Ứng dụng Agent AI trong phát triển nhà trường thông minh: Tổng quan nghiên cứu và định hướng triển khai tại Việt Nam
Tóm tắt
The rapid development of Generative Artificial Intelligence (Generative AI) and Agent AI has created new opportunities for digital transformation and the development of smart schools. However, existing studies mainly focus on isolated applications of Agent AI in teaching, learning, or educational management, while comprehensive reviews and integrated architectural models suitable for the Vietnamese educational context remain limited. This study employs a structured literature review method, combined with qualitative content analysis, to synthesize, analyze, and systematize research on AI agents in smart schools. Relevant publications were collected from Scopus, Web of Science, IEEE Xplore, SpringerLink, ScienceDirect, and Google Scholar, with the inclusion criteria covering peer-reviewed publications from 2020 to 2025 directly related to the research topic. The findings indicate that Agent AI is evolving from task-oriented AI assistants toward multi-agent ecosystems capable of autonomous planning, collaboration, and orchestration across educational activities. Based on the synthesized evidence, this paper proposes a conceptual Agent AI ecosystem model for Vietnamese smart schools, consisting of five functional layers and specialized agents supporting teaching, learning, assessment, research, educational management, and digital services. The proposed model provides a theoretical foundation and practical orientation for future research and implementation of Agent AI in educational institutions, contributing to the digital transformation of education in Vietnam.
Tài liệu tham khảo
Acharya, D. B., Kuppan, K., & Divya, B. (2025). Agentic AI: Autonomous Intelligence for Complex Goals-A Comprehensive Survey. IEEE Access, 13, 18912-18936. https://doi.org/10.1109/ACCESS.2025.3532853
Aguilar, J., Chamba-Eras, L., & Cordero, J. (2016). Specification of a Smart Classroom Based on Agent Communities (pp. 1003-1012). https://doi.org/10.1007/978-3-319-31232-3_95
Aguilar, J., Sánchez, M., Cordero, J., Valdiviezo-Díaz, P., Barba-Guamán, L., & Chamba-Eras, L. (2018). Learning analytics tasks as services in smart classrooms. Universal Access in the Information Society, 17(4), 693-709. https://doi.org/10.1007/s10209-017-0525-0
Alfoudari, A. M., Durugbo, C. M., & Aldhmour, F. M. (2021). Understanding socio-technological challenges of smart classrooms using a systematic review. Computers & Education, 173, 104282. https://doi.org/10.1016/j.compedu.2021.104282
Cetinkaya, N. E., & Krämer, N. (2025). Between transparency and trust: identifying key factors in AI system perception. Behaviour & Information Technology, 1-15. https://doi.org/10.1080/0144929X.2025.2533358
Deng, R., Jiang, M., Yu, X., Lu, Y., & Liu, S. (2025). Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies. Computers & Education, 227, 105224. https://doi.org/10.1016/j.compedu.2024.105224
Díaz-Rodríguez, N., Del Ser, J., Coeckelbergh, M., López de Prado, M., Herrera-Viedma, E., & Herrera, F. (2023). Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation. Information Fusion, 99, 101896. https://doi.org/10.1016/j.inffus.2023.101896
Figueroa, E., Batista, E., Molero-Aranda, T., Ferre, M., & Martínez-Ballesté, A. (2026). Smart classroom ontology: enhancing interoperability in learning environments. Knowledge and Information Systems, 68(1), 75. https://doi.org/10.1007/s10115-026-02695-4
Hauk, D., & Soujon, N. (2026). How reliable are large language models in analyzing the quality of written lesson plans? A mixed-methods study from a teacher internship program. Computers and Education: Artificial Intelligence, 10, 100538. https://doi.org/10.1016/j.caeai.2025.100538
Huang, L., Yu, W., Ma, W., Zhong, W., Feng, Z., Wang, H., Chen, Q., Peng, W., Feng, X., Qin, B., & Liu, T. (2025). A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions. ACM Transactions on Information Systems, 43(2), 1-55. https://doi.org/10.1145/3703155
Levine, S., Beck, S. W., Mah, C., Phalen, L., & PIttman, J. (2025). How do students use ChatGPT as a writing support? Journal of Adolescent & Adult Literacy, 68(5), 445-457. https://doi.org/10.1002/jaal.1373
