Introduction. The relevance stems from the need to further expand financial literacy teaching practices at all levels of general education, where teachers' financial behavior and trust are significant socio-pedagogical factors. The aim of this article is to study the characteristics of trust in financial institutions among young teachers at the regional level and to develop recommendations for improving the effectiveness of financial literacy education in Russia. Materials and methods. Drawing on Pierre Bourdieu's constructivist methodology, the authors examined trust as an internal component of the practices of agents involved in current financial situations. The study was conducted using an online questionnaire and included 225 young teachers from rural and urban areas. The results were analyzed using frequency distributions of responses and the creation of contingency tables. Results. The study revealed the persistence of conservative financial behavior among both urban and rural young teachers, as well as a bank-centric approach to institutional trust. The key role of banks as an object of trust was noted by 64.6% of urban and 57.1% of rural teachers. Basic reliability criteria were emphasized by 60.4% of urban and 71.4% of rural teachers. A high level of sensitivity to the security of personal financial data was recorded, as well as a correlation between trust and experience with financial institutions. Young teachers in rural areas demonstrated a stronger focus on reliability, government support, and insurance companies. 57.1% of rural teachers prioritized government support, while in urban areas this figure did not exceed 37.5%. Young teachers from urban areas were more open to institutional differentiation. Self-assessment of financial literacy showed a high demand for further training among both urban (68.8%) and rural (71.4%) young teachers, which allows us to focus on the work of teachers with their own financial experience, level of institutional trust, and practices of safe financial behavior. KEYWORDS Conclusion. In the context of increasing the effectiveness of teaching the basics of financial literacy, it is recommended to expand the legal basis for the program of state co-financing of teachers' investments, introduce gamification elements and demo versions of brokerage applications as part of teaching financial literacy, as well as corporate brokerage and insurance programs.
Introduction. Self-efficacy significantly influences the career maturity of students majoring in airline service. Furthermore, career maturity exerts a positive effect on their career preparation behavior. Notably, career values play a critical role in moderating the mediating path of career maturity between self-efficacy and career preparation behavior. This study empirically verified the moderated mediation effect of career values, demonstrating that the mediating influence of career maturity within the link between self-efficacy and career preparation behavior varies depending on the level of career values. Methods. The participants in this study consisted of 254 students majoring in airline service in an university. The sample included freshmen (33.1%), sophomores (24.3.0%), juniors (21.3%), and seniors (21.3%). Data were analyzed using SPSS Win version 21.0 to perform frequency analyses, reliability testing, and correlation analysis. For the moderated mediation analysis, Model 14 of the PROCESS macro version 4.3 was employed as the primary statistical method. KEYWORDS Results. First, self-efficacy exerted a significant positive influence on both career maturity (β = .210, p < .001) and career preparation behavior (β = .193, p < .01). Career maturity was also found to have a significant positive impact on career preparation behavior (β = 1.277, p < .001). Notably, the interaction between career maturity and career values yielded a significant effect on career preparation behavior (β= -.221, p < .05), suggesting a moderation effect. Second, the conditional indirect effects of self-efficacy on career preparation behavior via career maturity were statistically significant across all levels—low, middle, and high—of career values (p < .001). Consequently, these results empirically support the moderated mediation effect of career values within the hypothesized model. Conclusions. This study empirically confirmed that self-efficacy exerts a significant positive influence on career preparation behavior, specifically through the mediating mechanism of career maturity. These findings underscore the necessity of fostering and reinforcing students' career values as a strategic approach to enhancing both career maturity and career preparation behavior among airline service majors.
Introduction. Global higher education research increasingly underscores the necessity of comprehending the mechanisms that enable effective transfers to university. The aim of study is to examines learning indicators among Vietnamese freshmen, specifically analyzing demographic and how teacher confirmation impacts outcomes across different levels of self-esteem. Methods. A descriptive research design was employed, involving a sample of 418 first-year students within their first three months at Tra Vinh University (Vietnam). Data collection utilized validated instruments to assess learning indicators, teacher confirmation, self-esteem, and demographic variables. Analyses included independent t-tests, one-way ANOVA, and simple regression analysis. Results. Significant differences in learning indicators were observed across demographic variables, including ethnicity, classroom leadership roles, and high school academic performance (p < .05). No significant differences emerged between male and female students (p > .05). Teacher confirmation significantly predicted learning indicators for freshmen with low (R2 = .210, p < .01) and moderate (R2 = .241, p < .01) self-esteem, but not for those with high self esteem (R2 = .109, p > .05). KEYWORDS Discussion. Khmer ethnic minority students achieved significantly higher learning indicator scores than their Kinh (majority) peers, indicating a positive trend. Engagement in leadership activities fosters essential skills relevant to learning indicators. Furthermore, students with low or moderate self-esteem are more responsive to affirming instructor behaviors, which contributes to improved learning indicators. freshmen, learning indicators, self-esteem, teacher confirmation, Vietnam Conclusion. Learning indicators of Vietnamese freshmen are closely linked to student demographics, and teacher confirmation contributes to improvements in learning indicators across self-esteem levels. The results emphasize the role of teacher confirmation in fostering learning engagement among freshmen with lower self-esteem as a strategy to support students’ academic adjustment during the initial phase of their university experience.
