Author(s)

ZeYu Wang¹, JiaNan Wang², Ting Ye¹, Jun Ruan^3*

Affiliation(s)

¹School of Public Administration, Guangzhou University, Guangzhou 510006, Guangdong, China.

²School of Management, Guangzhou University, Guangzhou 510006, Guangdong, China.

³School of Marxism, Central China Normal University, Wuhan 430079, Hubei, China.

Corresponding Author

Jun Ruan

ABSTRACT

With the rapid development of information technology, the application of Artificial Intelligence (AI) in education has become increasingly widespread, demonstrating immense potential particularly in the management of student ideological dynamics. Focused on the theme "From 'Data Monitoring' to 'Value Guidance': Intelligent Perception and Closed-Loop Intervention Pathways for Student Ideological Dynamics in the AI Era," this study explores how AI technology empowers the management of student ideological education. Research indicates that traditional ideological education models suffer from issues such as lag, passivity, and data fragmentation, leading to a core contradiction between educational goals and operational reality. This paper proposes that AI technology can effectively address these challenges and facilitate a paradigm shift in educational models. Through an in-depth analysis of the current status of student management and AI applications in education, this study constructs an intelligent perception system and designs a closed-loop intervention pathway. This framework includes a multimodal data collection mechanism, AI-driven data analysis models, a tiered early warning mechanism, and intelligent recommendation strategies for intervention. The research finds that sentiment tendency recognition based on Natural Language Processing (NLP) and group feature analysis using clustering algorithms significantly enhance the accuracy of sentiment identification and the effectiveness of group profiling. Empirical analysis demonstrates that the designed closed-loop intervention pathway offers significant advantages in early warning response efficiency and the effectiveness of ideological guidance. Furthermore, the paper discusses ethical norms regarding data collection, as well as algorithmic transparency and supervision mechanisms, to ensure the safety and fairness of technological application. The results show that AI technology not only realizes the paradigm shift from "monitoring" to "leading" but also provides an effective path for the reform of ideological and political education in colleges and universities. Overall, this paper expands educational technology theory and offers specific practical recommendations for reform, while also providing an outlook for future research directions. Despite certain limitations, this study serves as an important reference for the in-depth application of AI technology in the field of education.

KEYWORDS

Artificial Intelligence (AI); Ideological dynamics; Intelligent perception; Closed-loop intervention; Value guidance; Paradigm shift

CITE THIS PAPER

ZeYu Wang, JiaNan Wang, Ting Ye, Jun Ruan. Intelligent perception and value guidance in student ideological dynamics: designing an AI-based closed-loop intervention framework. World Journal of Management Science. 2025, 3(4): 54-69. DOI: https://doi.org/10.61784/wms3091.

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