Evaluating the impact of COVID-19 on Educational system: Challenges, Modifications, and Future Directives

Abstract

The World Health Organization proclaimed the COVID-19 pandemic in December 2019, and it has severely disrupted many industries globally, including education. In this study, it is shown that how the outbreak of COVID-19 had affected education system along with the others areas of life. Indefinite holidays molded the system into a new form that was new or unacceptable to the majority. Especially, how the technical difficulties encountered in online classes affected the students and teachers. In this research, we utilized six supervised machine learning techniques to forecast the impact on the annual system of education by using qualitative data obtained from a sample of 1280 in Punjab, rural and urban areas. The Random Forest algorithm had the maximum accuracy and execution time efficiency both in the presence and absence of Principal Component Analysis (PCA). This study also identified the association between educational disruption and other categorical factors such as course completion, delivery mode, technology use, and disparities.