https://repository.hneu.edu.ua/handle/123456789/24439 2026-06-06T09:22:12Z https://repository.hneu.edu.ua/handle/123456789/40380 Назва: Implementing mattering mindset in the learning environment Автори: Nikishyna A. Короткий огляд (реферат): The work is devoted to analyzing the importance of changing approaches to teaching in modern society, involving each student in the learning process and providing opportunities to experience the benefits of teamwork, a friendly attitude, and, most importantly, to appreciate students for who they are, regardless of their achievements. 2026-01-01T00:00:00Z https://repository.hneu.edu.ua/handle/123456789/40377 Назва: AI as Your Personal Assistant: Learning Languages Smarter, Not Harder Автори: Aliyev A.; Lysenkova T. Короткий огляд (реферат): In recent years, Artificial Intelligence (AI) has emerged as a transformative force in education, fundamentally reshaping how languages are learned and taught. AI-powered language assistants, particularly large language models (LLMs) such as ChatGPT and Claude, offer learners unprecedented access to personalized, on-demand language practice and instruction. These models understand natural language input and generate contextually appropriate responses, enabling dynamic interactions that simulate real-life communication. This paper explores the broad landscape of AI applications in language learning, analyzing their advantages, potential drawbacks, and practical usage. The authors also share personal experiences highlighting how AI tools can complement traditional language learning methods to enhance effectiveness and learner engagement. 2026-01-01T00:00:00Z https://repository.hneu.edu.ua/handle/123456789/40369 Назва: Digital Security in Chinese Universities Автори: Yang Man; Sladkykh I. A. Короткий огляд (реферат): The thesis examines current issues of digital security in Chinese higher education institutions within the context of the rapid digitalization of the educational environment. The study analyzes the main areas of digital technology implementation in Chinese universities, including blended learning, cloud-based research collaboration, student information systems, and online educational platforms. Key digital security threats are identified, such as technical vulnerabilities, human-related risks, cyberattacks, and unauthorized use of personal data. The paper outlines a comprehensive approach to information security that includes technical protection measures, regulatory policies, process control mechanisms, and the development of digital literacy among educational stakeholders. Particular attention is paid to a shared governance model of digital security involving university administration, faculty members, and students. Short-term and long-term measures aimed at creating a secure digital educational environment are proposed. It is concluded that effective digital security is a fundamental prerequisite for ensuring educational quality, protecting information resources, and supporting the sustainable development of modern universities. 2026-01-01T00:00:00Z https://repository.hneu.edu.ua/handle/123456789/40368 Назва: Responsible use of generative AI in scientific research Автори: Lixiao Kang; Sladkykh I. A. Короткий огляд (реферат): The article examines the opportunities, benefits, risks, and ethical aspects of using generative artificial intelligence in scientific research. The practical value of generative AI tools at different stages of research activity is analyzed, including literature search and review, data processing, academic writing, and academic integrity verification. Particular attention is paid to potential risks associated with violations of academic integrity principles, the generation of inaccurate information, superficial analysis, and challenges in academic translation. The study formulates key recommendations for the responsible use of generative AI in research, emphasizing transparency, protection of personal data and intellectual property, compliance with legal regulations, and the preservation of the researcher’s leading role in knowledge creation. Permissible, conditionally permissible, and unacceptable forms of generative AI use in master’s and doctoral research are identified. It is concluded that generative artificial intelligence can serve as an effective support tool for scientific research when applied critically, ethically, and responsibly. 2026-01-01T00:00:00Z