Deadline Culture and AI Dependence: A Deep Learning Analysis of Students' Academic Behavior in The Digital Era

Abstract

In the midst of the widespread use of AI in academic activities, the phenomenon of deadline culture is increasingly seen as a factor that significantly shapes student learning behavior. The purpose of this study is to analyze how deadline culture encourages students to rely on AI as a quick strategy in completing tasks. The analysis is carried out through surveys and digital logs so that the phenomenon is seen empirically and objectively. The second goal is to explore the potential of deep learning in mapping AI usage patterns, including interaction time, intensity, and anomalies that appear before deadlines. This study uses a qualitative approach of the type of literature study with primary data from the book Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville as well as secondary data from books and articles relevant to this study. The results of this study are, first, showing that deadline culture plays a major trigger for the increase in students' dependence on AI, which can be seen through the acceleration of the use of this technology before the deadline, the shift in learning objectives from understanding to task completion, and the emergence of cognitive offloading patterns  that weaken independent thinking. Second, this study shows that deep learning is effective as an analytical tool to map students' academic behavior patterns, including the intensity of AI use, the type of task that triggers dependence, the motive for digital behavior, and the potential risk of academic dependence.