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Title: The application effect of MOOC videos in English audio-visual teaching

Authors: Yansong Zhang

Addresses: College of International Education, Henan Finance University, Zhengzhou, 450046, China

Abstract: In order to improve the completeness and accuracy of evaluation indicators for the analysis of the effectiveness of English audio-visual teaching, a method for analysing the application effect of massive open online course (MOOC) videos in English audio-visual teaching is proposed. The factor analysis method is adopted to screen evaluation indicators for the application effect of MOOC videos in English audio-visual teaching, and the balanced iterative reducing and clustering using hierarchies (BIRCHs) algorithm is utilised to cluster the evaluation indicator data. Using the clustered indicator data as input variables and the application effect evaluation values as output variables, an adaptive BP neural network model is constructed to achieve accurate analysis of the application effect of MOOC videos in English audio-visual teaching. The experimental results show that the proposed method achieves a maximum recall rate of 98.56% in evaluating English audio-visual teaching effectiveness, and the evaluation accuracy varies between 94.76% and 97.82%.

Keywords: MOOC videos; English; audio-visual teaching; application effect; BIRCH algorithm; adaptive BP neural network model.

DOI: 10.1504/IJCEELL.2026.151822

International Journal of Continuing Engineering Education and Life-Long Learning, 2026 Vol.36 No.7, pp.74 - 93

Received: 13 May 2025
Accepted: 30 Sep 2025
Published online: 20 Feb 2026 *