Cognitive Ease at a cost: The Influence of Large Language Models on Student’s Mental Effort and Reasoning Quality

Large Language Models (LLMs), like ChatGPT-3.5, are fundamentally changing how students approach research topics by providing fast and detailed answers. But how do LLMs affect students’ cognitive load and learning outcomes compared to traditional tools like search engines? A recent study by Stadler et al. (2024) examined how both tools influenced students’ cognitive effort, reasoning quality, and engagement with the learning material. 


The study involved 91 college students divided into two groups: One group used ChatGPT-3.5, while the other used Google Search to gather recommendations and provide justifications for their findings. Results showed that students using LLMs experienced a lower cognitive load in extraneous, intrinsic, and germane cognitive demands than those using Google. This means they found the task more manageable overall. However, the ease came at a cost: LLM users provided weaker reasoning and justifications for their final recommendations. This suggests that while LLMs simplify information gathering, they may not encourage the deeper engagement with material needed for improved learning outcomes. Students relying on LLMs appeared less likely to process or critically analyze the information.   

Interestingly, the study found no significant difference in the variety of recommendations and justifications between the two groups. This indicates that LLMs don’t necessarily limit creativity or idea diversity. However, the quality of justifications was heavily influenced by germane cognitive load, highlighting the importance of more profound interaction with content.  

Key Takeaways for Educators and Learners 

The study revealed that while LLMs reduce cognitive effort, they may hinder the development of critical thinking and reasoning skills. Educators should guide students in using these tools responsibly, combining them with traditional methods like search engines or hands-on research. Encouraging students to cross-check information and engage deeply with diverse sources can enhance learning outcomes. In conclusion, while LLMs offer convenience, they cannot replace the intellectual rigor required for effective learning. Balancing technology use with critical thinking practices is crucial for fostering meaningful engagement and knowledge development. 

References
  • Stadler, M., Bannert, M., & Sailer, M. (2024). Cognitive ease at a cost: LLMs reduce mental effort but compromise depth in student scientific inquiry. Computers in Human Behavior, 160, 108386. https://doi.org/10.1016/j.chb.2024.108386 

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