It's Bad but It's Good: An Exploration of AI Cheating on Higher Educational Students Perspectives

Abstract

The ubiquitous artificial intelligence (AI) technology in the academic field is like a double-edged sword. The phenomenon has attracted researchers’ attention with more empirical evidence of the bright sights of AI adoption. To provide balanced views, this study aimed to extensively explore students’ perspectives on AI cheating behavior. The study consists of two phases, with a mixed-method design. The first phase adopts a quantitative in examining the relationship between external and internal factors in the decision to use AI technology being moderated by workplace spirituality. The second phase involves a qualitative approach aiming at gaining deeper perspectives on AI adoption among university students. The result of the first study revealed that only perceived injustice, intelligence, and self-efficacy affect AI cheating behavior. Meanwhile, spirituality lowers the possibility of AI cheating triggered by low intelligence and self-efficacy. The first phase of the study confirmed the adapted planned behavior framework in explaining students’ AI cheating mechanism. The second study further extends the study of understanding students’ AI cheating motivation, frequency, and consequences. Despite the unethical image and negative consequences, students still find it beneficial to their academic advancement. Finally, this study enhances the existing knowledge on AI cheating by setting the ground for further development of related constructs surrounding students’ AI cheating behavior. The finding suggested several ways universities could establish policies to mitigate students’ AI cheating behavior.

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