Gaidelys, V., Čiutienė, R., & Cibulskas, G. (2023). Distance Learning Exit Economic Model. Preprints. https://doi.org/10.20944/preprints202308.1767.v1
Chicago/Turabian Style
Gaidelys, V., Rūta Čiutienė and Gintautas Cibulskas. 2023 "Distance Learning Exit Economic Model" Preprints. https://doi.org/10.20944/preprints202308.1767.v1
Abstract
At the beginning of 2020, with the onset of the pandemic, the traditional learning environment for learners drastically changed globally. Since then, most students/teachers have started and practiced distance and virtual learning/teaching. Thus, a technological breakthrough in virtual learning has followed. In connection with this, many countries worldwide have commenced allocating additional financing and funds for educational institutions' technological improvement and development. The long-term stay in distance learning has revealed and highlighted new problems students face: their knowledge level has decreased, they lack socialization skills, and they face psychological and physical health problems. Due to this negative impact on students, a need to research and evaluate how much the EU countries allocated to solve the distance learning-caused problems and what programs or models they prepared has emerged and encouraged further studies. The research has found that many countries increased their allocations very minimally, e.g., 0.0.1%, but some increased their available budgets to 32%. Notably, most countries did not separate distance learning exit funding from distance learning preparation funding. Based on the problems the countries saw, only a few states identified withdrawal from distance learning as a problem. Considering this, we set ourselves the goal to evaluate exit models from distance learning and allocated funding amounts.
The following objectives were planned to achieve the goal:
· to evaluate the global practice of exit from distance learning;
· to determine the scope of funding for pandemic management;
· to evaluate the amounts of funding allocated to manage pandemic-caused consequences and the GDP ratio.
Research methods: mathematical-statistical analysis, empirical analysis, and analysis of scientific literature.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