Liao, J., Zhong, L., Zhe, L., Xu, H., Liu, M., & Xie, T. (2024). Scaffolding Computational Thinking With ChatGPT. IEEE Transactions on Learning Technologies, 17, 1628-1642. https://doi.org/10.1109/TLT.2024.3392896
Liu, Q., & Khalil, M. (2023). Understanding privacy and data protection issues in learning analytics using a systematic review. British Journal of Educational Technology, 54(6), 1715-1747. https://doi.org/10.1111/bjet.13388
Li, Z., Wang, Z., Wang, W., Hung, K., Xie, H., & Wang, F. L. (2025). Retrieval-augmented generation for educational application: A systematic survey. Computers and Education: Artificial Intelligence, 8, 100417. https://doi.org/10.1016/j.caeai.2025.100417
Lu, J., Zheng, R., Gong, Z., & Xu, H. (2024). Supporting Teachers’ Professional Development With Generative AI: The Effects on Higher Order Thinking and Self-Efficacy. IEEE Transactions on Learning Technologies, 17, 1267-1277. https://doi.org/10.1109/TLT.2024.3369690
McCormack, L., & Bendechache, M. (2025). A comprehensive survey and classification of evaluation criteria for trustworthy artificial intelligence. AI and Ethics, 5(3), 1973-1994. https://doi.org/10.1007/s43681-024-00590-8
Ng, D. T. K., Tan, C. W., & Leung, J. K. L. (2024). Empowering student self‐regulated learning and science education through ChatGPT: A pioneering pilot study. British Journal of Educational Technology, 55(4), 1328-1353. https://doi.org/10.1111/bjet.13454
Okonkwo, C. W., & Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100033. https://doi.org/10.1016/j.caeai.2021.100033
Pham, N., Pham Ngoc, H., & Nguyen-Duc, A. (2025). Fairness for machine learning software in education: A systematic mapping study. Journal of Systems and Software, 219, 112244. https://doi.org/10.1016/j.jss.2024.112244
Possaghi, I., Vesin, B., Zhang, F., Sharma, K., Knudsen, C., Bjørkum, H., & Papavlasopoulou, S. (2025). Integrating multi-modal learning analytics dashboard in K-12 education: insights for enhancing orchestration and teacher decision-making. Smart Learning Environments, 12(1), 53. https://doi.org/10.1186/s40561-025-00410-4
Rojas, M. P., & Chiappe, A. (2024). Artificial Intelligence and Digital Ecosystems in Education: A Review. Technology, Knowledge and Learning, 29(4), 2153-2170. https://doi.org/10.1007/s10758-024-09732-7
Sharma, S., Mittal, P., Kumar, M., & Bhardwaj, V. (2025). The role of large language models in personalized learning: a systematic review of educational impact. Discover Sustainability, 6(1), 243. https://doi.org/10.1007/s43621-025-01094-z
Shi, Y., Yu, K., Dong, Y., & Chen, F. (2026). Large language models in education: a systematic review of empirical applications, benefits, and challenges. Computers and Education: Artificial Intelligence, 10, 100529. https://doi.org/10.1016/j.caeai.2025.100529
Smutny, P., & Schreiberova, P. (2020). Chatbots for learning: A review of educational chatbots for the Facebook Messenger. Computers & Education, 151, 103862. https://doi.org/10.1016/j.compedu.2020.103862
Tao, Y., Viberg, O., Baker, R. S., & Kizilcec, R. F. (2024). Cultural bias and cultural alignment of large language models. PNAS Nexus, 3(9). https://doi.org/10.1093/pnasnexus/pgae346
Terzieva, V., Ilchev, S., & Todorova, K. (2022). The Role of Internet of Things in Smart Education. IFAC-PapersOnLine, 55(11), 108-113. https://doi.org/10.1016/j.ifacol.2022.08.057
Tian, J., & Zhang, R. (2025). Learners’ AI dependence and critical thinking: The psychological mechanism of fatigue and the social buffering role of AI literacy. Acta Psychologica, 260, 105725. https://doi.org/10.1016/j.actpsy.2025.105725
Walters, W. H., & Wilder, E. I. (2023). Fabrication and errors in the bibliographic citations generated by ChatGPT. Scientific Reports, 13(1), 14045. https://doi.org/10.1038/s41598-023-41032-5
Xi, Z., Chen, W., Guo, X., He, W., Ding, Y., Hong, B., Zhang, M., Wang, J., Jin, S., Zhou, E., Zheng, R., Fan, X., Wang, X., Xiong, L., Zhou, Y., Wang, W., Jiang, C., Zou, Y., Liu, X., … Gui, T. (2025). The rise and potential of large language model based agents: a survey. Science China Information Sciences, 68(2), 121101. https://doi.org/10.1007/s11432-024-4222-0
Tải xuống
Đã Xuất bản
Cách trích dẫn
Số
Chuyên mục
Giấy phép
Bản quyền (c) 2026 Tạp chí Giáo dục
Tác phẩm này được cấp phép theo Ghi nhận tác giả của Creative Commons Giấy phép quốc tế 4.0 .
