A quantitative evaluation method of online teaching quality based on data mining

被引：0
|
作者：
Diao, Xiangzheng [1 ]
机构：
[1] Jiangsu Vocat Inst Commerce, Sch Int Educ, Nanjing 211168, Peoples R China
来源：
INTERNATIONAL JOURNAL OF CONTINUING ENGINEERING EDUCATION AND LIFE-LONG LEARNING | 2024年 / 34卷 / 2-3期
关键词：
data mining; online teaching; quality assessment; association rules; principal component analysis; fuzzy analytical hierarchy process; STUDENTS;
D O I：
10.1504/IJCEELL.2024.137114
中图分类号：
G40 [教育学];
学科分类号：
040101 ; 120403 ;
摘要：
The quantitative evaluation of online teaching quality is affected by data and has problems of high time consumption and low accuracy. Therefore, a quantitative evaluation method of online teaching quality based on data mining is designed. Firstly, through association rules in data mining, data are collected, evaluation indexes are obtained by principal component analysis, and evaluation index system is established. Then, fuzzy analytic hierarchy process (AHP) is used to calculate the weights of evaluation indexes in the evaluation index system. Finally, an evaluation model is established to realise the quantitative evaluation of online teaching quality. The experiment shows that the accuracy value of the proposed method reaches 89%, and the evaluation time is 3.8 s, which improves the accurate and efficient evaluation of online teaching quality.
引用
收藏
页码：286 / 298
页数：14
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