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 accessAbstract
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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Cites
A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions
Oliver, R. L. (1980) · Journal of Marketing Research · doi:10.1177/002224378001700405 · Cited by 14,494
The DeLone and McLean Model of Information Systems Success: A Ten-Year Update
(2003) · Journal of Management Information Systems · doi:10.1080/07421222.2003.11045748 · Cited by 11,791
A national customer satisfaction barometer: the Swedish experience
Fornell, C. (1992) · Journal of Marketing · doi:10.2307/1252129 · Cited by 5,641
Intransitivity of preferences.
Tversky, A. (1969) · Psychological Review · doi:10.1037/h0026750 · Cited by 2,188
Understanding e-learning continuance intention: An extension of the Technology Acceptance Model
Roca, J. C., Chiu, C.-M., & Martínez, F. J. (2006) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2006.01.003 · Cited by 1,399
What is Web 2.0? Ideas, technologies and implications for education
Anderson, P. F. (2007) · Cited by 1,180
Cloud computing for education: A new dawn?
Sultan, N. (2010) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2009.09.004 · Cited by 973
More on improving service quality measurement
Parasuraman, A., Berry, L. L., & Zeithaml, V. A. (1993) · Journal of Retailing · doi:10.1016/s0022-4359(05)80007-7 · Cited by 878
Foundations of the American Customer Satisfaction Index
Anderson, E. W., & Fornell, C. (2000) · Total Quality Management · doi:10.1080/09544120050135425 · Cited by 553
A theory of online learning as online participation
Hrastinski, S. (2009) · Computers & Education · doi:10.1016/j.compedu.2008.06.009 · Cited by 528
Cited by
Hong, J.-C., Lee, Y.-F., & Ye, J.-H. (2021) · Personality and Individual Differences · doi:10.1016/j.paid.2021.110673 · Cited by 283
Applications of artificial intelligence in battling against covid-19: A literature review
Tayarani N., M.-H. (2021) · Chaos, Solitons & Fractals · doi:10.1016/j.chaos.2020.110338 · Cited by 210
Cornide-Reyes, H., Riquelme, F., Monsalves, D., Noel, R., Cechinel, C., Villarroel, R., Ponce, F., & Munoz, R. (2020) · Sensors · doi:10.3390/s20216337 · Cited by 40
Rahman, A., Islam, M. S., Ahmed, N. A. M. F., & Islam, M. M. (2023) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2023.100646 · Cited by 19
(2021) · doi:10.2196/24027 · Cited by 7
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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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.