Chunhua Du1This email address is being protected from spambots. You need JavaScript enabled to view it., Qingpo Liu1, Wenjie Ji2, and Xiaohui Zhang1
1Zhejiang A&F University
2College of Economics and Management, Nanjing Agricultural University
Received: December 11, 2025 Accepted: January 18, 2026 Publication Date: March 2, 2026
Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.
Artificial Intelligence (AI) technology is driving a profound educational transformation, shifting from a supplementary instructional tool toward a strategic enabler of teaching management and instructional coordination. In traditional educational settings, teachers shoulder extensive responsibilities, which creates growing challenges in balancing instructional quality with increasing managerial and administrative demands. A critical issue is how AI can be leveraged to reduce teaching management burdens while improving the efficiency and coordination of instructional processes. To address this issue, this study investigates an AI-enabled multi-agent collaborative approach to support teaching management across the instructional workflow. The coordinated operation of multiple pedagogical AI teaching assistant supports core management functions, including lesson planning, assessment design, grading, learning progress monitoring, and instructional feedback coordination. The study is based on a real-world pilot implementation in a university setting and adopts a descriptive evaluation framework drawing on system usage data and faculty and student feedback. Results from nearly one year of application indicate that AI-supported teaching management can reduce lesson preparation time by approximately 70%, improve grading efficiency by about 90%, and enable rapid generation of multiple exam paper versions. These findings suggest that AI-enabled multi-agent collaboration can serve as an effective support mechanism for more efficient and coordinated teaching management in higher education.
[1] A. G. Cascu, (2025) “ARTIFICIAL INTELLIGENCE IN EDUCATION.THEPROMISEANDCHALLENGES OF THE SCHOOL OF THE FUTURE "International Journal of Social and Educational Innovation (IJ SEIro) 12(23): 83–98.
[2] M. Y. Mustafa, A. Tlili, G. Lampropoulos, R. Huang, P. Jandri´c, J. Zhao, S. Salha, L. Xu, S. Panda, Kinshuk, et al., (2024) “A systematic review of literature reviews on artificial intelligence in education (AIED): a roadmap to a future research agenda" Smart Learning Environments 11(1): 59.
[3] T. R. Gadekallu, G. Yenduri, R. Kaluri, D. S. Rajput, K. Lakshmanna, K. Fang, J. Chen, and W. Wang, (2025) “The role of GPT in promoting inclusive higher education for people with various learning disabilities: a review" PeerJ Computer Science 11: e2400.
[4] M. Zhuang, S. Long, F. Martin, and D. Castellanos Reyes, (2025) “The affordances of Artificial Intelligence (AI) and ethical considerations across the instruction cycle: A systematic review of AI in online higher education" The Internet and Higher Education: 101039.
[5] M. Imran and N. Almusharraf, (2024) “Google Gemini as a next generation AI educational tool: a review of emerging educational technology" Smart Learning Environments 11(1): 22.
[6] A. Harry, (2023) “Role of AI in education." Interdiciplinary Journal & Hummanity (INJURITY) 2(3):
[7] W. Park and H. Kwon,(2024) “Implementing artificial intelligence education for middle school technology education in Republic of Korea" International journal of technology and design education 34(1): 109–135.
[8] S. Salih, O. Husain, M. Hamdan, S. Abdelsalam, H. Elshafie, and A. Motwakel, (2025) “Transforming education with AI: A systematic review of ChatGPT’s role in learning, academic practices, and institutional adoption" Results in Engineering 25: 103837.
[9] H. C. Chen, J. X. Tian, and C. H. J. Chan, (2025) “Enhancing English pronunciation production and perception through corpus and AI-aided pedagogy" Computer Assisted Language Learning: 1–22.
[10] H. Crompton, A. Edmett, N. Ichaporia, and D. Burke, (2024) “AI and English language teaching: Affordances and challenges" British Journal of Educational Tech nology 55(6): 2503–2529.
[11] C.-J. Lin, H.-Y. Lee, W.-S. Wang, Y.-M. Huang, and T.-T. Wu, (2025) “Enhancing reflective thinking in STEM education through experiential learning: The role of gener ative AI as a learning aid" Education and Information Technologies 30(5): 6315–6337.
[12] W. Zhou, X. Xu, X. Luo, and G. Yang, (2025) “AI assisted instruction: an empirical study of an objective, observation, and organization-based SVVR approach to promote students’ English impromptu speaking performance, speaking anxiety, and cognitive network structure" Interactive Learning Environments: 1–18.
[13] A. Nam, (2025) “VIRTUAL AND TRADITIONAL LEARNING IN HIGHER EDUCATION IN UZBEK ISTAN: A SYSTEMATIC REVIEW OF COMPARA TIVE STUDIES." AMERICANJOURNALOFEDU CATIONANDLEARNING3(5):115–121.
[14] L. AlTwijri and S. M. Abdelhalim, (2026) “Enhancing reading engagement in adult EFL classrooms through AI supported instruction: A mixed-methods study" System 136: 103906.
[15] Y. Zhang, M. Zhang, L. Wu, and J. Li, (2025) “Digital transition framework for higher education in AI-assisted engineering teaching: Challenge, strategy, and initiatives in China" Science & Education 34(2): 933–954.
[16] M. Airaj, (2024) “Ethical artificial intelligence for teaching-learning in higher education" Education and Information Technologies 29(13): 17145–17167.
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