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Analysis through machine learning on influence of covid-19 on higher education before, during and after pandemic
Data mining, a process of uncovering silent characteristics of big data is one of such techniques which have nowadays become more popular for treating massive volume of data set information. In the current study, we apply a machine learning analysis, one of the data mining techniques to classify grades obtained by students before, during and after Covid-19 pandemic. The results obtained permit us to have a sense of knowing if pandemic affected the grades of the students or helped the students to improve their average. The main objective of this study is to optimize monitoring techniques in a public university located in Colombia which will be very valuable to the government, educators, students, researchers and others involved in understanding seriousness of the problem that Covid-19 present in the education.
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