From Innovation to Imitation: Associations Between Exposure to AI Prompt-Sharing Content on Social Media, Moral Disengagement, and Intention to Engage in Academic Misconduct

Abstract

The use of AI today has raised significant ethical concerns regarding its potential misuse in academic contexts. This paper aims to examine relationship between university students’ exposure to AI prompt-sharing content on social media, moral disengagement, perceived academic norms, and intentions to engage in AI-assisted academic misconduct. Specifically, the study investigated whether exposure to AI prompt-sharing content was associated with students’ intentions to engage in AI-assisted academic misconduct, whether moral disengagement mediated this relationship, and whether perceived academic norms moderated the association between exposure and moral disengagement. The study conducted SPSS-based descriptive statistics, regression, mediation, and moderation analyses of data collected through a structured questionnaire administered to 600 Chinese university students to verify three hypotheses. The findings indicate that greater exposure to AI prompt-sharing content was significantly associated with stronger intentions to engage in AI-assisted academic misconduct, with moral disengagement acting as a significant mediator, and perceived academic norms strengthening the association between exposure and moral disengagement. These observations indicate that AI prompt-sharing content on social media can be associated with students’ ethical decision-making regarding AI use in academic settings and highlight the importance of promoting responsible AI use and academic integrity in higher education.