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Satisfaction of Online Education in Covid-19 Pandemic Situation Prediction With Data Mining in Bangladesh

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dc.contributor.author Poushy, Lamisha Haque
dc.contributor.author Bhuiyan, Salauddin Ahmed
dc.date.accessioned 2021-07-13T05:30:24Z
dc.date.available 2021-07-13T05:30:24Z
dc.date.issued 2021-01-31
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/5904
dc.description.abstract Our research paper “SATISFACTION OF ONLINE EDUCATION IN COVID-19 PANDEMIC SITUATION PREDICTION WITH DATA MINING IN BANGLADESH” focus on education based online learning platform. Online education is becoming more popular all over the world because of COVID-19 pandemic situation. Counted how effective it will play by conducting a survey of 799 students from different academic institutions, schools, colleges and universities on the quality of online education in COVID-19 pandemic situations. Influence online measurement and overall satisfaction with online learning. We used an online google form as the method of data collection for this survey. This paper perused the prediction of online education through data mining and machine learning approaches in an online program. The data was collected through online questionnaires. To predict the satisfaction rate of online education we use Linear Regression algorithm and Logistic Regression model. The main goal of this study is to see student are satisfied with starting the new online class teaching system, whether it will have an ambivalent effect on students in the future. en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Data mining en_US
dc.subject Distance education students en_US
dc.subject Online education en_US
dc.title Satisfaction of Online Education in Covid-19 Pandemic Situation Prediction With Data Mining in Bangladesh en_US
dc.type Other en_US


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