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

页码：336 / 349

共 50 条

[1] A recognition method of learning behaviour in English online classroom based on feature data mining
Shi, Lu
Di, Xiaoran
International Journal of Reasoning-based Intelligent Systems, 2023, 15 (01): : 8 - 14
[2] Online Learning for Multimodal Data Fusion With Application to Object Recognition
Shahrampour, Shahin
Noshad, Mohammad
Ding, Jie
Tarokh, Vahid
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2018, 65 (09) : 1259 - 1263
[3] A recognition method of learning behaviour in online classroom based on feature data mining
Wang Y.
International Journal of Reasoning-based Intelligent Systems, 2024, 16 (01) : 50 - 57
[4] A Deep Reinforcement Learning Method For Multimodal Data Fusion in Action Recognition
Guo, Jiale
Liu, Qiang
Chen, Enqing
IEEE SIGNAL PROCESSING LETTERS, 2022, 29 : 120 - 124
[5] Multimodal music emotion recognition method based on multi data fusion
Zeng, Fanguang
INTERNATIONAL JOURNAL OF ARTS AND TECHNOLOGY, 2023, 14 (04) : 271 - 282
[6] An evaluation method of English online learning behaviour based on feature mining
Han, Chao
INTERNATIONAL JOURNAL OF CONTINUING ENGINEERING EDUCATION AND LIFE-LONG LEARNING, 2023, 33 (2-3) : 326 - 336
[7] An online learning behaviour recognition method based on tag set correlation learning
Ma, Ruijing
INTERNATIONAL JOURNAL OF BIOMETRICS, 2024, 16 (3-4) : 350 - 363
[8] Study on abnormal behaviour recognition of MOOC online English learning based on multi-dimensional data mining
Zhang, Fengxiang
Wang, Feifei
INTERNATIONAL JOURNAL OF CONTINUING ENGINEERING EDUCATION AND LIFE-LONG LEARNING, 2024, 34 (01) : 111 - 122
[9] A multimodal fusion emotion recognition method based on multitask learning and attention mechanism
Xie, Jinbao
Wang, Jiyu
Wang, Qingyan
Yang, Dali
Gu, Jinming
Tang, Yongqiang
Varatnitski, Yury I.
NEUROCOMPUTING, 2023, 556
[10] A reinforcement learning-based multimodal scenario hazardous behaviour recognition method
Sun, Di
Li, Yanjing
Han, Yuexia
International Journal of Computational Intelligence Studies, 2023, 12 (1-2) : 52 - 71

← 1 2 3 4 5 →