检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:杜丽娟[1] DU Lijuan(South China Institute of Software Engineering.GU,Guangzhou 510990,China)
出 处:《现代电子技术》2020年第15期101-104,共4页Modern Electronics Technique
摘 要:针对传统教育质量分级评价方法指标体系单一,导致分级评价准确性低,为此设计一种基于数据挖掘技术的大学教育质量分级评价方法。分析大学教育质量分级评价要求,确定分级评价指标,采用层次分析法计算分级指标权重,并进行一致性检验,最后将数据挖掘技术应用到大学教育质量分级评价中,实现大学教育质量分级评价。设计实例分析,以专家评价结果为标准,将设计方法和常规评价方法比较,常规方法与专家评价值最大误差为0.08分,设计方法与专家评价值最大误差为0.05分,因此,证明基于数据挖掘技术的大学教育质量分级评价方法比传统方法准确性高。The traditional grading evaluation method of education quality has a single index system,which leads to low accuracy of grading evaluation.Therefore,a university education quality grading evaluation method based on data mining is designed.The grading evaluation requirements of university education quality is analyzed,the grading evaluation indexes are determined,the grading index weights are calculated by analytic hierarchy process,and then consistency check is implemented.Finally,the data mining is applied to grading evaluation of university education quality to realize its grading evaluation.Examples are designed for analysis.Taking the expert evaluation results as the standard,the maximum error between the conventional method and the expert evaluation value is 0.08 points,while the maximum error between the design method and the expert evaluation value is 0.05 points when comparing the design method with the conventional evaluation method.Therefore,it proves that the university education quality grading evaluation method based on data mining is more accurate than the traditional method.
关 键 词:数据挖掘技术 指标体系 教育质量 分级评价 评价值对比 指标权重
分 类 号:TN911.1-34[电子电信—通信与信息系统] TP181[电子电信—信息与通信工程]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.15