摘要
由于现有评估模型无法实现大任务量下的实效性量化评估。为此,提出了基于聚类分析算法的思政课程实效性量化评估模型。利用直接法对各个评估指标数据进行标准化处理,计算评估指标数据相关性,根据聚类分析算法将相关性较高的指标数据进行融合,通过聚类后的本质因子划分子序列的评估指标的类别,根据不同类别下的因子得分系数构建了思政课程自动评估模型,实现了思政课程时效性的自动评估。仿真实验结果表明,所提方法实现了大任务量下的思政课程时效性量化评估,且评估结果准确度较高,耗时较低。
Because the existing evaluation model can not realize the quantitative evaluation of the effectiveness under the large task. Therefore, a quantitative evaluation model of ideological and political curriculum effectiveness based on clustering analysis algorithm is designed. Using the direct method to standardize the data of each evaluation index, it calculates the correlation of the evaluation index data, and fuses the high correlation index data according to the clustering analysis algorithm. The automatic evaluation model of ideological and political curriculum is constructed according to the factor score coefficient of different categories, and the automatic evaluation of the timeliness of ideological and political curriculum is realized. The simulation results show that the proposed method realizes the quantitative evaluation of the timeliness of ideological and political courses under large task volume, and the evaluation results are more accurate and time-consuming.
作者
张哲
ZHANG Zhe(Zhaoqing Medical College,Ideological and Political Theory Teaching Department,Zhaoqing 526020 China)
出处
《自动化技术与应用》
2022年第6期166-168,186,共4页
Techniques of Automation and Applications
关键词
聚类分析算法
指标量化
自动评估
cluster analysis algorithm
quantification of indicators
automation assessment