Mediating effects of artificial intelligence on the relationship between academic engagement and mental health among Chinese college students - Yalin Wang; Hui Wang (Frontiers in Psychology)
IntroductionAcademic engagement of Chinese college students has received increasing research attention due to its impact on Students’ Mental health and wellbeing. The emergence of artificial intelligence (AI) technologies marked the beginning of a new era in education, offering innovative tools and approaches to enhance learning. Still, it can be viewed from positive and negative perspectives. This study utilizes the Theory of Planned Behavior (TPB) as a theoretical framework to analyze the mediating role of students’ attitudes toward AI, perceived social norms, perceived behavioral control, and their intention to use AI technologies in the relationships between Students’ academic engagement and Mental health.MethodsThe study involved a total of 2,423 Chinese college students with a mean age of approximately 20.53 ± 1.51 years. The survey was conducted through Questionnaire Star, using a secure website designed specifically for the study. The Hayes’ PROCESS Macro (Version 4.2) Model 80 with SPSS 29.0, a multivariate regression analysis with a chain mediation model that allows for multiple mediators to be tested sequentially, has been used. The statistical test explored the direct and indirect effects of students’ engagement (X) on mental health (Y) through a series of mediators: attitude toward AI (M1), subjective norm (M2), perceived behavioral control over AI use (M3), and AI use behavioral intention (M4).ResultsThe direct positive relationship between engagement and mental health (β = 0.0575; p < 0.05), as well as identifying key mediating factors such as perceived behavioral control (β = 0.1039; p < 0.05) and AI use of behavioral intention (β = 0.0672; p < 0.05), highlights the potential of AI tools in enhancing students’ well-being. However, the non-significant mediating effects of attitude toward AI (β = 0.0135), and subjective norms (β = –0.0005), suggest that more research is needed to understand the nuances of these relationships fully.DiscussionOverall, the study contributes to the growing body of literature on the role of AI in education and offers practical implications for improving mental health support in academic settings.