https://opendata.uni-halle.de//handle/123456789/2 Sat, 11 Apr 2026 05:46:53 GMT 2026-04-11T05:46:53Z http://opendata.uni-halle.de:80/retrieve/d42e1469-6e68-42e4-9e23-9cfcd1ffe70e/zeitschriften3.jpg https://opendata.uni-halle.de//handle/123456789/2 https://opendata.uni-halle.de//handle/1981185920/124819 Title: Life satisfaction in times of crisis : the role of social class and resources in Germany Author(s): Hajji, Rahim; Peters, Meggy Abstract: This study examines life satisfaction in Germany and its association with perceived crisis-related stress, subjectively assessed social class, and social and psychological resources. It further explores which resources are associated with an attenuation of the negative relationship between low social class and life satisfaction. Thu, 19 Mar 2026 00:00:00 GMT https://opendata.uni-halle.de//handle/1981185920/124819 2026-03-19T00:00:00Z https://opendata.uni-halle.de//handle/1981185920/124818 Title: AI in Education : Revolutionizing Learning and Personalized Instruction Author(s): Jumaev, Giyosjon Abstract: Artificial Intelligence (AI) is quickly reshaping industries globally, and the field of education is particularly poised for transformative innovation. Conventional instructional approaches frequently find it difficult to meet the varied needs and speeds of students, often resulting in deficiencies in both understanding and involvement. In response to these shortcomings, technology leveraging AI has been deployed to enrich educational experiences and boost learning achievements. The purpose of this research is to investigate how AI is fundamentally changing education, specifically concentrating on customized learning, smart tutoring systems, and improved efficiency in administrative tasks. The study adopted a literature review approach, analyzing current academic studies, case analyses, and AI implementations across both compulsory (K-12) and post-secondary education sectors. The results show that AI substantially raises student performance by providing customized teaching, adaptive evaluations, and immediate feedback via Intelligent Tutoring Systems (ITS). Furthermore, predictive data analysis enables instructors to proactively identify vulnerable students, while automation solutions alleviate administrative pressures, including tracking attendance and grading. AI-driven accessibility and language translation tools also promote an inclusive environment by assisting students from varied linguistic and cultural origins. Ultimately, AI exhibits considerable promise for enhancing individualized teaching, boosting educational effectiveness, and broadening access to high-quality learning. Nevertheless, critical issues like ethical dilemmas, data security, and the potential for decreased human interaction in educational settings require careful consideration. In summary, AI is a powerful resource that can supplement existing teaching methods, guiding the development of an educational system that is more adaptive, accessible, and successful. Mon, 01 Dec 2025 00:00:00 GMT https://opendata.uni-halle.de//handle/1981185920/124818 2025-12-01T00:00:00Z https://opendata.uni-halle.de//handle/1981185920/124817 Title: Balancing Career and Academic Pursuits of Young Professionals for Sustainable Career and Education Development Author(s): Iglesia, Anna Pearl B. Abstract: Young professionals aged 24 to 29 often struggle to juggle the different needs of their career and academic pursuits. This dual responsibility builds overlapping pressures that can affect their personal well-being, their academic achievement, and professional development. In this research, the authors utilized the SEM analysis to investigate the major drivers that affect this balance. An online survey questionnaire was employed to collect data among fifty participants on indicators such as balanced engagement, academic performance, career achievement, and psychological and emotional stressors. The result of the study emphasizes the importance of academic performance, professional advancement, and job contentment; moreover too, having structured routines, a good support system, well-being, and stress resilience are all very important. The findings of this study gave valuable insights to young professionals, employers, and educational institutions in creating an enabling environment for career growth and lifelong learning. The SEM findings further provide a basis for future studies aimed at enhancing support mechanisms for sustainable academic and professional growth that are aligned with broader global sustainability efforts. Mon, 01 Dec 2025 00:00:00 GMT https://opendata.uni-halle.de//handle/1981185920/124817 2025-12-01T00:00:00Z https://opendata.uni-halle.de//handle/1981185920/124816 Title: Innovation-Driven Analysis of Social Project Mechanisms for Renewable Energy Transition Author(s): Zikrillayev, Nurullo Abstract: This study focuses on the public perception and social acceptance of renewable energy projects, as well as on the analysis of mechanisms for stakeholder and community engagement. The article examines the main factors influencing public support for renewable energy initiatives, including levels of awareness, trust in project developers, environmental concerns, and cultural contexts. A comprehensive analysis of survey data, media content, and case studies of both successful and unsuccessful projects was conducted. Based on these data, models were developed to explain the interrelations among key factors, and practical recommendations were formulated to enhance community support for renewable energy initiatives. Particular attention is given to the role of communication, transparency, and community participation at all stages of project implementation. Public perception and social acceptance are interpreted as multidimensional phenomena encompassing psychological, cultural, economic, and political dimensions. Theoretical frameworks applied in this research include the diffusion of innovations theory, social capital model, trust theory, and risk perception models. The analysis demonstrates that active stakeholder involvement and transparent communication substantially increase public trust and support for renewable energy initiatives. Furthermore, the use of advanced methods of social media analytics and network analysis enables the identification of key sources of both negative and positive sentiment, which is essential for designing effective public opinion management strategies. The results confirm the need for a systemic and interdisciplinary approach to accelerate the transition toward sustainable energy systems. The study provides practical recommendations for policymakers, businesses, and research institutions aimed at enhancing social support for renewable energy projects and reducing resistance from local communities. Mon, 01 Dec 2025 00:00:00 GMT https://opendata.uni-halle.de//handle/1981185920/124816 2025-12-01T00:00:00Z