Adaptation of the educational process in Ukraine to artificial intelligence technologies: A systematic review
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Анотація
Artificial intelligence (AI) is crucial in transforming the modern educational system. This article analyses the key processes involved in adapting Ukraine's educational system to AI technologies through a systematic review. To achieve this aim, PRISMA guidelines were employed, enabling the identification of the most relevant literature on the subject. The selected academic sources were analyzed using the content analysis method. The findings highlight that the primary objectives of AI integration in education include facilitating personalized learning, enhancing digital skills, automating tasks, influencing motivation, fostering self-regulation and reflection, and improving the analysis of educational data. These objectives support personalized educational programs, the exploration of new digital technologies, critical thinking, and the automated processing of organizational information within education. However, several obstacles have been identified, such as insufficient funding, a shortage of qualified personnel, infrastructure challenges, the lack of legal frameworks regulating AI usage, issues with data accessibility, risks associated with automation, and related ethical concerns. Addressing these challenges will require comprehensive solutions, including increased investment in education and scientific infrastructure, legislative changes, continued incentives for innovation, and educational outreach efforts. The conclusions emphasize the importance of preparing teaching and technical staff to respond to the educational environment's evolving demands adequately.
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Ключові слова
Digitalization, Artificial intelligence, Integration, Challenges, Educational environments, Ukraine
Бібліографічний опис
Adaptation of the educational process in Ukraine to artificial intelligence technologies: A systematic review / V. Motorina, O. Khodorkovskyi, V. Olianich, O. Kyrychenko, L. Yaroshevska // Periodicals of Engineering and Natural Sciences. – 2025. – Vol. 13 Nr. 1. – March 25. – P. 55-68
