Application Analysis of Artificial Intelligence Technology in the Education Industry

Wen-Hua Zhang ( Cloud Network Technology Center, Migu Culture Technology Co., Ltd., Nanjing, Jiangsu, 210026, China )

https://doi.org/10.37155/2972-483X-0301-6

Abstract

With the rapid advancement of artificial intelligence (AI) technology, its application in the field of education has gradually deepened, exerting a profound impact on teaching models, learning support, educational management, and resource allocation. This paper examines the current state of AI application across four dimensions: instructional assistance, personalized learning, educational administration, and resource development. It analyzes practical challenges in areas such as technological compatibility, conceptual transformation, and ethical risks. The study highlights that the integration of AI and education must overcome limitations in data collection, algorithmic opacity, and system silos, while also addressing issues such as conflicts with traditional educational values, disparities in teachers’ digital literacy, and outdated evaluation systems. Based on these insights, the paper proposes coordinated strategies across technological development, educational practice, and social ethics, aiming to provide guidance for building an education ecosystem that balances technological empowerment with humanistic care, and to promote the rational application and deep integration of AI technology in educational settings.

Keywords

Artificial intelligence technology; education industry; educational management; educational resource development

Full Text

PDF

References

[1] Jin Min, Cao Peijie, Huang Baozhong. Technological Transformation and Educational Equity: Artificial Intelligence Reshaping Educational Opportunities. Journal of Zhejiang University (Humanities and Social Sciences Edition), 2025, 55(4): 39-55.
[2] Peng Ziming, Tan Weizhi. Technological Reconstruction of Learning and Educational Responses in the Era of Generative AI. Journal of Soochow University (Educational Science Edition), 2025, 13(1): 25-34.
[3] Mou Zhijia, Yue Ting, Zhu Tao. Personalized Learning Design Based on Cognitive Intelligence Large Models from the Perspective of Human-Machine Collaboration. Research in Electrochemical Education, 2025, 46(2): 80-87.

Copyright © 2025 Wen-Hua Zhang Creative Commons License Publishing time:2025-02-10
This work is licensed under a Creative Commons Attribution 4.0 International License