Evaluating the effectiveness of online courses in international trade using deep learning

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%.

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Publication Details

Journal
PeerJ Computer Science
Published
2024-11-21
DOI
https://doi.org/10.7717/peerj-cs.2509
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.41
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article

Evaluating the effectiveness of online courses in international trade using deep learning

Javier de Andrés Suárez, Zhaozhe Zhang
1 citations
PeerJ Computer Science
Online Learning and Analytics
0.41
article

Evaluating the effectiveness of online courses in international trade using deep learning

Javier de Andrés Suárez, Zhaozhe Zhang
article en
1 citations

Abstract

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%.

PeerJ Computer ScienceVol. 10
Universidad de Oviedo (ES)
Partnerships for the goals
Openalex Percentile: Top 25%
Online Learning and Analytics
0.41
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