Title: A recognition method of abnormal learning behaviour in MOOC online education based on background subtraction

Authors: Hongmei Wan

Addresses: School of Marxism, Hunan City University, Yiyang, Hunan, 413000, China

Abstract: In order to overcome the problems of high time-consuming and poor recognition accuracy of learning behaviour recognition, this paper proposes an abnormal learning behaviour recognition method for MOOC online education based on background subtraction. Firstly, the characteristics of students' abnormal learning behaviours are collected and extracted. Then, the background difference algorithm is used to obtain the foreground object and background of the learning image, and the image pixels are classified. Finally, the mean background method is used to obtain the learning background, the abnormal behaviour recognition classifier is designed, and the background subtraction method is used to realise the abnormal learning behaviour recognition. The results show that the recognition accuracy of this method is as high as 98.32%, the recognition time is only 0.52 s, and the recognition recall rate is as high as 96.7%, indicating that this method can improve the recognition effect of abnormal learning behaviour.

Keywords: background subtraction; binarisation treatment; mean background method; background difference method; online education.

DOI: 10.1504/IJITM.2025.144110

International Journal of Information Technology and Management, 2025 Vol.24 No.1/2, pp.52 - 66

Received: 24 Jun 2022
Accepted: 23 Sep 2022
Published online: 28 Jan 2025 *

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