Research Paper on Covid19 and Global Analysis of Online Learning in Higher Education Using Machine Learning
This study aims to evaluate student perspectives of worldwide higher education institutions using the new digital culture produced by the COVID-19 epidemic, namely online learning. Based on student state residency, the study used quantitative survey methods and a sample size of 581 worldwide students from universities, polytechnics, colleges, and different departments of higher education. According to a research, students are disappointed with virtual learning undertaken by many higher education institutions during the COVID-19 lockdown. They do not want online learning to continue after the epidemic owing to inadequate internet infrastructure and a shortage of electricity. Global higher education students have minimal acceptance of online learning technologies, preferring the traditional classroom setting, according to the diffusion innovation theory. The conservative and slow to adopt new technology group. The research suggests universities engage students more interactively through texts and video examples. It will increase their online learning so they don't fall behind academically, and they'll spend more time on it until traditional learning returns. As soon as the pandemic is finished, global higher education administrators should revert to a traditional teaching and learning structure and revamp the internet and electrical system nationwide.