No abstract

COVID-19 had a major impact on education, substantially stimulating the need for digital remote education. From paperback books to PDFs, from physical classes to e-conferencing, and from various traditional mechanisms of information transmission to systems that are driven by artificial intelligence and use adaptive learning approaches, all of these had to be adopted by both teachers and students. This paper analyzes the use of an adaptive learning system before and during the COVID-19 pandemic from a statistical point of view on a set of data gathered in Romania during a pilot project. The main data inputs are the number of students that enrolled for a certain course, the percentage of students that successfully completed it, and information about their age group, location and main area of interest. Our study finds that the use of artificial intelligence has increased during the COVID-19 pandemic and, by analyzing the data obtained during the study, we managed to prove that artificial-intelligence-driven tools and systems have gained traction among all the parties involved in the educational process.

The COVID-19 pandemic has caused several disruptions in almost all day-to-day matters around the world. To keep things under control, ever since the beginning worldwide authorities-imposed restrictions in relation to physical activities and therefore, organizations were forced to rethink the way they carry out professional activities. Thus, most areas that were based on the physical interaction between people were severely impacted by these sets of measures. Unfortunately, a negative impact that the pandemic state has had over the fields that were based on physical work is that economic pressure has forced some of the entities to completely suspend their activity, leading to high rates of unemployment around the world, which also led to consistent financial efforts sustained by the government. To gain relevant conclusions, we analyzed several datasets that offer insights over all aspects of the labor market around the world mainly before and during the pandemic period. We also computed a correlation matrix based on economic sectors to compare the effects in the labor market for various industries. We analyzed the evolution of unemployment rate from Romania, commented on the breakdown of job loss by activity, interpreted the evolution of mobility based on Google data, explained the correlation between unemployment rate and the application of restrictive measures.