AI Article Synopsis
- The COVID-19 pandemic shifted education from traditional in-person teaching to online platforms, affecting education quality.
- A study in China focused on user satisfaction with online education using surveys and web analysis, resulting in a customer satisfaction index and a BP neural network model for forecasting.
- Findings revealed that personal factors don’t significantly affect satisfaction, but platform availability is crucial, leading to recommendations for enhancing online education during the pandemic.
Article 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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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7551570 | PMC |
| http://dx.doi.org/10.3390/healthcare8030200 | DOI Listing |
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