Sun Wenyan, Jiang Zhanfeng, Hai Shenyang
School of MarXism, Henan Normal University, Xinxiang 453000, China.
International Business School, Hainan University, Haikou 570100, China.
Behav Sci (Basel). 2025 Sep 16;15(9):1267. doi: 10.3390/bs15091267.
Generative artificial intelligence (AI) has become an indispensable resource in contemporary higher education, providing substantial benefits to both students and institutions. As its adoption accelerates, it is important to balance these advantages against potential risks that may arise from students' varying levels of interaction with AI. Whereas most prior studies have focused on the favorable outcomes of AI for college students, the present research investigates its "double-edged sword" effects. Guided by social affiliation theory, a new model has been developed and empirically tested to clarify how and under what conditions the frequency of student-AI interaction influences social needs and behaviors. Longitudinal data obtained from 388 undergraduates showed that AI interaction frequency can shape prosocial behavior and problematic mobile phone use through a dual pathway involving the need for affiliation and feelings of loneliness. Furthermore, peer support moderates the indirect effect of AI interaction frequency on college students' prosocial behavior via their need for affiliation. The results showed that peer support did not significantly moderate the indirect relationship between AI interaction frequency and problematic mobile phone use through loneliness. Overall, our study extends the framework of the social affiliation theory and provides practical insights that guide the appropriate use of AI by college students, thereby supporting the development of healthy social skills and technology engagement in the age of AI.
生成式人工智能（AI）已成为当代高等教育中不可或缺的资源，为学生和院校带来了诸多益处。随着其应用加速，在这些优势与学生与AI不同互动水平可能引发的潜在风险之间取得平衡至关重要。尽管此前大多数研究聚焦于AI给大学生带来的积极成果，但本研究调查了其“双刃剑”效应。在社会归属理论的指导下，已开发并实证检验了一个新模型，以阐明学生与AI互动的频率如何以及在何种条件下影响社会需求和行为。从388名本科生那里获得的纵向数据表明，AI互动频率可通过一条涉及归属需求和孤独感的双重路径塑造亲社会行为和问题手机使用。此外，同伴支持调节了AI互动频率通过大学生的归属需求对其亲社会行为产生的间接影响。结果表明，同伴支持并未显著调节AI互动频率通过孤独感对问题手机使用产生的间接关系。总体而言，我们的研究扩展了社会归属理论的框架，并提供了实用见解，指导大学生恰当地使用AI，从而在人工智能时代支持健康社交技能和技术参与的发展。
