Innovative Pathways for AI-Empowered Educational Management Models
DOI:
https://doi.org/10.63313/IJED.9030Keywords:
AI, Educational Administration, Model Innovation, Educational ResourcesAbstract
The application of Artificial Intelligence (AI) in education continues to expand, holding significant practical value in promoting innovation in educational management. By examining relevant domestic and international research to grasp cutting-edge developments in this field, this study conducts an in-depth analysis of AI-assisted educational management innovation pathways. It explores three dimensions—intelligent teaching management, precision student management, and efficient educational resource management—to detail how AI drives innovation in educational management models. Subsequently, this analysis examines multiple challenges currently faced—including technical bottlenecks, talent shortages, and institutional barriers—and proposes corresponding strategies to advance the modernization of educational management.
References
[1] Zhu, Z. T., Li, T. Y., & Zhang, Y. (2024). Developing new-quality education: A new path for digital and intelligent transformation in basic education. Research on Modern Distance Education, 36(04), 3-13+30.
[2] Zhang, Y. (2025, March 10). Exploring reforms in junior high school Chinese language teaching in a digital context. Middle School Curriculum Guidance.
[3] Yang, Q. W., & Tang, Q. (2025). Generative AI empowering graduate education: Theoretical logic, legal risks, and governance pathways. Research on Graduate Education, (02), 26-33.
[4] Shang, J. J. (2025, April 18). Artificial intelligence and higher education. https://nhb.shnu.edu.cn/a0/08/c28783a827400/page.htm
[5] Zhong, X. (2025). Technology literacy empowerment: A new pathway for learning transfer in language laboratories. Education and Research, 07(04), 105-108.
[6] Yang, Y. (2025). Exploring pathways to accelerate Hunan's development as an education powerhouse under the national education strategy. Contemporary Education Forum, (02), 1-6.
[7] Xuan, C. X., & Zhang, W. (2025). Digital intelligence empowering new-quality talent culti-vation in vocational colleges: Logical implications, practical challenges, and implementa-tion pathways. Journal of University Education Science, (01), 117-127.
[8] Ke, Q. C., Huang, C., Mi, Q. W., & Li, F. Q. (2025). How digitalization shapes new advantages in educational development during the construction of an education powerhouse. Re-search on Modern Distance Education, 37(01), 14-23.
[9] Zheng, Q. H., Sun, H. T., Chen, Y. H., & Liu, C. X. (2016). Modeling and application of online learning assessment based on learning analytics: A study on integrated modeling methods. Research on Educational Technology, 37(12), 40-45.
[10] Gu, X. Q., & Li, Y. Y. (2025). Building digital-ready schools: Teaching application scenarios and effectiveness empowered by digital intelligence. China Educational Technology, (04), 13-22.
[11] Zhong, X. (2024). Current status and future trends of artificial intelligence technolo-gy-driven curriculum informatization. International Journal of Computer Science and In-formation Technology (IJCSIT), 4(3), 426-435.
[12] Li, Y. F. (2025). International references for AI-empowered reform of higher education evaluation. Research in Educational Technology, 46(02), 32-40.
[13] Cai, M., & Sun, Z. Q. (2025). Value implications, core characteristics, and implementation pathways of AI-empowered vocational education. Education and Vocational Training, (03), 98-105.
[14] Mou, Z. J., Li, Y. T., & Yan, D. H. (2018). Design and implementation of a learning early warning system based on learning behavior data in a blended learning environment. Jour-nal of Distance Education, 36(03), 55-63.
[15] Feng, Y. G., & Liu, X. Q. (2025). The dialectical logic of reforming basic education systems. Educational Research, 46(03), 105-117.
[16] Xiao, M., Yu, L., Xiao, Y., Chen, K., Zhou, D. B., & Zhao, L. (2025). Research on AI-based aca-demic early warning models for college students. Modern Electronic Technology, 48(08), 155-163.
[17] Yi, H. (2024). How to conduct large-unit teaching in primary mathematics under the new curriculum standards. Tianjin Education, (19), 91-93.
[18] Wang, C. L. (2023). Research on the construction and application of precision teaching models supported by intelligent adaptive learning systems. Shanghai Education Research, (11), 55-60.
[19] Yi, K. Y., & Han, X. B. (2025). From blended learning to human-AI collaborative teaching: New pedagogical forms under generative AI transformation. China Distance Education, 45(04), 85-98.
[20] Li, P. L., Zhang, T., Ke, X., & Li, Z. R. (2024). Teaching reform and innovation in fine chemi-cal synthesis courses in the big data era. Yunnan Chemical Industry, 51(10), 203-207.
[21] Zhong, X. (2024). Innovative strategies for artificial intelligence-enabled language labora-tory teaching in the context of educational modernization. International Journal of Educa-tion and Social Development (IJESD), 1(2), 24-29.
[22] Chang, S., & Ding, Z. J. (2024, August 20). Practical challenges and breakthrough pathways for comprehensive quality evaluation in university admissions under the new college en-trance examination system. Education and Culture Materials, (16), 168-172.
[23] Yang, S. (2022, July 30). Amid the AI wave, data security must be safeguarded. Guangming Daily.
[24] Peng, D. Q. (2025, March 3). Are schools prepared for the impact of artificial intelligence? https://www.toutiao.com/article/7477431696531505718
[25] NetEase News. (2025, January 24). Over 70 million PowerSchool records stolen in massive education data breach. https://c.m.163.com/news/a/JMLP5E0A0511BLFD.html
[26] 26. Wang, Y. T. (2024, November 6). Roundup: Top ten cybersecurity incidents in the global education industry. https://wlaq.sspu.edu.cn/2024/1106/c5570a157676/page.htm
[27] Zheng, Q. S., & Wang, B. (2025). Strategic vision, real risks, and prevention strategies for generative AI empowering vocational education transformation. Education and Vocational Training, (06), 40-47.
[28] Zhong, X. (2024). Trends and prospects for the use of AI technology in language courses. Journal of Education and Educational Research (JEER), 8(2), 99-102.
[29] Qin, X. L., Gu, X., Li, D. C., & Xu, H. W. (2025). Overview and outlook of large language mod-els. Computer Applications, 45(03), 685-696.
[30] Chen, J. L., Kan, R., & Wang, D. (2024, May 30). Exploring AI-empowered talent cultivation models for economics elite. Foreign Economic Relations, (05), 136-139.
[31] Du, P., & He, Q. (2025). An analysis of teacher work hours in countries with high educa-tional performance: Current status, regulatory measures, and implications. Foreign Educa-tion Research, 52(02), 80-97.
[32] Lü, M. J. (2024). Research on innovation in university foreign language teaching models supported by intelligent foreign language teaching systems. Modern English, (08), 1-3.
[33] Min, W. F. (2025). Enhancing educational research quality through innovative research methods. Journal of East China Normal University (Educational Science Edition), 43(05), 1-15.
[34] Zhao, W. X. (2024, August 15). Research on the curriculum integration of counselor work in higher vocational colleges. Journal of Liaoning Economic Management Cadre Institute. Liaoning Economic Vocational and Technical College, (04), 109-111.
[35] Zhong, X. (2024). A new path to enhance students' comprehensive language literacy based on intelligent language laboratory. Scientific Journal of Technology (SJT), 6(11), 16-30.
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