The Effect of University Students’ Attitudes toward Artificial Intelligence on Academic Motivation and Procrastination Behavior

Nowadays, with the widespread use of artificial intelligence (AI) technologies in educational environments, how students' attitudes toward these technologies affect academic processes has become an important research topic. This study aims to examine the effects of university students' attitudes toward AI on academic motivation and procrastination behaviors. 198 university students participated in the study. The data were collected online via Google Forms using a convenience sampling method from university students who volunteered to participate and using the General Attitude s Artificial Intelligence Scale, Academic Motivation Scale, and Tuckman Procrastination Tendency Scale. Pearson Correlation Analysis, Multivariate Analysis of Variance (MANOVA), and Multiple Linear Regression Analysis were used in the analysis of data. The findings showed that a positive AI attitude increased both intrinsic and extrinsic academic motivation, while a negative AI attitude only increased amotivation. However, no significant relationship was found between attitudes toward AI and procrastination behavior. Regression analyses showed that positive AI attitude had a statistically significant effect on increasing academic motivation, but this effect was limited by low explanation percentages. The findings of the study revealed that positive attitudes toward AI may support academic motivation, but it does not have a direct relationship with procrastination behavior. These results suggest that fostering positive attitudes toward AI may enhance students’ academic motivation, whereas procrastination behavior appears to be influenced by other individual factors beyond AI attitudes. The results emphasize the importance of strategies to improve individuals' attitudes toward AI to better understand the role of AI in academic processes and to encourage its effective use in educational environments.