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4. From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and Turkey

Author

Pekdogan, Tugce, Udriștioiu, Mihaela Tinca, Yildizhan, Hasan, Ameen, Arman, Pekdogan, Tugce, Udriștioiu, Mihaela Tinca, Yildizhan, Hasan, and Ameen, Arman

Abstract

Air pollution significantly threatens human health and natural ecosystems and requires urgent attention from decision makers. The fight against air pollution begins with the rigorous monitoring of its levels, followed by intelligent statistical analysis and the application of advanced machine learning algorithms. To effectively reduce air pollution, decision makers must focus on reducing primary sources such as industrial plants and obsolete vehicles, as well as policies that encourage the adoption of clean energy sources. In this study, data analysis was performed for the first time to evaluate air pollution based on the SPSS program. Correlation coefficients between meteorological parameters and particulate matter concentrations (PM1, PM2.5, PM10) were calculated in two urban regions of Romania (Craiova and Drobeta-Turnu Severin) and Turkey (Adana). This study establishes strong relationships between PM concentrations and meteorological parameters with correlation coefficients ranging from −0.617 (between temperature and relative humidity) to 0.998 (between PMs). It shows negative correlations between temperature and particulate matter (−0.241 in Romania and −0.173 in Turkey) and the effects of humidity ranging from moderately positive correlations with PMs (up to 0.360 in Turkey), highlighting the valuable insights offered by independent PM sensor networks in assessing and improving air quality.

Published
2024
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5. Students' Well-Being and Academic Engagement: A Multivariate Analysis of the Influencing Factors.

Author

Puiu, Silvia, Udriștioiu, Mihaela Tinca, Petrișor, Iulian, Yılmaz, Sıdıka Ece, Pfefferová, Miriam Spodniaková, Raykova, Zhelyazka, Yildizhan, Hasan, and Marekova, Elisaveta

Subjects
SATISFACTION, QUESTIONNAIRES, UNIVERSITIES & colleges, MULTIVARIATE analysis, STRUCTURAL equation modeling, FAMILY roles, DESCRIPTIVE statistics, STUDENTS, LEISURE, ACADEMIC achievement, PSYCHOLOGICAL stress, STUDENT attitudes, SOCIAL support, CONFIDENCE intervals, WELL-being, VOCATIONAL guidance
Abstract

This paper aims to identify the factors that are positively or negatively impacting students' well-being and their academic engagement. We used partial least-squares structural equation modeling (PLS-SEM) using the data collected through a questionnaire from four countries: Romania, Turkey, Slovakia, and Bulgaria. The model includes seven factors that influence the well-being of students and indirectly their academic engagement: stressors in the students' lives; professors' support; social support from family and friends; the students' perceived satisfaction in their lives; engaging in activities during their leisure time; self-exploration regarding their careers; and environmental exploration regarding their careers. The results show that all factors, except for stressors and environmental exploration regarding their careers, positively influence the students' well-being and thus their academic engagement. These findings are useful for university professors and managers in better organizing activities to increase academic performance. [ABSTRACT FROM AUTHOR]

Published
2024
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6. The Behavioral Intention to Use Virtual Reality in Schools: A Technology Acceptance Model.

Author

Puiu, Silvia and Udriștioiu, Mihaela Tinca

Subjects
*TECHNOLOGICAL innovations, *TECHNOLOGY Acceptance Model, *STRUCTURAL equation modeling, *VIRTUAL reality, *LEAST squares
Abstract

This paper presents the impact of using virtual reality (VR) in education and focuses on the main factors that affect the behavioral intention of using this new technology for the benefit of both professors and students. As part of our research methodology, we conducted a survey based on the Technology Acceptance Model and used partial least squares structural equation modelling. The results show that the intention to use VR technology in education is influenced by both usage satisfaction and the task–technology fit. The system quality of the VR technology proved to be important in influencing both the task–technology fit and perceived usefulness. The findings are useful for professors considering the adoption of new technologies that might improve the efficiency of learning for their students. Additionally, managers of educational institutions can use these insights to direct investments towards this type of innovation, which appeals to newer generations. [ABSTRACT FROM AUTHOR]

Published
2024
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