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Journal of Nursing ›› 2024, Vol. 31 ›› Issue (16): 12-16.doi: 10.16460/j.issn1008-9969.2024.16.012

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Application of high-fidelity scenario simulation teaching based on knowledge graph in Emergency and Critical Care Nursing

RONG Xin-wen, SHI Lei, QIN Fang, FANG Ya-xuan, DONG Guang-yuan, LI Nan-yan, ZHU Wen-ting   

  1. School of Nursing, Southern Medical University, Guangzhou 510515, China
  • Received:2024-04-07 Online:2024-08-25 Published:2024-09-05

Abstract: Objective To explore the teaching effect of high-fidelity scenario simulation teaching based on knowledge graph in Emergency and Critical Care Nursing. Methods Nursing undergraduates in grade 2020 were selected. One class was randomly assigned as control group (35 students) and received conventional teaching. Another class was designated as experimental group (39 students) and participated in high-fidelity scenario simulation teaching using the knowledge graph in "Emergency and Critical Care Nursing". At the end of the course, autonomous learning ability in the two groups were compared. Teaching effectiveness questionnaire and qualitative interview were used to assess teaching effectiveness and students’ experience. Results The score of autonomous learning ability in the two groups were higher than that before the teaching (P<0.001, P<0.05). There was no statistical significance in the score between the two groups (P>0.05). In the experimental group, 77% of the students believed that the knowledge graph help "form patterns of thinking and problem-solving," and 69% thought knowledge graph was "beneficial for cultivating clinical thinking". Both teachers and students in the experimental group were satisfied with knowledge graph and the teaching plan. Conclusion The combination of knowledge graph and high-fidelity scenario simulation teaching can stimulate nursing students' interest, enhance their comprehensive competency, cultivate clinical thinking, and serve as reference for the intelligent transformation in nursing education.

Key words: knowledge graph, problem graph, Emergency and Critical Care Nursing, high-fidelity scenario simulation teaching

CLC Number: 

  • R47
[1] 中华人民共和国国家卫生健康委员会. 专科护理领域护士培训大纲[R]. (2007-06-12)[2023-09-03]. . 专科护理领域护士培训大纲[R]. (2007-06-12)[2023-09-03]. http://www.nhc.gov.cn/wjw/gfxwj/201304/ca9f66add17c45d89fd936a98dc75317.shtml.
[2] 曾慧, 杨娜娜, 李昌秀, 等. 3 C引导性反馈下情境模拟教学联合反思提示卡在护理学导论中的应用[J]. 护理学报, 2024, 31(3):21-24. DOI:10.16460/j.issn1008-9969.2024.03.021.
[3] 秦芳, 史蕾, 方雅璇, 等. 情境模拟在急危重症护理学教学中的应用[J]. 中华护理教育, 2019,16(7):524-528. DOI:10.3761/j.issn.1672-9234.2019.07.012.
[4] 张姮, 陈丽霞, 杜世正. 护理专业学生线上学习体验的现象阐释学研究[J]. 中华护理教育, 2022, 19(12):1091-1095. DOI:10.3761/j.issn.1672-9234.2022.12.007.
[5] 戴岭, 祝智庭. 教育数字化转型的逻辑起点、目标指向和行动路径[J]. 中国教育学刊, 2023(7): 14-20.
[6] 中共中央,国务院. 中国教育现代化2035[R]. (2019-02-23)[2023-08-27].中国教育现代化2035[R]. (2019-02-23)[2023-08-27].http://www.gov.cn/xinwen/2019-02/23/content_5367987.htm.
[7] 冯婷婷, 刘德建, 黄璐璐, 等. 数字教育:应用、共享、创新——2024世界数字教育大会综述[J]. 中国电化教育, 2024(3):20-36.
[8] SHAW RS.A study of learning performance of e-learning materials design with knowledge maps[J]. Computers & Education, 2010, 54(1):253-264. DOI:10.1016/j.compedu.2009.08.007.
[9] 杨冰香, 黄润, 徐爱京, 等. 模拟教学引导性反馈的标准和策略[J]. 中华护理教育, 2020, 17(1): 18-23. DOI:10.3761/j.issn.1672-9234.2020.01.003.
[10] 李振, 周东岱. 教育知识图谱的概念模型与构建方法研究[J]. 电化教育研究, 2019, 40(8):78-86;113. DOI:10.13811/j.cnki.eer.2019.08.010.
[11] 秦芳, 何小凤, 史蕾, 等. 同伴引航式引导性反馈在高仿真情境模拟教学中的应用[J]. 护理学杂志, 2023, 38(24): 68-71;75. DOI:10.3870/j.issn.1001-4152.2023.24.068.
[12] Cheng SF, Kuo CL, Lin KC, et al.Development and preliminary testing of a self-rating instrument to measure self-directed learning ability of nursing students[J]. Int J Nurs Stud, 2010, 47(9):1152-1158. DOI:10.1016/j.ijnurstu.2010.02.002.
[13] 李萍, 付路易, 棣群. 基于“SCE”项目改进《急危重症护理学》教学效果的研究[J]. 解放军护理杂志, 2020, 37(1): 86-89. DOI:10.3969/j.issn.1008-9993.2020.01.023.
[14] 蔡福满, 潘艳, 章飞飞, 等. 基于急危重症护理学在线课程平台的翻转课堂教学实践[J]. 解放军护理杂志, 2021, 38(6): 83-86. DOI:10.3969/j.issn.1008-9993.2021.06.022.
[15] Eel S, KYNGÄS H. The qualitative content analysis process[J]. J Adv Nurs, 2008, 62(1): 107-115. DOI:10.1111/j.1365-2648.2007.04569.x.
[16] 王敏, 陈丹, 欧阳旭平, 等. 基于自主学习系统的动态情景模拟在急危重症护理实训中的应用[J].护理学报, 2019, 26(17):10-13. DOI:10.16460/j.issn1008-9969.2019.17.010.
[17] 翟雪松, 许家奇, 童兆平, 等. 人工智能赋能高校韧性教学生态的路径研究[J]. 中国远程教育, 2023, 43(1): 49-58. DOI:10.13541/j.cnki.chinade.2023.01.007.
[18] 罗莎莎. 论智能时代教师角色变革的根本立场与价值逻辑[J]. 教师教育研究, 2021, 33(4): 32-37. DOI:10.13445/j.cnki.t.e.r.2021.04.006.
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