Mental Health

ChatGPT Use Could be Ruining Students' Memory, Grades

By Dynne C. | Update Date: Apr 08, 2024 03:00 AM EDT

Education and technology are both continuously evolving fields, and the integration of artificial intelligence (AI) tools in education has become increasingly prevalent. 

Among the many yet still increasing number of options, ChatGPT has been a crowd favorite. It has proven to be a powerful generative AI model, capable of providing quick responses to user queries. However, researchers found a concerning trend, where students relying heavily on ChatGPT may face detrimental consequences to their academic performance and cognitive abilities.

In a study, researchers revealed insights into the relationship between ChatGPT usage and academic outcomes. Conducted by researchers at the National University of Computer and Emerging Sciences in Pakistan, the study surveyed hundreds of university students across multiple phases.

The study uncovered a correlation between heavy ChatGPT reliance and negative academic indicators. Students facing high academic workloads and time pressures were more likely to turn to ChatGPT for assistance. However, this reliance was associated with increased procrastination, memory loss, and a decline in grade point averages (GPAs). The ease with which ChatGPT provides answers may lead students to reduce cognitive efforts, ultimately impairing their academic performance.

The role of rewards and motivation

Interestingly, the study also found that students sensitive to rewards were less inclined to use generative AI tools. This suggests a fear of potential repercussions among those seeking good grades, highlighting the relationship between motivation and technological dependency in academic settings.

While the study's findings emphasize the potential risks of excessive ChatGPT usage, it is essential to approach the results with caution. The bidirectional relationship between AI usage and academic performance needs further investigation, as does the reliance on self-reported data, which may introduce biases.

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