基于数据挖掘的高职院校评价体系的研究与实践

Research and Practice of Evaluation System of Higher Vocational Colleges Based on Data Mining

指标体系的设计是高职院校评价的核心,目前国内对高职院校评价体系的研究集中在理论和政策方面,实证与模型研究较少。文章在前人研究的基础上,提出构建高职院校质量评价指标体系的15个关键点。以全国首批197所"双高计划"入选学校为样本,使用基于SOM神经网络的数据挖掘模型探索指标聚类关系,提出一套包含5个一级指标的评价体系,并以此为依据进行分类组合,验证了分别归属于不同类的指标组合能得到更好的聚类效果,筛选出合适的指标用以指导进一步的研究工作。

The design of the index system is the core in the evaluation of higher vocational colleges.The current domestic research on higher vocational evaluation system focuses on theories and policies.There are few empirical and model studies.On the basis of previous studies,15 key points are proposed to construct the quality evaluation index system of higher vocational colleges.The article also takes the first batch of 197 colleges selected in the"Double High Plan"as a sample,uses a data mining model based on SOM neural network to explore the index clustering relationship,proposes a set of index systems containing 5 first-level indicators,which are used as a basis for classification and combination,verifying that the combination of indicators belonging to different classes can get better clustering results,and selects suitable indicators to guide further research.