Title: A visual presentation of English online teaching information from a digital perspective

Authors: Feifei Dang

Addresses: School of Culture, Tourism and International Education, Henan Polytechnic Institute, Nanyang, Henan, 473009, China

Abstract: English online teaching needs auxiliary information when displaying teaching contents and methods. How to visually display this information has become the research focus. In this study, the cyclic neural network is introduced to extract the features of text and image. To solve the short storage time in the cyclic neural network, the long- and short-time memory network and gating unit are introduced. In addition, the stacking attention mechanism is introduced to improve the accuracy of text and image feature extraction. The results show that in the datasets Flickr-30K and MS-COCO, the recall and accuracy of the new model are higher. When dealing with textual data, it's A, R and F values are 0.892, 0.876 and 0.883, respectively; its maximum accuracy is 93.57%. It indicates that the attention mechanism can effectively improve the algorithm performance. The visualisation method based on neural network improves the display effect of English online teaching information.

Keywords: digital; English; online teaching; information visualisation; presentation methods.

DOI: 10.1504/IJCSYSE.2024.142778

International Journal of Computational Systems Engineering, 2024 Vol.8 No.3/4, pp.139 - 147

Received: 10 Apr 2023
Accepted: 02 May 2023
Published online: 21 Nov 2024 *

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