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在医学教育中评估人工智能教师反:计算机基础和应用课程的案例研究本科生课程

Penglong Wang¹, Boyan Mi¹, Jiangdong Lu¹

¹Faculty of Military Health Services, Naval Medical University, Shanghai, China.

Disability and rehabilitation. Assistive technology

|September 15, 2025

概括

医学学生需要及时的反;人工智能导师提供解决方案. 虽然人工智能辅导员在专业课程中显示出明确,准确的反的潜力,但人类辅导员在整体上仍然优越.

科学领域:

医学教育医学教育
教育中的人工智能
计算机科学计算机科学

背景情况:

医学本科生面临的挑战是有限的计算机课程时间和网络访问,需要有效的反机制.
人工智能 (AI) 的进步为开发智能辅导系统提供了机会,以满足这些教育需求.

研究的目的:

探索AI反对医学学生学习成果的影响,使用微调的本地语言模型.
为了比较人工智能导师的表现和学生对传统人类导师的看法.

主要方法:

为第一年医学学生 (n=200) 开发了一个微调的本地语言模型作为人工智能导师.
学生在计算机课程之前和之后与人工智能导师互动,通过结构化问卷提供反.
部分最小平方结构方程建模 (PLS-SEM) 用于分析人工智能教师特征,学生特征和学习成果之间的关系.

主要成果:

人工智能和人类辅导员之间观察到一个显著的差异 (W=17.894,p<0.005).
人工智能教师的表现和学生的特征与学习结果的一致性较低 (HTMT 0.314,0.228).
人工智能导师获得了更高的准确度评分 (3.40,p<0.001) 并展示了对训练有素的知识领域的潜力.

结论:

人工智能导师在为医学学生提供专门的计算机课程中提供清晰,及时的反方面表现有前途.
人工智能导师可以作为有效的"智能笔记本"来提供短期的学习支持.
与人类导师相比,需要进一步开发以提高AI导师的表现和与学习成果的一致性.

关键词:

人工智能辅导员 AI辅导员人工智能 (AI) 是一种人工智能.行为建模行为建模.计算机基础课程计算机基础课程医学本科生医学本科生

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