The Potential of Artificial Intelligence in Personalizing Learning Experiences for Students in Remote Chinese Regions
DOI:
https://doi.org/10.53797/ujssh.v4i2.22.2025Keywords:
AI in education, personalized learning, educational equity, remote learning, teacher empowermentAbstract
This study investigates the potential of artificial intelligence (AI) in personalizing learning for students in remote Chinese regions, a context characterized by significant educational disparities and resource scarcity. Using a quantitative quasi-experimental design with a pre-test/post-test control group, the research evaluated the impact of an AI-powered personalized learning platform over a six-month period. The sample consisted of middle school students and teachers in an underserved rural area. Key metrics included student academic performance, engagement levels, and teacher-reported workload and technology confidence. The findings reveal a statistically significant positive effect of the AI intervention. Students in the experimental group showed a remarkable 26.2% average score improvement, nearly double that of the control group. This was accompanied by a significant increase in student engagement, as evidenced by a higher post-test score on a motivational scale. Concurrently, teachers in the AI group reported a substantial reduction in time spent on grading and a marked increase in their confidence in using educational technology. The results suggest that AI offers a viable and effective strategy for bridging educational resource gaps, enhancing student outcomes, and empowering educators in geographically isolated and under-resourced environments. The study provides a strong empirical foundation for the strategic integration of AI into educational policy aimed at promoting equity.
References
Bhutoria, A. (2022). Personalized education and artificial intelligence in the United States, China, and India: A systematic review using a human-in-the-loop model. Computers and Education: Artificial Intelligence, 3, 100068.
https://doi.org/10.1016/j.caeai.2022.100068
Dai, M. (2024). Frontiers of Intelligent Education: Artificial Intelligence Reshaping the New Landscape of Chinese Higher Education. Journal of Advanced Research in Education, 3(2), 37–43. https://doi.org/10.56397/jare.2024.03.05
Huang, X. (2021). Aims for cultivating students’ key competencies based on artificial intelligence education in China. Education and Information Technologies, 26, 5127–5147. https://doi.org/10.1007/s10639-021-10530-2
Kangtong, L. (2021). Chinese Teachers Perceptions on the Use of AI-based Education Platform (Doctoral dissertation).
Koukaras, C., Koukaras, P., Ioannidis, D., & Stavrinides, S. G. (2025, March). AI-driven telecommunications for smart classrooms: Transforming education through personalized learning and secure networks. Telecom, 6(2), 21. https://doi.org/10.3390/telecom6020021
Li, Y., & Chai, Y. (2025). Bridging regional disparities through AI-driven personalized learning paths: evidence from Chinese high school education. Interactive Learning Environments, 1–16. https://doi.org/10.1080/10494820.2025.2523388
Liu, M., Ren, Y., Nyagoga, L. M., Stonier, F., Wu, Z., & Yu, L. (2023). Future of education in the era of generative artificial intelligence: Consensus among Chinese scholars on applications of ChatGPT in schools. Future in Educational Research, 1(1), 72-101. https://doi.org/10.1002/fer3.10
Liu, Z., & Yushchik, E. (2024). Exploring the prospects of using artificial intelligence in education. Cogent Education, 11(1), 2353464. https://doi.org/10.1080/2331186x.2024.2353464
Mahmoud, C. F., & Sørensen, J. T. (2024). Artificial Intelligence in Personalized Learning with a Focus on Current Developments and Future Prospects. Research and Advances in Education, 3(8), 25–31. https://doi.org/10.56397/rae.2024.08.04
Mustopa Mustopa, Nasikhin Nasikhin, Rikza Chamami, Hamidatun Nihayah, Muhammad Romadlon Habibullah, & Manshur, A. (2024). Challenges in Artificial Intelligence Development in Higher Education in China, India, and Indonesia: International Students’ Perspectives. International Journal of Learning, Teaching and Educational Research, 23(2), 354–373. https://doi.org/10.26803/ijlter.23.2.17
Papadopoulos, I., Lazzarino, R., Miah, S., Weaver, T., Thomas, B., & Koulouglioti, C. (2020). A systematic review of the literature regarding socially assistive robots in pre-tertiary education. Computers & Education, 155, 103924. https://doi.org/10.1016/j.compedu.2020.103924
Sun, L. (2024). Enhancing intercultural competence of Chinese English majors through AI-enabled Collaborative Online International Learning (COIL) in the digital era. Education and Information Technologies, 1-33. https://doi.org/10.1007/s10639-024-13143-7
Tapalova, O., & Zhiyenbayeva, N. (2022). Artificial Intelligence in Education: AIEd for Personalised Learning Pathways. Electronic Journal of E-Learning, 20(5), 639–653. https://doi.org/10.34190/ejel.20.5.2597
Wang, K., Chai, C.-S., Liang, J.-C., & Sang, G. (2024). Exploring teachers’ behavioural intentions to design artificial intelligence-assisted learning in Chinese K–12 education. Technology Pedagogy and Education, 1–17. https://doi.org/10.1080/1475939x.2024.2369241
Wei, X., Sun, S., Wu, D., & Zhou, L. (2021). Personalized online learning resource recommendation based on artificial intelligence and educational psychology. Frontiers in Psychology, 12, 767837. https://doi.org/10.3389/fpsyg.2021.767837
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