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ARTIFICIAL INTELLIGENCE AS AN EFFECTIVE TOOL FOR PERSONALIZED LEARNING IN MODERN EDUCATION

Vasyl Kovalchuk, С. А. Рева, Iryna Volch, Svitlana Shcherbyna, Halyna Mykhailyshyn, Tetiana Lychova

2025Environment Technology Resources Proceedings of the International Scientific and Practical Conference8 citationsDOIOpen Access PDF

Abstract

Artificial Intelligence (AI) plays a pivotal role in the modernization of the educational process, particularly in higher education institutions, by enhancing the quality of professional training for future specialists. The integration of AI fosters personalized learning through adaptive technologies that optimize students' educational trajectories based on their individual needs and knowledge levels. This paper explores critical elements such as the implementation of virtual simulations and laboratories, automated assessment systems, and AI-powered learning tools. These innovations contribute to creating a more efficient, interactive, and engaging educational environment. The primary objective of this study is to substantiate the role of AI in personalized learning and improving the efficiency of the educational process. It also aims to analyze the specific features of AI integration into vocational education and assess the impact of adaptive learning technologies, automated assessment systems, and virtual simulations on the training of future professionals. The research employs both theoretical and empirical methods. The empirical research involved an experimental study with the participation of 45 educators and 120 students. To assess the effectiveness of AI integration in educational settings and professional activities, a customized survey was developed. The questionnaire addressed issues such as familiarity with, application of, and perceived benefits from AI-driven tools, including chatbots, automated grading systems, and adaptive learning platforms. The analysis of survey responses reveals widespread adoption of AI technologies among students. Approximately 70% of the students are familiar with these technologies and actively use AI-powered chatbots, automated assessment systems, and adaptive learning platforms. Virtual simulations and AI-driven learning assistants also contribute to practical skill development, although their full potential remains underutilized due to infrastructure limitations. Among educators, AI adoption is comparatively lower. Only 40% actively use AI in their teaching practices, while 35% apply it on an occasional basis. The main barriers to AI adoption include insufficient technical training (60%), lack of funding (50%), and legal and ethical concerns (40%). Nevertheless, 55% of educators recognize the potential of AI to enhance personalized learning and are willing to integrate AI tools into their teaching methodologies. The study confirms AI’s significant potential in improving the educational process. AI-driven adaptive learning environments can accommodate individual learning styles, knowledge levels, and personal preferences. AI-powered assessment tools, such as Google Forms with AI modules, enable efficient and objective evaluation of student knowledge, thereby reducing educators' workload and providing immediate feedback. Virtual assistants, including GPT-based platforms, offer real-time support for learning and task completion, particularly in remote and blended learning environments. The integration of AI in education enhances teaching efficiency, fosters innovative learning methodologies, and prepares students for the evolving demands of the modern job market. The adoption of advanced AI technologies is crucial for developing a competitive educational ecosystem capable of addressing the global challenges of digital transformation. Future research should focus on improving AI accessibility, enhancing educator training, and addressing ethical concerns to fully harness the benefits of AI in education. Furthermore, the continued development of adaptive algorithms, virtual tutors, and augmented reality will be essential in shaping the future of AI-powered learning environments.

Topics & Concepts

Personalized learningComputer scienceArtificial intelligenceHuman–computer interactionPsychologyMathematics educationTeaching methodOpen learningCooperative learningEngineering Education and TechnologyTechnology and Human Factors in Education and HealthArtificial Intelligence in Education
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