Multiple evaluation methods of MOOC online English teaching quality based on social network

被引：0
作者：
Wang F. [1 ]
Zhang F. [1 ]
机构：
[1] College of Foreign Languages, Hebei University of Economics and Business, Shijiazhuang
来源：
International Journal of Web Based Communities | 2023年 / 19卷 / 2-3期
关键词：
comprehensive sorting; cosine similarity; diversified evaluation; MOOC online English teaching; social network;
D O I：
10.1504/ijwbc.2023.131401
中图分类号：
学科分类号：
摘要：
In order to solve the problem of low evaluation accuracy of English teaching quality evaluation methods, this paper designs a diversified evaluation method of MOOC online English teaching quality based on social network. Firstly, the characteristics of social networks and the information interaction process between users are analysed, and the data affecting the quality evaluation are collected for normalisation. Then, the data with high similarity is determined by cosine similarity calculation to realise data preprocessing. Finally, the diversified evaluation indicators are normalised, the weight of diversified evaluation indicators is calculated, the quality data evaluation model of diversified teaching indicators is constructed, and the diversified evaluation is completed. The experimental results show that the evaluation accuracy of this method is always higher than 90%, and the evaluation time is less than 2.6 s, which has a certain reliability. Copyright © 2023 Inderscience Enterprises Ltd.
引用
收藏
页码：175 / 186
页数：11
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