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

By Tinggui Chen, Lijuan Peng, Xiaohua Yin, Jingtao Rong, Jianjun Yang, Guodong Cong. Healthcare, 2020

434 citations recorded by the source corpus.

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.

Subfields: Information Systems and Management, Organizational Behavior and Human Resource Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/8bc389be4a53ccd078a061a32fdcd70b3175813d

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In Sociology and Political Science

Citations in the corpus

Difficulties in Remote Learning: Voices of Philippine University Students in the Wake of COVID-19 Crisis (2020, background): “This may also stem from teachers’ lack of experience in remote learning (Chen et al., 2020), thus giving them a hard time to produce appropriate supplementary materials specifically designed for online teaching platforms (Burgess & Sievertsen, 2020).”