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Predicting student satisfaction of emergency remote learning in higher education during COVID-19 using machine learning techniques
2021
PLoS ONE
Despite the wide adoption of emergency remote learning (ERL) in higher education during the COVID-19 pandemic, there is insufficient understanding of influencing factors predicting student satisfaction for this novel learning environment in crisis. The present study investigated important predictors in determining the satisfaction of undergraduate students (N = 425) from multiple departments in using ERL at a self-funded university in Hong Kong while Moodle and Microsoft Team are the key
doi:10.1371/journal.pone.0249423
pmid:33798204
fatcat:ux3ggargh5acbkxej2mlm7bvue