在中国护士执照考试中,DeepSeek和ChatGPT-4o的比较表现
Xu Liu1,2, Haiyan Wang1, Xinyu Guo1,2
1The First Hospital of Jilin University.
The Journal of nursing education
|February 9, 2026
概括
开源的DeepSeek模型显示了护理教育的巨大潜力,在许可证考试问题上的准确性和逻辑一致性上超过了ChatGPT-4o. 需要进一步的研究来探索它们的全部教育应用.
科学领域:
- 教育中的人工智能
- 护理教育 技术 技术
背景情况:
- 像DeepSeek这样的开源AI模型为护理教育提供了潜力.
- 这些先进的人工智能模型在护理教育中的有效性目前尚未被探索.
研究的目的:
- 为了评估DeepSeek-R1,DeepSeek-V3和ChatGPT-4o的性能.
- 评估人工智能模型的准确性和逻辑一致性,用于护理执照考试.
主要方法:
- 利用了2025年中国护士执照考试的三个模拟考试中的720个问题.
- 与DeepSeek-R1,DeepSeek-V3和ChatGPT-4o的性能进行比较.
- 对答案准确性和逻辑一致性的集中分析.
主要成果:
- 在准确性方面,DeepSeek模型显著超过了ChatGPT-4o.
- 深度搜索-R1实现了87.5%-95.8%的准确性;深度搜索-V3实现了85.8%-94.2%的准确性.
- 深度搜索模型提供了比ChatGPT-4o更合乎逻辑的一致性和专业基础的解释.
结论:
- 深度搜索模型显示了作为护理和其他领域的教育工具的巨大潜力.
- 需要进一步的研究才能充分了解DeepSeek在教育中的应用和局限性.
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