https://repository.hneu.edu.ua/handle/123456789/24439 Tue, 09 Jun 2026 20:35:37 GMT 2026-06-09T20:35:37Z https://repository.hneu.edu.ua/handle/123456789/40598 Назва: An overview of the evolution of artificial intelligence and its role in higher education Автори: Dubtsova O. V.; Makhatilov A. I. Короткий огляд (реферат): The article provides a comprehensive overview of the evolution of artificial intelligence and analyses its role in the development of modern higher education, offering a structured synthesis of its evolutionary trajectory and highlighting its growing significance as a transformative factor in contemporary higher education systems, contributing to the enhancement of learning processes and educational outcomes. Artificial intelligence is understood as a field of computer science that develops systems capable of independently performing tasks traditionally associated with human intelligence through the acquisition, analysis and processing of information from the environment. Artificial intelligence has undergone continuous development, attracting increasing scientific interest and evolving from early theoretical concepts to advanced technological systems. The article examines the evolution of artificial intelligence by identifying five key stages of its development, ranging from symbolic systems and expert programs to machine learning, deep neural networks and transformer-based architectures. Each stage is characterized by the emergence of new approaches and methodologies that have contributed to the formation of modern artificial intelligence. Particular attention is given to its role in higher education, where artificial intelligence contributes to the transformation of educational practices and the development of adaptive and accessible learning environments. The study emphasizes that contemporary advancements in higher education are increasingly associated with the integration of artificial intelligence into the educational practices of higher education institutions. In this context, artificial intelligence enhances the efficiency and flexibility of the educational process, supports personalized learning and expands access to educational resources. As a result, artificial intelligence is becoming an essential component of the modern educational landscape. Thu, 01 Jan 2026 00:00:00 GMT https://repository.hneu.edu.ua/handle/123456789/40598 2026-01-01T00:00:00Z https://repository.hneu.edu.ua/handle/123456789/40576 Назва: Innovative-Oriented English Language Teaching for Future Teachers Автори: Lazarenko T. Короткий огляд (реферат): The article is devoted to the issue of innovation-oriented English language teaching for future teachers in the context of the digitalization and globalization of education. It examines modern pedagogical approaches, including Project-Based Learning, the Flipped Classroom, Blended Learning, and gamification, as well as the role of digital technologies in developing professional, communicative, digital, and intercultural competences. The study highlights the importance of fostering students’ critical thinking, creativity, autonomy, and self-education skills. The main challenges of implementing innovative methods and the ways to overcome them are also outlined. Thu, 01 Jan 2026 00:00:00 GMT https://repository.hneu.edu.ua/handle/123456789/40576 2026-01-01T00:00:00Z https://repository.hneu.edu.ua/handle/123456789/40516 Назва: Applying generative artificial intelligence in higher education: risks, technological limitations, and the distribution of responsibility Автори: Kovalenko O. Y. Короткий огляд (реферат): The article examines the risks, technological limitations, and responsibility models associated with the use of generative artificial intelligence in higher education. The relevance of the topic is determined by the rapid integration of generative AI into teaching, learning, academic writing, assessment, educational content creation, and research support, while the pace of its adoption significantly exceeds the development of coherent pedagogical, ethical, legal, and institutional frameworks. Recent international and national documents increasingly emphasise the need for human oversight, transparency, accountability, academic integrity, protection of human rights, data privacy, and a risk-based approach to the use of AI in education. Therefore, the issue should not be reduced to isolated concerns such as plagiarism or technological convenience. Instead, it requires an integrated analytical model combining risk classification, identification of technological limitations, and a clear distribution of responsibility among the main actors in the educational process. The purpose of the article is to provide a theoretical substantiation of the risks and limitations of generative artificial intelligence in higher education and to develop a model of distributed responsibility for its use among participants in the educational process. The study is based on a set of theoretical methods, including the analysis of scholarly literature, international and national policy and regulatory documents, comparative legal analysis, classification, systematisation, generalisation, and modelling. The study identifies and systematises the main groups of risks related to the use of generative AI in higher education: academic, cognitive, informational, ethical, legal, and organisational risks. It is argued that these risks are interconnected and cannot be reduced solely to issues of academic misconduct. The article separately distinguishes risks from the technological limitations of generative AI systems. The latter include the probabilistic nature of text generation, hallucinations, dependence of output quality on prompt quality, opacity of response formation mechanisms, instability and variability of outputs, and limited contextual and value sensitivity. It is demonstrated that ignoring these limitations often leads to an overestimation of generative AI as a reliable source of academic knowledge rather than a supportive instrument requiring human verification and interpretative control. The article proposes an authorial model of distributed responsibility based on three interrelated levels: the student, the teacher, and the higher education institution. At the individual level, the student is responsible for academic integrity, fact-checking, critical verification, and the proper use of AI tools. At the pedagogical level, the teacher is responsible for assignment design, communicating the acceptable boundaries of AI use, and applying assessment methods that verify understanding rather than merely the ability to generate text. At the institutional level, the higher education institution is responsible for internal policies, methodological guidance, procedural clarity, and the protection of the rights of all participants in the educational process. The study concludes that a productive model for regulating generative AI in higher education is neither total prohibition nor unrestricted use, but rather an institutionally regulated, human-centred, and accountable approach grounded in distributed responsibility and human oversight. Wed, 01 Jan 2025 00:00:00 GMT https://repository.hneu.edu.ua/handle/123456789/40516 2025-01-01T00:00:00Z https://repository.hneu.edu.ua/handle/123456789/40507 Назва: The role and significance of e-learning methods in teaching the discipline “foreign language (english)” in economic hei Автори: Ved Т.; Lyutviyeva Ya. Короткий огляд (реферат): This article examines the role and significance of e-learning methods in teaching the course “Foreign Language (English)” at higher education institutions specializing in economics. This study is relevant due to digitalization in education, globalization, and the increasing demand for professional competence in foreign languages among future specialists. The scientific novelty lies in clarifying the essence of e-learning and substantiating its role in developing students' professional competence in foreign languages at economic higher education institutions. The article aims to support the effectiveness of e-learning and determine its impact on student training quality. The study used theoretical methods of analysis, generalization, and systematization of scientific sources. It also used comparative and descriptive-analytical methods. The concepts “e-learning,” “distance learning,” “virtual learning,” and “online learning” were examined, and their interrelationships identified. The main e-learning tools analyzed include online platforms, interactive services, and multimedia resources that help develop students’ language skills. Using digital technologies increases learning motivation, ensures flexibility in the educational process, and promotes personalized learning. However, the study also identifies challenges. These include insufficient interpersonal interaction and a need to adapt teaching materials. The feasibility of integrating e-learning in English language instruction as a factor in developing competitive professionals has been substantiated. Thu, 01 Jan 2026 00:00:00 GMT https://repository.hneu.edu.ua/handle/123456789/40507 2026-01-01T00:00:00Z