Issue #2 (Volume 10 2026)

Type of the article: Research Article

The study aims to analyze institutional policies governing the use of generative artificial intelligence (GenAI) in Ukrainian universities and assess their regulatory maturity. Drawing on the authors’ Taxonomy of Institutional AI Policy Maturity (AI-PMT), which comprises twelve analytical dimensions, the study examines a sample of 23 publicly available institutional policy documents adopted between 2023 and 2025. The analysis combines qualitative and quantitative approaches. A directed content analysis was used to assign ordinal scores (0-2) across twelve dimensions, enabling the construction of a cumulative maturity index (0-24) for each institution. The results reveal an uneven distribution of regulatory development, with more elaborated provisions related to teaching and learning, and comparatively less developed components addressing research practices, data governance, and infrastructural support. To synthesize these patterns, an analytical typology of institutions was developed based on cumulative maturity scores, identifying three broad groups that differ in the degree of regulatory completeness and procedural specification. In parallel, thematic analysis of policy content identified recurring patterns, including the normalization of AI use in education, the emphasis on transparency and disclosure, the prevalence of precautionary approaches to data and confidentiality, and several contested provisions. Comparison with international policy frameworks suggests that Ukrainian universities broadly align with global normative trends in principles, but exhibit limited operationalization of governance mechanisms and research-related provisions. The findings highlight structural imbalances in institutional AI governance and underscore the need to further develop research-oriented regulation, institutional support mechanisms, and coordinated policy approaches.

Acknowledgment
We thank the Armed Forces of Ukraine for providing security for this work, which was made possible only thanks to the resilience and bravery of the Ukrainian Army.

Type of the article: Research Article

Lecturers’ financial well-being is an important factor influencing work motivation, teaching quality, and professional commitment in implementing the Tri Dharma of Higher Education. This study is motivated by the financial challenges faced by lecturers at private higher education institutions in underdeveloped, frontier, and outermost regions, particularly in Southwest Papua, Indonesia, which are characterized by limited income and high financial vulnerability. The study aims to examine the effects of financial stress, money attitude, financial risk tolerance, and financial socialization on financial well-being, with financial literacy as a mediating variable. Using a quantitative explanatory design, data were collected from 230 certified lecturers across eight private higher education institutions in Southwest Papua through a census approach within a defined sub-population. Data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM). The findings show that money attitude has a positive and significant direct effect on financial well-being and financial literacy. Financial stress and financial risk tolerance significantly influence financial literacy but have no direct effect on financial well-being, while financial socialization shows no significant effect. Financial literacy significantly mediates the relationships between financial stress, money attitude, and financial risk tolerance toward financial well-being. The model explains 39.7% of financial well-being and 34.8% of financial literacy variance. These results highlight the importance of structured financial literacy programs for lecturers in underdeveloped, frontier, and outermost regions.

Type of the article: Research Article

Despite the rapid digital transformation in higher education, empirical evidence explaining how digital entrepreneurship learning contributes to human capital formation, entrepreneurial universities, and economic growth remains limited. This study investigates the role of Digital Canvas Learning (DCL), a digital-based entrepreneurship learning approach that enables students to design and test business models using an interactive Business Model Canvas. The study employs a structured survey conducted in 2024 involving 206 undergraduate and graduate students enrolled in entrepreneurship programs at universities within Higher Education Service Institutions Regions III and IX, Indonesia. The respondents were selected because they were actively engaged in entrepreneurship education, making the sample relevant for examining the outcomes of digital entrepreneurship learning. The data were analyzed using Partial Least Squares – Structural Equation Modeling (PLS-SEM). The results show that DCL has a strong and significant effect on Human Resource Development (β = 0.752; p < 0.001) and Economic Growth (β = 0.690; p < 0.001), and a significant influence on University Entrepreneurship (β = 0.337; p < 0.001). Furthermore, Human Resource Development significantly affects University Entrepreneurship (β = 0.527; p < 0.001) and Economic Growth (β = 0.273; p < 0.001), while University Entrepreneurship strongly contributes to Economic Growth (β = 0.662; p < 0.001). The structural model explains 79.4% of the variance in Economic Growth, indicating substantial explanatory power. These findings demonstrate that Digital Canvas Learning not only enhances students’ entrepreneurial competencies but also strengthens human capital development, supports entrepreneurial universities, and contributes to sustainable economic growth.

Acknowledgment
We would like to express our deepest gratitude to the Education Fund Management Institute (LPDP) of the Ministry of Finance of the Republic of Indonesia and Universitas Terbuka for the administrative and funding support and the opportunities given to the author.