Zhang Zhaozhe, Andrés Javier De
School of Economics and Management, Henan Technical Institute, Zhengzhou, China.
Department of Accounting, Universidad de Oviedo, Oviedo, Spain.
PeerJ Comput Sci. 2024 Nov 21;10:e2509. doi: 10.7717/peerj-cs.2509. eCollection 2024.
The development of the world economy has prompted various countries to pay more attention to the teaching of online international trade courses based on deep learning. In the Internet age, online teaching has become an essential way for people to receive education. To guide the public in obtaining high-quality online teaching resources related to international trade, we propose an evaluation method for the implementation of international trade online courses based on deep learning. Firstly, by analyzing the characteristics of online education in international trade courses, we decompose the evaluation methods of online courses in international trade. Then, using deep learning technology, we propose a fusion method of multimodal evaluation features of online courses in international trade. Finally, we design a classification model to realize the effect evaluation of the course by inputting the fused features. Experiments show that our method can accurately evaluate the effect of international trade online courses, with an accuracy of 78.53%.
世界经济的发展促使各国更加重视基于深度学习的在线国际贸易课程教学。在互联网时代，在线教学已成为人们接受教育的一种重要方式。为了引导公众获取与国际贸易相关的优质在线教学资源，我们提出了一种基于深度学习的国际贸易在线课程实施效果评估方法。首先，通过分析国际贸易课程在线教育的特点，我们分解了国际贸易在线课程的评估方法。然后，利用深度学习技术，我们提出了一种国际贸易在线课程多模态评估特征的融合方法。最后，我们设计了一个分类模型，通过输入融合后的特征来实现课程效果评估。实验表明，我们的方法能够准确评估国际贸易在线课程的效果，准确率为78.53%。
