基于数据挖掘的思政教师教学能力评估模型设计

Design of Teaching Ability Evaluation Model for Ideological and Political Teachers Based on Data Mining

现有教学能力评估模型多为定性评估或简单的线性统计,其评估指标缺少关联性计算,影响模型评估精度,因而基于数据挖掘设计了思政教师教学能力评估模型。从课前、课中和课后3个方面选取评估指标,利用k-means聚类算法划分思政教师教学能力聚类。利用数据挖掘,关联能力评估指标,确定对教学能力的影响程度。采用层次分析和一致矩阵计算各指标的相对权重,构建教学能力评估模型。实验结果:此次设计模型的F1值为0.935,比现有模型高出0.094和0.085,证明设计模型输出结果的精度较高,具有更好的评估质量。

Most of the existing teaching ability evaluation models are qualitative evaluation or simple linear statistics, and their evaluation indexes lack of correlation calculation, which affects the evaluation accuracy. Therefore a system of evaluation indexes is determined from three aspects: before class, in class and after class, and the k-means clustering algorithm is used to divide the teaching ability of ideological and political teachers. Data mining is used to correlate the ability evaluation indicators, and determine the degree of influence on teaching ability. Analytic hierarchy process and consistent matrix are used to calculate the relative weight of each index, and the teaching ability evaluation model is constructed. Experimental results: the F1 value of the design model is 0.935, which is 0.094 and 0.085 higher than the existing models, and proves that the design model has higher accuracy and better evaluation quality.