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2021 | OriginalPaper | Chapter

Influencing Factors of Students’ Online Learning Satisfaction During the COVID-19 Outbreak: An Empirical Study Based on Random Forest Algorithm

Authors : Yuzhuo Zhang, Po Zhang, Hongji Yang, Kangrui Zhao, Chunmei Han

Published in: Learning Technologies and Systems

Publisher: Springer International Publishing

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Abstract

New coronavirus is wreaking havoc around the world and has a profound impact on the international community, especially on higher education. Online teaching provides an effective path for higher education to avoid the risk of cross-contagion in traditional classroom education under epidemic condition. In order to ensure the quality of online teaching during the epidemic, this study takes the students’ satisfaction of online education learning as a measurement object. 1120 online learners from 126 colleges and universities in 26 provinces were investigated through 50 questions survey in 10 dimensions. First, the chi-square test is used to pre-process all the characteristics of the factors, and 30 influencing factors with the highest feature correlation are selected. Random forest algorithm is used to establish a satisfaction classification model in the training set. The accuracy in the test set is 0.72. Through the ranking of feature contribution, the influential factors with higher weight are obtained. The results show that in online learning, the attractiveness of teachers’ teaching methods is the most influential factor, while curriculum arrangement and learning environment rank second and third. Finally, according to the research results, this paper puts forward some suggestions and countermeasures.

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Metadata
Title
Influencing Factors of Students’ Online Learning Satisfaction During the COVID-19 Outbreak: An Empirical Study Based on Random Forest Algorithm
Authors
Yuzhuo Zhang
Po Zhang
Hongji Yang
Kangrui Zhao
Chunmei Han
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-66906-5_10

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