Svitlana Lutkovska

The ongoing war in Ukraine has posed unprecedented challenges to traditional education systems, disrupting learning and affecting education quality. As universities adapt to these challenges, the growing reliance on distance learning strategies becomes crucial for maintaining academic management processes. This paper investigates the role of distance learning tools in addressing wartime challenges and enhancing university academic management.
Utilizing a mixed-methods approach, the study combines quantitative data analysis of student performance with qualitative insights from educators and students affected by the war. The results prove the effectiveness of distance learning tools in maintaining education quality during the war while also addressing the unique challenges faced by universities in conflict areas.
The findings reveal that distance learning tools serve as a valuable resource for universities to mitigate the negative impact of the war on education quality as part of academic management processes. However, specific challenges such as developing digital competencies, ensuring access to technology, and designing effective distance learning materials must be addressed in war-related disruptions.
The quantitative analysis of student performance data highlights the potential of innovative distance learning tools in maintaining education quality during crises and wars. However, the efficiency of their use during the large-scale war in Ukraine has shown a decline and thus necessitates further research. Nevertheless, these insights provide valuable guidance for educators and academician managers to support students and educators during challenging times.

Small and medium-sized enterprises (SMEs) create more than half of the added value, providing about two-thirds of employment in most countries. However, they need more liquidity, access to credit resources, and significant outstanding loans. This study aims to identify the impact of interest rates on outstanding loans of enterprises on their structure as a way to prevent bankruptcy. The correlation-regression analysis used OECD statistical data for 2008‒2019 sampling individual countries; it showed an ambiguous situation between the interest rate and the share of outstanding loans of SMEs in the overall structure of outstanding loans. The paper verified constructed regression equations and estimated their parameters. The regression equations for Belgium, the Czech Republic, Estonia, and Latvia are statistically reliable. Thus, in Belgium and the Czech Republic, a negative relationship was recorded (r = –0.822; D = 0.675; r = –0.9274; D = 0.794; F-criterion > Ft, respectively), and in Estonia and Latvia – a positive one (r = 0.876; D = 0.767; F-criterion > F•Ft; r = 0.800; D = 0.641; F-criterion > Ft , respectively). Australia, Italy, Slovakia, and France practically do not have a corresponding relationship. The regression equations make it possible to estimate the change in the level of interest rate on the share of outstanding loans of enterprises in the overall structure of outstanding loans, make predictions of the corresponding performance indicator, and develop measures of restoring the solvency of enterprises as an essential task of preventing their bankruptcy.