines in China. Our findings confirm that both generative AI tool integration and instructor facilitation significantly enhance writing proficiency and critical thinking, with these relationships substantially mediated by student engagement with AI tools. The structural model reveals stronger effects on technical writing skills (β = 0.844) compared to critical thinking abilities (β = 0.709), with instructor facilitation demonstrating slightly greater influence than tool availability alone. The measurement model exhibits excellent reliability and validity, with all constructs showing Cronbach’s alpha values exceeding 0.87 and Average Variance Extracted (AVE) values above 0.79. These results provide empirical evidence for the effectiveness of generative AI in Chinese writing education while highlighting the crucial role of human guidance and student engagement in maximizing educational benefits, offering theoretical insights and practical guidance for educators seeking to integrate these emerging technologies into language instruction.
Keywords—generative Artificial Intelligence (AI), Chinese writing instruction, structural equation modelling, student engagement, higher education
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Keywords—generative Artificial Intelligence (AI), Chinese writing instruction, structural equation modelling, student engagement, higher education
Cite: Zhiqin Li and Tan Li Huan, "Measuring the Impact of Generative AI on College Chinese Writing: A Structural Equation Modelling Approach," International Journal of Information and Education Technology, vol. 16, no. 9, pp. 2367-2377, 2026.
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).