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Innovative Application and Societal Impact of AI in Student Behavior Early Warning Systems within Smart Campuses

Author(s)

Feng Zhou, Hong Lv*, Ke Zhou, Meilin Sheng, Junjie Jiang

Affiliation(s)

Xiangnan University, Chenzhou, China *Corresponding Author

Abstract

This study explores the innovative application and societal impact of artificial intelligence (AI) in student behavior early warning systems (EWS) within smart campuses. As information technology advances, smart campuses have become integral to modern education, and AI introduces new possibilities for EWS. Through literature review and theoretical analysis, this paper systematically reviews related studies, examining the current applications and potential societal impacts of AI in EWS. The study first defines the basic concepts of smart campuses and AI, followed by an analysis of AI's specific applications in EWS, including behavior data collection, analysis, and anomaly detection. A comprehensive review of existing research reveals that AI enhances the accuracy and timeliness of warnings and provides scientific decision support for educational administrators. However, AI's application also raises data privacy and ethical concerns, necessitating the development of relevant laws and ethical standards. The paper proposes future research directions, including optimizing AI algorithms, fostering interdisciplinary collaboration, and exploring AI applications in various educational settings. This study aims to provide theoretical support for smart campus development, promote the widespread use of AI in education, and enhance educational equity and quality.

Keywords

Smart Campus; Artificial Intelligence; Student Behavior Early Warning; Educational Management; Societal Impact

References

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