A study on the application effectiveness of a BOPPPS teaching model synergistically empowered by multiple generative language models in an undergraduate emergency medicine course
Teaching Reform|更新时间:2026-06-17
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A study on the application effectiveness of a BOPPPS teaching model synergistically empowered by multiple generative language models in an undergraduate emergency medicine course
Chinese Journal of Medical Education ResearchVol. 25, Issue 6, Pages: 686-693(2026)
作者机构:
1.兰州大学第一医院重症医学科,兰州 730000
2.兰州大学第一医院重症医学教研室,兰州 730000
3.兰州大学第一临床医学院,兰州 730000
4.兰州大学第一医院急诊科教研室,兰州 730000
5.兰州大学第一医院信息中心,兰州 730000
6.兰州大学第一临床医学院教务处,兰州 730000
7.兰州大学第一医院教务处,兰州 730000
8.兰州大学第一医院医学检验中心,兰州 730000
9.甘肃省妇幼保健院(甘肃省中心医院),兰州 746400
作者简介:
Chang Guixia, Email: Changguixia@lzu.edu.cn
基金信息:
Lanzhou University Education and Teaching Reform Research Project(20231118);Lanzhou University Education and Teaching Reform Research Project(20231119);Gansu Provincial Universities Postgraduate "Innovation Star" Program(2025CXZX-207)
Zhu Lei, Xu Yunpeng, Li Junfen, et al. A study on the application effectiveness of a BOPPPS teaching model synergistically empowered by multiple generative language models in an undergraduate emergency medicine course[J]. Chinese Journal of Medical Education Research, 2026, 25(6): 686-693.
Zhu Lei, Xu Yunpeng, Li Junfen, et al. A study on the application effectiveness of a BOPPPS teaching model synergistically empowered by multiple generative language models in an undergraduate emergency medicine course[J]. Chinese Journal of Medical Education Research, 2026, 25(6): 686-693.DOI: 10.3760/cma.j.cn116021-20251130-02237.
A study on the application effectiveness of a BOPPPS teaching model synergistically empowered by multiple generative language models in an undergraduate emergency medicine course
To investigate the application effectiveness of a BOPPPS teaching model (bridge-in
objective
pre-assessment
participatory learning
post-assessment
and summary) synergistically empowered by ChatGPT and Zhipu Qingyan in an undergraduate emergency medicine course.
Methods
2
A total of 741 medical students enrolled in the emergency medicine course at Lanzhou University during the 2024-2025 academic year were selected as the participants. Randomization was performed by class
assigning 375 students to the intervention group and 366 to the control group. The intervention group received instruction via the BOPPPS teaching model synergistically empowered by multiple generative language models
while the control group received instruction via the conventional BOPPPS model. ChatGPT was used to assist in generating course exercises
which were reviewed by teaching and research experts to establish an item bank. In addition
an intelligent course agent
the Emergency Medicine Artificial Intelligence (AI) Teaching Assistant
was developed based on Zhipu Qingyan. The item-generation performance of ChatGPT was evaluated. Differences in final examination scores between the two groups were compared
and surveys on classroom satisfaction and learning experience were conducted within the intervention group. Statistical analyses included
t
-tests
chi-square tests
and nonparametric tests.
Results
2
ChatGPT generated 440 single-choice and 440 multiple-choice questions. Based on a 5-point Likert scale evaluation
the overall satisfaction rates for single-choice and multiple-choice questions were 84.55% (372/440) and 80.91% (356/440)
respectively. The final comprehensive course score of the intervention group was 78 (74
81) points
which was significantly higher than the 75 (71
79) points in the control group (
P
<
0.001). Student satisfaction in the intervention group was higher than that in the control group across six domains: course introduction
clarity of learning objectives
classroom discussion and interaction
promotion of thinking development during teaching
immediate post-class assessment
and class summary (all
P
<
0.001). The learning experience survey in the intervention group showed that 85.00% (68/80) of students considered the AI teaching assistant appropriately designed
and 70.00% (56/80) expressed strong willingness to continue using it.
Conclusions
2
The BOPPPS teaching model synergistically empowered by ChatGPT and Zhipu Qingyan can effectively improve classroom learning outcomes and student learning experience in undergraduate emergency medicine education. This approach provides a feasible solution for the deep integration of AI technology with structured instructional models and warrants broader implementation.
关键词
Keywords
references
Taybeh EO , Naser AY , Taybeh A , et al . Public preparedness and knowledge about emergency medicine: a study across 6 countries [J ] . Medicine , 2025 , 104 ( 28 ): e43217 . DOI: 10.1097/md.0000000000043217 http://dx.doi.org/10.1097/md.0000000000043217 .
Cheng Y , Zhu L . A review of ChatGPT in medical education: exploring advantages and limitations [J ] . Int J Surg , 2025 , 111 ( 7 ): 4586 - 4602 . DOI: 10.1097/js9.0000000000002505 http://dx.doi.org/10.1097/js9.0000000000002505 .
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