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空军军医大学护理系,西安 710000
画妍,Email:huayan1112@126.com
收稿:2026-01-09,
纸质出版:2026-04-20
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杨豪爽, 柳琴, 张立华, 等. 基于建构主义的“三段式”人机协同教学模式在心理护理实践教学的效果评估[J]. 中华医学教育探索杂志, 2026, 25(4): 424-433.
Yang Haoshuang, Liu Qin, Zhang Lihua, et al. Effectiveness evaluation of a constructivism-based three-stage human-artificial intelligence collaborative teaching model in psychological nursing practice education[J]. Chinese Journal of Medical Education Research, 2026, 25(4): 424-433.
杨豪爽, 柳琴, 张立华, 等. 基于建构主义的“三段式”人机协同教学模式在心理护理实践教学的效果评估[J]. 中华医学教育探索杂志, 2026, 25(4): 424-433. DOI: 10.3760/cma.j.cn116021-20260109-02270.
Yang Haoshuang, Liu Qin, Zhang Lihua, et al. Effectiveness evaluation of a constructivism-based three-stage human-artificial intelligence collaborative teaching model in psychological nursing practice education[J]. Chinese Journal of Medical Education Research, 2026, 25(4): 424-433. DOI: 10.3760/cma.j.cn116021-20260109-02270.
目的
2
在建构主义指导下,设计并实施“三段式”人机协同教学模式,评估其在心理护理实践教学中的应用效果。
方法
2
采用混合研究方法。选取空军军医大学2022级20名护理本科生为试验组,实施“三段式”人机协同教学模式;以2021级24名学生为对照组,接受传统教学。通过课程考核成绩比较、自编问卷调查学习效果,并采用目的抽样法对试验组11名学生进行半结构化访谈,运用Colaizzi现象学分析法提炼主题。采用SPSS 19.0进行统计分析。
结果
2
试验组课程考核成绩(82.95±3.49)高于对照组(77.63±5.84),差异有统计学意义(
t
=3.58,
P
<
0.001)。问卷调查结果显示,学生对教学模式的整体教学评价高(各条目得分4.65~4.80分),知识掌握自评(4.10±0.72分)、非知识性收获(各条目得分4.55~4.75分),教学模式体验(各条目得分4.30~4.80分)各项评分与理论中值(3分)比较,差异均有统计学意义(
t
值范围分别为5.66~19.62、6.85、13.58~17.62及6.73~19.62,均
P
<
0.001)。访谈归纳出4个主题:生成式人工智能(generative artificial intelligence,GAI)作为学习伙伴促进主动知识建构;问题驱动促进知识整合;教师主导是促进学生发展的关键支架;GAI是学生批判性认知加工工具。同时,研究发现GAI在情感回应深度等方面存在局限。
结论
2
“三段式”人机协同教学模式具有较好的教学效果,GAI作为学习伙伴,能有效支持学生在仿真实践中主动建构知识,教师作为高级学习伙伴的作用不可替代。
Objective
2
To design and implement a three-stage human-artificial intelligence (AI) collaborative teaching model under the guidance of constructivism
and evaluate its effectiveness in psychological nursing practice education.
Methods
2
A mixed-methods approach was adopted. Twenty undergraduate nursing students enrolled in 2022 at Air Force Medical University were assigned to the experimental group and received the three-stage human-AI collaborative teaching model
while 24 students enrolled in 2021 served as the control group and received traditional teaching. Learning outcomes were assessed through comparison of course examination scores and a self-designed questionnaire. Additionally
semi-structured interviews were conducted with 11 students from the experimental group selected through purposive sampling
and the data were analyzed using Colaizzi's phenomenological method to extract themes. Statistical analysis was conducted using SPSS 19.0.
Results
2
The experimental group achieved a significantly higher course examination score compared to the control group (82.95±3.49 vs. 77.63±5.84
t
=3.58
P
<
0.001). Questionnaire results showed high overall evaluations of the teaching model (item scores ranged from 4.65 to 4.80). The scores of overall evaluation
self-assessed knowledge mastery (4.10±0.72)
non-knowledge gains (item scores ranged from 4.55 to 4.75)
and teaching model experience (item scores ranged from 4.30 to 4.80) were significantly higher than the theoretical median of 3 points
and the
t
values were 5.66-19.62
6.85
13.58-17.62
and 6.73-19.62
respectively (all
P
<
0.001). Four themes emerged from the interviews: generative artificial intelligence (GAI) as a learning partner promotes active knowledge construction
problem-driven learning facilitates knowledge integration
teacher guidance serves as a key scaffold for student development
and GAI functions as a tool for students' critical cognitive processing. Limitations were identified
particularly in the depth of GAI emotional responsiveness.
Conclusions
2
The three-stage human-AI collaborative teaching model demonstrated favorable educational outcomes. GAI as a learning partner effectively supported students in active knowledge construction in simulated practice. However
the irreplaceable role of teachers as advanced learning partners remains essential.
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