Nataliia Tkalenko

During the full-scale war, educational institutions of Ukraine were at the epicenter of hostilities and suffered from attacks and bombing by the russian army: many schools, colleges, and universities were destroyed or damaged, and tens of thousands of students and teachers became refugees or forced displaced persons, lost their property and housing. Chernihiv Polytechnic National University (CPNU), located in the northern border region of Ukraine, was also significantly affected.
This study aims to systematize the features of the functioning of CPNU under siege, bombing, and shelling. An analytical method was used to assess statistical reports available in open access on the official websites of CPNU and the Ministry of Education and Science of Ukraine. The paper identified that during active hostilities, 25% of the university’s infrastructure was destroyed by shelling and bombing; 37 teachers and researchers emigrated; about 4% of students stopped their studies. Currently, CPNU suffers from loss of human capital, physical destruction of educational and research infrastructures, lack of R&D financing, increased cyber security threats, and violation of the educational process. In response to military challenges, the university management rethinks and forms a new vision for further development based on sustainability principles to recover educational and research infrastructures, promote human capital development, and modernize the learning environment. The new vision of CPNU integrates “7R” principle – seven key pillars covering different directions of its operation (teaching, research, innovation, international activity, etc.).

The increasing integration of Artificial Intelligence (AI) into education requires studying the motives for its use among students. This study aims to identify the key motivations for economics students to use AI and compare these motivations by grade level and gender. The study examines satisfaction with the use of AI and analyzes the number of AI tools used.

An anonymous empirical study was conducted among 264 students from the Faculty of Economics at Taras Shevchenko National University of Kyiv, Ukraine. Data analysis included descriptive statistical methods, non-parametric statistical methods, and exploratory factor analysis.

The study found that students’ main motivations for using AI are the automation of routine tasks (34.2%) and the need to save time (21.5%), while 18.7% use AI to compensate for lack of experience. Among Bachelor’s students, motivations such as automating routine tasks and saving time increased from 53% to 58% over the course of their studies, while lack of experience decreased from 22% to 15%. In contrast, Master’s students showed a decrease in routine automation (from 36% to 28%) but an increase in the need to compensate for lack of experience (from 15% to 28%) and to save time (from 18% to 25%). In terms of gender, men are more likely to use AI for learning and personal development, while women are slightly more likely to use AI for work. More than 38% of respondents say they need to use at least 2 AIs to achieve their goals.

Acknowledgment
This publication is based upon work from 24-PKVV-UM-002, ‘Strengthening the Resilience of Universities: Czech-Ukrainian Partnership for Digital Education, Research Cooperation, and Diversity Management,’ supported by the Czech Development Agency and the Ministry of Foreign Affairs under the initiative ‘Capacity Building of Public Universities in Ukraine 2024.’