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Cited by 517

The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.

Analysis of User Satisfaction with Online Education Platforms in China during the COVID-19 Pandemic

Open access
Chen, Tinggui, Peng, Lijuan, Yin, Xiaohua, Rong, Jingtao, Yang, Jianjun, Cong, Guodong·2020·Healthcare

Abstract

The outbreak of Corona Virus Disease 2019 (COVID-19) in various countries at the end of last year has transferred traditional face-to-face teaching to online education platforms, which directly affects the quality of education. Taking user satisfaction on online education platforms in China as the research object, this paper uses a questionnaire survey and web crawler to collect experience data of online and offline users, constructs a customer satisfaction index system by analyzing emotion and the existing literature for quantitative analysis, and builds aback propagation (BP) neural network model to forecast user satisfaction. The conclusion shows that users’ personal factors have no direct influence on user satisfaction, while platform availability has the greatest influence on user satisfaction. Finally, suggestions on improving the online education platform are given to escalate the level of online education during the COVID-19 pandemic, so as to promote the reform of information-based education.

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Crossref · 10.3390/healthcare8030200

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Metadata

Authors
Chen, T., Peng, L., Yin, X., Rong, J., Yang, J., & Cong, G.
Venue
Healthcare
Publisher
MDPI AG
Published
2020-07-07
Volume
8
Issue
3
Pages
200
ISSN
2227-9032 (ISSN-L)
OpenAlex
W3039163099
Cited by
517
References
35
FWCI
161.39
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Analysis of User Satisfaction with Online Education Platforms in China during the COVID-19 Pandemic. https://app.cochat.ai/papers/10.3390/healthcare8030200
The paper
Chen, T., Peng, L., Yin, X., Rong, J., Yang, J., & Cong, G. (2020). Analysis of User Satisfaction with Online Education Platforms in China during the COVID-19 Pandemic. Healthcare. https://doi.org/10.3390/healthcare8030200

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.