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

Authors: Xiangzheng Diao

Addresses: School of International Education, Jiangsu Vocational Institute of Commerce, Nanjing, 211168, China

Abstract: 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.

Keywords: data mining; online teaching; quality assessment; association rules; principal component analysis; fuzzy analytical hierarchy process.

DOI: 10.1504/IJCEELL.2024.137114

International Journal of Continuing Engineering Education and Life-Long Learning, 2024 Vol.34 No.2/3, pp.286 - 298

Received: 04 Mar 2022
Accepted: 12 Jul 2022
Published online: 01 Mar 2024 *

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