Cognitive ease at a cost: LLMs reduce mental effort but compromise depth in student scientific inquiry
LMU Klinikum · Ludwig-Maximilians-Universität München · +2 more institutions
Abstract
This study explores the cognitive load and learning outcomes associated with using large language models (LLMs) versus traditional search engines for information gathering during learning. A total of 91 university students were randomly assigned to either use ChatGPT3.5 or Google to research the socio-scientific issue of nanoparticles in sunscreen to derive valid recommendations and justifications. The study aimed to investigate potential differences in cognitive load, as well as the quality and homogeneity of the students' recommendations and justifications. Results indicated that students using LLMs experienced significantly lower cognitive load. However, despite this reduction, these students demonstrated…
Citation impact
- FWCI
- 95.21
- Percentile
- 100%
- References
- 45
Authors
3Topics & keywords
- Argumentation theory
- Cognitive load
- Cognition
- Psychology
- Social psychology
- Mathematics education
- Applied psychology
- Cognitive psychology