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Qualitative interview findings revealed three major themes:
1. Cognitive offloading – students described using AI tools to reduce mental
effort in academic tasks.
2. Attention fragmentation – many participants reported difficulty
maintaining focus during long readings.
3. Reduced confidence in independent reasoning – several students
expressed uncertainty about their ability to produce academic work without technological
assistance.
4.2. Discussion
The findings of this study provide evidence that digital environments characterized
by rapid information consumption not only affect learning behavior but also profoundly
impact fundamental cognitive processes necessary for deep thinking. Consistent with
previous studies (Ophir et al., 2009; Rosen et al., 2013), students who frequently engage
in media multitasking show weaker attention span, particularly in tasks requiring
sustained focus. This suggests that continuous exposure to rapid and varied stimuli in
digital environments may impair the ability to maintain sustained attention – a
prerequisite for deep information processing.
From a cognitive perspective, these results can be explained through the concept of
cognitive offloading proposed by Andy Clark and David Chalmers (1998). Accordingly,
humans tend to transfer some cognitive processes to external tools. In the modern
context, these tools are not limited to information storage devices but have expanded to
include artificial intelligence systems capable of performing analytical, synthesis, and
reasoning tasks. When students rely excessively on AI for core cognitive activities, the
level of brain involvement in the learning process can be significantly reduced. This
weakens deep coding and limits the formation of lasting neural connections.
From a neuroscience perspective, the patterns observed in this study may be
related to disruptions in the activity of brain networks responsible for executive control
and long-term memory, particularly the interaction between the prefrontal cortex,
hippocampus, and neocortex. When attention is constantly fragmented, the neural
activity sequences necessary for memory consolidation through long-term potentiation
(LTP) may not be sustained long enough. This results in information being processed at a
superficial level and difficult to transfer to long-term memory. In the long run, neural
pathways involved in deep processing may weaken, while quick and surface cognitive
reflexes become dominant.
However, the findings also underscore that technology, including artificial
intelligence, is not inherently negative. On the contrary, the impact of AI strongly depends
on how it is used in the learning process. Students who use tools like ChatGPT as a means
to receive feedback, check reasoning, or refine ideas show higher levels of analytical
thinking than those who use AI to generate complete answers. This suggests that AI can
act as a cognitive scaffold – a tool to support thinking – if used correctly, rather than
becoming a mechanism to replace thinking.
When placing these findings within the broader context of the digital economy, it
can be seen that changes in students' cognitive behavior are not isolated phenomena but
rather the result of structural shifts in how knowledge is produced, distributed, and
consumed. The digital economy prioritizes speed, immediacy, and rapid information
processing. Technological platforms are designed to maximize user attention through
mechanisms such as personalized algorithms and dopamine-based reward loops. In such

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