From AI to action: Exploring the mediating role of ethical decision-making in the generative AI-procrastination relationship

Faculty Education Year: 2025
Type of Publication: ZU Hosted Pages: 2242- 2254
Authors:
Journal: International Journal of Innovative Research and Scientific Studies الهند Volume: 8
Keywords : From , , action: Exploring , mediating role , ethical    
Abstract:
This study explores the mediating role of ethical decision-making in the relationship between generative AI usage and academic procrastination among university students, addressing gaps in understanding how moral reasoning influences AI-human behavioral interactions. A cross-sectional survey was conducted with 727 participants from Al-Azhar University, Egypt, and the College of Basic Education, Public Authority for Applied Education and Training, Kuwait, with 609 females (83.8%) and 118 males (16.2%) across diverse educational backgrounds (doctoral, master's, graduate diploma levels, and undergraduate levels). Results revealed significant relationships among all variables. Generative AI usage negatively affected academic procrastination (β = -.208, p < .001) and positively affected ethical decision-making (β = .118, p < .001). Ethical decision-making negatively affected procrastination (β = -.159, p < .001). The total effect of generative AI usage on procrastination was significant (β = -.227, p < .001). The mediation analysis demonstrated that ethical decision-making partially mediates the AI-procrastination relationship, with a significant indirect effect (β = -.0188, 95% CI [-.0126, -.0022]) representing 8.27% of the total effect. Despite common assumptions, generative AI usage is linked to reduced academic procrastination, with ethical decision-making acting as a modest mediator. Moral reasoning is one pathway through which AI tools influence student behavior, while other mechanisms account for the majority of the effect. Educational institutions should develop AI literacy programs that promote technical competencies and ethical reasoning, rather than restrictive policies, to enhance academic productivity and promote responsible AI integration strategies.
   
     
 
       

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