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Students' attitudes toward LLMs and its association with metacognitive abilities: A cross-sectional study
Shihui Natalie Yeh1, Chiew-Jiat Rosalind Siah1
1National University of Singapore, Singapore.
Nurse Education in Practice
|September 26, 2025
Summary
Nursing students use large language models (LLMs) for enhanced learning regulation, but may experience reduced cognitive awareness. Digital literacy and metacognitive strategy instruction are recommended to mitigate overreliance on LLMs.
Area of Science:
- Educational Technology
- Nursing Education
- Cognitive Science
Background:
- Large language models (LLMs) offer personalized learning support.
- Limited understanding exists on LLM impact on nursing undergraduates' metacognition.
Purpose of the Study:
- Evaluate nursing undergraduates' attitudes toward LLMs.
- Assess the association between LLM use and metacognitive abilities.
Main Methods:
- Exploratory, cross-sectional, descriptive quantitative design.
- Examined relationships between student attitudes, metacognition, and LLM use.
Main Results:
- 204 nursing undergraduates participated.
- Found weaker cognitive awareness (p < .001) but stronger regulatory skills (p < .001) when using LLMs.
Conclusions:
- LLM use enhances regulatory skills but risks overreliance and reduced knowledge.
- Recommends explicit digital literacy and metacognitive strategy instruction.
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