Introduction. The quality of higher education remains a critical concern for policymakers and institutions globally, yet empirical cross-national research, particularly in post-Soviet contexts, remains scarce. Existing studies often rely on single-institution data, retrospective methodologies, and traditional input-based indicators, while neglecting emergent determinants such as institutional culture, leadership, and student resilience. This study addresses these gaps by investigating two research questions: (1) Do quality indicators differ significantly depending on the specific characteristics of the educational institution? and (2) Which quality constructs have predictive power in the relationship between institutional culture and student satisfaction? Research methods. A cross-sectional survey design was employed, collecting data from 719 students across four diverse universities in Russia and Uzbekistan: a large Russian federal university (KFU), its branch in Uzbekistan (KFUJ), a private Uzbek university (REU), and a national classical Uzbek university (NUU). Eight latent constructs (institutional culture, teaching effectiveness, academic staff quality, digital competency, educational resources, leadership and policy, academic resilience, and student satisfaction) were measured using 35 items on a 5-point Likert scale. Data were analyzed using confirmatory factor analysis (CFA), one-way ANOVA, and partial least squares structural equation modeling (PLS-SEM) with 500 bootstrap resamples. KEYWORDS Results. The measurement model demonstrated excellent fit (CFI=0.999, RMSEA=0.022). Statistically significant inter-institutional differences were found across all eight constructs (p<0.05), with NUU and KFU students reporting the highest overall quality scores and KFUJ the lowest. Leadership and policy emerged as the strongest predictor of student satisfaction (β=0.442, f2=0.648, p<0.001), followed by teaching effectiveness (β=0.202), academic staff quality (β=0.141), and academic resilience (β=0.138). Educational resources and digital competency showed only bivariate correlations with satisfaction but lost significance in the multivariate model due to multicollinearity with leadership. Conclusion. The study provides the first validated cross-national empirical comparison of an eight-variable quality assessment model in post-Soviet higher education. Leadership and policy-not traditional inputs like resources-constitute the most powerful driver of student satisfaction. These findings challenge prevailing quality models that emphasize teaching inputs and physical infrastructure while downplaying governance and student adaptive capacities. Practical recommendations include investing in evidence-based governance, faculty development in active pedagogy, structured mentorship programs to build academic resilience, and strategic quality assurance reforms aligned with ESG 2015 standards. Future longitudinal and multi-group SEM research is needed to establish causality and test measurement invariance across broader institutional typologies
Introduction. The rapid implementation of generative artificial intelligence (AI) in higher education has intensified the problem of maintaining learning quality under conditions of technological mediation of the educational process. AI systems expand students’ access to information and support knowledge construction; however, their use is accompanied by risks of reduced cognitive engagement, overreliance on automated responses, and a shift from understanding to task completion. The aim of the study was to develop a conceptual model explaining the role of epistemic regulation in maintaining learning quality in hybrid human-AI systems. Materials and Methods. The study was based on an integrative analysis of literature and theoretical synthesis. The analysis covered research on generative AI in education, self-regulated learning, metacognition, distributed cognition, hybrid intelligence, and human-AI interaction. At the first stage, approaches to understanding the influence of generative AI on learning quality, the hybridization of learning activity, and the distribution of cognitive functions between the student and AI were compared. At the second stage, theoretical synthesis was conducted, which made it possible to identify epistemic regulation as a mechanism for maintaining learning quality. KEYWORDS Results. The integrative analysis showed that generative AI transforms learning not only as a means of access to information, but also as a participant in the production, reformulation, and structuring of educational content. Under these conditions, educational activity acquires hybrid and distributed characteristics, while classical models of self-regulated learning and metacognition prove insufficient for describing control over knowledge emerging in interaction with AI. A conceptual model is proposed in which generative AI creates both educational opportunities and epistemic risks, while epistemic regulation ensures control over the status of knowledge. Its functions include evaluation, verification, comparison, trust calibration, interaction structuring, and responsibility for the final position. The model distinguishes epistemic regulation from metacognitive regulation and describes six levels of its development. Conclusion. Learning quality in hybrid human-AI educational systems depends not on the mere use of generative AI, but on students’ ability to preserve epistemic control over distributed knowledge construction. The proposed model provides a basis for designing learning tasks that support verification, critical evaluation, reflection, and responsible authorship in AI-mediated learning.
