Acceleration of Digital Education in Pakistan during pandemic (COVID-19): A case study based on ML

This research examines the rapid evolution of DE in Pakistan, specifically during the COVID-19 pandemic. Study shows that consistent allocation of resources to enhance digital literacy would significantly enhance the quality of the learning process. The research uses statistical analysis and machine learning algorithms to explore DE’s impact, challenges, and prospects in education. A quantitative approach is a case study methodology involving a questionnaire survey of 300 students across diverse Pakistani educational institutions. Ethical considerations ensure privacy protection by excluding intrusive queries. The data collected includes categorical and ordinal variables, covering aspects like gender, institute type, preferred platforms, satisfaction levels, and difficulty perceptions. The study uncovers insights into the acceleration of DE, revealing student preferences and pandemic-related experiences. Challenges posed by technology and remote learning are highlighted, with poor internet connectivity emerging as a significant hurdle. This research informs policy decisions for crisis-driven education reforms, contributing to improved remote learning quality. Analyzing the accuracy of machine learning algorithms provides predictions of DE trends. The study fosters a comprehensive understanding of Pakistan’s DE landscape, fostering future enhancements and innovations in remote learning strategies.