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

Authors: Feifei Wang; Fengxiang Zhang

Addresses: College of Foreign Languages, Hebei University of Economics and Business, Shijiazhuang 050061, China ' College of Foreign Languages, Hebei University of Economics and Business, Shijiazhuang 050061, China

Abstract: 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.

Keywords: social network; MOOC online English teaching; diversified evaluation; cosine similarity; comprehensive sorting.

DOI: 10.1504/IJWBC.2023.131401

International Journal of Web Based Communities, 2023 Vol.19 No.2/3, pp.175 - 186

Received: 31 Oct 2021
Accepted: 21 Feb 2022
Published online: 09 Jun 2023 *

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