Objective To design a WeChat mini program called Chinese Syndrome Differentiation Learning Platform(CSDLP)on smartphone to improve health literacy.Methods The developer tools of WeChat(Version:v1.01.170925)were used f...Objective To design a WeChat mini program called Chinese Syndrome Differentiation Learning Platform(CSDLP)on smartphone to improve health literacy.Methods The developer tools of WeChat(Version:v1.01.170925)were used for designing and debugging the mini program.SPSS17.0 was used for statistical purposes.“View container”“Basic content”“Form component”“Navigation”and“Media components”were used for the development of the WeChat mini program.The detailed method was referred to https://mp.weixin.qq.com/debug/wxadoc/dev/.Results A WeChat mini program called CSDLP was developed.This program has three major functions which are WeChat reading,WeChat class and WeChat syndrome differentiation.The official test report showed that there were no functionality errors for the seven android smartphones(referred to as A,B,C,D,E,F and G)that CSDLP was tested on.Statistical analysis results showed that the average memory in D,E,F and G was lower than in A,B and C.Average ratio was the highest in F and the lowest in G.The average loading time was the same for all smartphones.The audio database for diagnostics using traditional Chinese medicine(TCM)and a lecture video database were based on diagnostic textbook.Our team built a syndrome differentiation database which included 51 diseases.Conclusion CSDLP can improve knowledge visualization,studying process,and information sharing in terms of the training and development of new techniques for syndrome differentiation and treatment in TCM,and it can provide a better illustration for people to understand TCM.展开更多
[目的]针对《生物统计与试验设计》课程中数据处理复杂、学生参与度低等问题,开发一款轻量化教学工具,探索数字化教学改革的有效路径。[方法]基于Uniapp跨平台框架,结合豆包人工智能辅助开发技术,构建集成生物统计计算、试验设计模拟及...[目的]针对《生物统计与试验设计》课程中数据处理复杂、学生参与度低等问题,开发一款轻量化教学工具,探索数字化教学改革的有效路径。[方法]基于Uniapp跨平台框架,结合豆包人工智能辅助开发技术,构建集成生物统计计算、试验设计模拟及案例实操功能的微信小程序,在实验班(医动2211,n=23)与对照班(医动2212,n=26)开展对比教学实验,评估小程序的应用效果。[结果]教学实践数据显示:实验组学生完成数据处理任务的平均耗时较对照组缩短43.75%(45 min vs.80 min),课堂主动提问频次提升149%(2.64次/课vs.1.06次/课),理论知识考核成绩提高21.4%(85分vs.70分),实践操作成绩提升33.3%(40分vs.30分),差异均具有统计学意义(P<0.05);问卷调查表明,实验组学生课堂参与积极性达70%,显著高于对照组的35%。[结论]基于Uniapp和豆包AI的轻量化开发的微信小程序,显著提升了学生的理论理解深度与实践能力,为职业院校专业课程的数字化转型提供了可复制的解决方案。未来可进一步优化小程序功能,深化工具与教学场景的融合。展开更多
基金funding support from the National Natural Science Foundation of China (No.81373551)2016 Hunan Provincial Postgraduate Research Innovation Project (No.CX2016B367)
文摘Objective To design a WeChat mini program called Chinese Syndrome Differentiation Learning Platform(CSDLP)on smartphone to improve health literacy.Methods The developer tools of WeChat(Version:v1.01.170925)were used for designing and debugging the mini program.SPSS17.0 was used for statistical purposes.“View container”“Basic content”“Form component”“Navigation”and“Media components”were used for the development of the WeChat mini program.The detailed method was referred to https://mp.weixin.qq.com/debug/wxadoc/dev/.Results A WeChat mini program called CSDLP was developed.This program has three major functions which are WeChat reading,WeChat class and WeChat syndrome differentiation.The official test report showed that there were no functionality errors for the seven android smartphones(referred to as A,B,C,D,E,F and G)that CSDLP was tested on.Statistical analysis results showed that the average memory in D,E,F and G was lower than in A,B and C.Average ratio was the highest in F and the lowest in G.The average loading time was the same for all smartphones.The audio database for diagnostics using traditional Chinese medicine(TCM)and a lecture video database were based on diagnostic textbook.Our team built a syndrome differentiation database which included 51 diseases.Conclusion CSDLP can improve knowledge visualization,studying process,and information sharing in terms of the training and development of new techniques for syndrome differentiation and treatment in TCM,and it can provide a better illustration for people to understand TCM.
文摘[目的]针对《生物统计与试验设计》课程中数据处理复杂、学生参与度低等问题,开发一款轻量化教学工具,探索数字化教学改革的有效路径。[方法]基于Uniapp跨平台框架,结合豆包人工智能辅助开发技术,构建集成生物统计计算、试验设计模拟及案例实操功能的微信小程序,在实验班(医动2211,n=23)与对照班(医动2212,n=26)开展对比教学实验,评估小程序的应用效果。[结果]教学实践数据显示:实验组学生完成数据处理任务的平均耗时较对照组缩短43.75%(45 min vs.80 min),课堂主动提问频次提升149%(2.64次/课vs.1.06次/课),理论知识考核成绩提高21.4%(85分vs.70分),实践操作成绩提升33.3%(40分vs.30分),差异均具有统计学意义(P<0.05);问卷调查表明,实验组学生课堂参与积极性达70%,显著高于对照组的35%。[结论]基于Uniapp和豆包AI的轻量化开发的微信小程序,显著提升了学生的理论理解深度与实践能力,为职业院校专业课程的数字化转型提供了可复制的解决方案。未来可进一步优化小程序功能,深化工具与教学场景的融合。
