Learning behaviour recognition method of English online course based on multimodal data fusion

被引：0
|
作者：
Li, Liangjie [1 ]
机构：
[1] Department of Foreign Affairs, Henan Finance University, Zhengzhou,450000, China
来源：
International Journal of Business Intelligence and Data Mining | 2024年 / 25卷 / 3-4期
关键词：
The conventional methods for identifying English online course learning behaviours have the problems of low recognition accuracy and high time cost. Therefore; a multimodal data fusion-based method for identifying English online course learning behaviours is proposed. Firstly; the analytic hierarchy process is used for decision fusion of multimodal data of learning behaviour. Secondly; based on the fusion results of multimodal data; weight coefficients are set to minimise losses and extract learning behaviour features. Finally; based on the extracted learning behaviour characteristics; the optimal classification function is constructed to classify the learning behaviour of English online courses. Based on the transfer information of learning behaviour status; the identification of online course learning behaviour is completed. The experimental results show that the recognition accuracy of the proposed method is above 90%; and its recognition accuracy is and can shorten the recognition time of learning behaviour; with high practical application reliability. © 2024 Inderscience Enterprises Ltd;
D O I：
10.1504/IJBIDM.2024.140880
中图分类号：
学科分类号：
摘要：
引用
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页码：336 / 349
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