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新发传染病电子杂志 ›› 2025, Vol. 10 ›› Issue (1): 97-101.doi: 10.19871/j.cnki.xfcrbzz.2025.01.020

• 教育园地 • 上一篇    

基于粗糙集-重要表现程度分析法模型的区域远程教育云平台远程教育质量评价研究

苏日娜, 莎娜, 白杨, 刘建清, 张丽芳, 田峻玮   

  1. 内蒙古自治区人民医院远程医疗中心,内蒙古呼和浩特 010017
  • 收稿日期:2024-08-29 出版日期:2025-02-28 发布日期:2025-03-31
  • 通讯作者: 苏日娜,Email:297296117@qq.com
  • 基金资助:
    1.“宽带网络+健康乡村”入围应用试点项目(第一批)(工信厅联通信函〔2023〕393号);2.内蒙古自治区人民医院院内基金项目(2022YN37);3.内蒙古医学科学院公立医院联合基金项目(2024GLLH0066)

Research on quality evaluation of distance education in regional distance education cloud platform based on rough set-IPA model

Su Rina, Sha Na, Bai Yang, Liu Jianqing, Zhang Lifang, Tian Junwei   

  1. Inner Mongolia Autonomous Region People's Hospital, Inner Mongolia Hohhot 010017, China
  • Received:2024-08-29 Online:2025-02-28 Published:2025-03-31

摘要: 目的 以区域远程教育平台为研究基础,以平台内各级医院医务人员为研究对象,调查分析远程教育质量关键指标,为有效调整区域远程教育模式提供依据。方法 采用文献法、问卷调查法,以粗糙集-重要表现程度分析法(importance-performance analysis,IPA)为理论依据,构建区域远程教育质量指标库及权重。结果 通过粗糙集筛选指标、确定权重,最终筛选17个三级指标;经IPA建模,各指标重要程度的平均值是0.0588,满意度平均值为4.0260,有3项指标位于第Ⅰ象限继续维持区;9项指标位于第Ⅱ象限表现过渡区;2项指标位于第Ⅲ象限低优先级区;3项指标位于第Ⅳ象限重点改进区。结论 通过粗糙集理论及IPA模型的应用,可有效筛选出影响远程教育质量的关键因素,在远程教育工作中,加强激励机制,建立回访沟通机制,完善培训回放共享体系,优化远程教育流程,为医务人员提供更加便捷、优质的远程教育平台。

关键词: 粗糙集, 重要表现程度分析法模型, 远程教育, 质量评价

Abstract: Objective To investigate and analyze key indicators of tele-education quality based on regional tele-education platform, with medical personnel from hospitals at all levels within the platform as the research objects, in order to provides the basis for the effective adjustment of regional distance education model. Method Based on rough set and IPA model, the regional distance education quality index database and its weights are constructed by using literature method and questionnaire survey. Result 17 third-level indicators were selected through rough set screening and weight determination. After the IPA model was built, the average importance value of the indicators was 0.0588, and the average satisfaction value was 4.026. Three indicators were located in the sustaining area of the first quadrant, nine indicators were located in the transition area of the second quadrant, two indicators were located in the low priority area of the third quadrant, and three indicators were located in the priority improvement area of the fourth quadrant. Conclusion By applying rough set theory and IPA model, it is possible to effectively identify the key factors affecting the quality of remote education. In remote education work, it is necessary to strengthen the incentive mechanism, establish a feedback and communication mechanism, improve the sharing system of training replay, optimize the remote education process, and provide medical staff with a more convenient and high-quality remote education platform.

Key words: Rough set, Importance-Performance Analysis model, Distance education, Quality evaluation

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