Online education has become a vital part of a student’s life since the emergence of the COVID-19 pandemic. Although the trend of online education has been there for a long time, but, it received a greater attention after the emergence of the global pandemic. Education like any other daily activity can’t be off for a very long time. This led to the rise of online education as a replacement of in-person classes in the schools, colleges and universities. Even now when the pandemic seems to be almost over, many educational institutions still provide online learning besides in-person classes. Hence, it is very important to ensure the quality of online education and analyze how useful or impactful it is for the students. It needs to be studied how to constantly improve the quality of the online classes and identify what are the problems that are faced by the students during the online classes. These identified problems will help in formulating a better online education system that is more acceptable among the mass students. In this project, I have used common machine learning models to develop a classifier that can predict if the students are satisfied or not satisfied with the current online education system. For details, please read the Report.
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E-learning, Machine Learning models in R
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