Background and Aim: The current study aimed to develop a structural model exploring the impact of attitudes toward Artificial Intelligence (AI) and social media on academic dishonesty behaviors among elementary and middle school students.
Methods: This study utilized a quantitative, descriptive-correlational strategy. The statistical population consisted of all students in Urmia with N=90,000 during the 2024-2025 academic year, from which a sample of 401 students was selected using stratified random sampling. Data collection instruments included the General Attitudes Toward AI scale by Shipman and Rodway (2020), Use of Social Media scale by Hejazi et al. (2016), and the Academic Dishonesty scale by McCabe and Trevino (1996). Data analysis was performed using Structural Equation Modeling (SEM) through SPSS and Amos software.
Results: The findings indicated that attitude toward AI has a direct and significant effect on social media (beta=0.33, P<0.05) and an academic dishonesty (beta=0.28, P<0.05). Also, social media was the strongest direct predictor of academic dishonesty behaviors with a path coefficient (beta=0.54, P<0.01). Testing for indirect effects also confirmed the significant mediating role of social media in the relationship between attitudes toward AI and academic dishonesty (beta=0.39, P<0.05).
Conclusion: The research results elucidate that AI serves as a "tool" and social media as a "platform" which, by establishing group norms and fostering cognitive dependency, facilitate academic misconduct among the new generation. These results underscore the urgent necessity of revising traditional assessment models and integrating digital ethics and media literacy into school curricula to safeguard academic integrity.