Plagiarism or Productivity? Students Moral Disengagement and Behavioral Intentions to Use ChatGPT in Academic Writing

TL;DR

This study investigates how moral disengagement influences Filipino students' intentions to use ChatGPT in academic writing, highlighting the importance of clear policies and ethical guidance to promote responsible AI use.

Contribution

It introduces a model linking moral disengagement mechanisms to students' behavioral intentions to use ChatGPT, emphasizing the role of institutional and peer influences.

Findings

Attribution of blame strongly influences behavioral intentions.

Attitudes significantly impact students' willingness to use ChatGPT.

The model explains over half of the variation in students' behavioral intentions.

Abstract

This study examined how moral disengagement influences Filipino college students' intention to use ChatGPT in academic writing. The model tested five mechanisms: moral justification, euphemistic labeling, displacement of responsibility, minimizing consequences, and attribution of blame. These mechanisms were analyzed as predictors of attitudes, subjective norms, and perceived behavioral control, which then predicted behavioral intention. A total of 418 students with ChatGPT experience participated. The results showed that several moral disengagement mechanisms influenced students' attitudes and sense of control. Among the predictors, attribution of blame had the strongest influence, while attitudes had the highest impact on behavioral intention. The model explained more than half of the variation in intention. These results suggest that students often rely on institutional gaps and peer behavior to justify AI use. Many believe it is acceptable to use ChatGPT for learning or when rules are unclear. This shows a need for clear academic integrity policies, ethical guidance, and classroom support. The study also recognizes that intention-based models may not fully explain student behavior. Emotional factors, peer influence, and convenience can also affect decisions. The results provide useful insights for schools that aim to support responsible and informed AI use in higher education.