ARTIFICIAL INTELLIGENCE IN PERSONALIZATION OF LEARNING

Аннотация

The article outlines the enormous potential of artificial intelligence in personalization and accessibility in education, the existence of digital inequality, which is a significant obstacle to personalization of learning, which requires joint efforts of educators, technologists and politicians tocreate afair educational environment forall students. In today’s world, there is a growing focus on the potential and role of artificial intelligence (AI) in personalizing learning and bridging the digital divide. The paper is based on a literature review and case study analysis demonstrating that AI can improve educational outcomes by tailoringthe learning process to individual student needs. However, thedigital divide, manifested in unequal access to technology and digital skills, remains a significant barrier to the widespread adoption of AI in education. The discussion highlights the need to develop inclusive strategies and ethical approaches to the use of AI. The paper concludes with practical recommendations for educators and policymakers, as well as suggestions for future research aimed at studying the long-term effects and scalability ofAIsolutions. The educational landscape is undergoing significant changes under the influence of modern technologies, and AI is becoming one of the key drivers of this transformation, offering new approaches to learning and teaching. AI technologies such as machine learning, natural language processing, and big data analytics are actively integrated into educational systems. They are used in the creation of smart classrooms, virtual assistants, automated assessment systems, and adaptive learning platforms. These innovations not only simplify administrative processes, but also open up opportunities for creating individualized learning paths that take into account the uniqueneeds of each student. Technological literacy is becoming an integral part of success in modern education, which is faced with theneed to adapt to the challenges of the digital age. However, traditional educational approaches based on uniform programs and a fixed pace of learning are often ineffective in the contextofthediversity of students'abilities andinterests. AI offers a solution through personalized learning, allowing the content, methods, and pace of learning to be tailored to the individual student. Personalized learning using AI involves dynamically adapting the educational process. For example, intelligent tutoring systems can analyze a student’s mistakes in real time and offer customized assignments that help fill gaps in knowledge. Adaptive platforms can adjust the complexity of the material depending on the student’s success or difficulty. This approach contrasts with the traditional “one size fits all” approach, which can either overwhelm students with low levels of preparation or understimulate thosewho havealready mastered thematerial. Despitethe potential of AI, itsimplementation faces a majorobstacle: the digital divide. Millions of students around the world lack access to basic technological resources such as high-speed internet, personal computers, or tablets. This problem is particularly noticeable in low-income page1892 INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE ISSN:2692-5206,ImpactFactor:12,23 AmericanAcademicpublishers,volume05,issue03,2025 Journal: https://www.academicpublishers.org/journals/index.php/ijai regions, rural areas, and among socially vulnerable groups. For example, in developing countries, only 34% of households have access to the internet, according to the International Telecommunication Union (ITU, 2022). The digital divide is exacerbated by a lack of digital literacy, which limitsthe abilityof studentsand teachers to effectively useAItools. The aim of the study is– analyze how AI can simultaneously serve as a tool for personalizing learning and as ameans ofbridging thedigital divide. Objectives of thestudy: -identify which AI technologies are already being used topersonalizelearning; -determine theimpact ofAI technology oneducational outcomes; -identify barriers related tothedigital dividethat hindertheireffective use; -identify strategies topromote moreinclusiveuseof AIineducation. To study the topic, a systematic review of the academic literature was conducted, including more than 50 sources published between 2015 and 2023. The main focus was on empirical studies, theoretical papers, and reviews related to the use of AI in education. The search was conducted in the Google Scholar, IEEE Xplore, and ERIC databases using the keywords: “artificial intelligence ineducation”, “personalized learning”,“digital divide”, “adaptive technologies”,and their combinations with Boolean operators (e.g., AND, OR). Inclusion criteria: publications in English or Russian; availability of data on the impact of AI on learning; mention of aspects of digital access or equality. The review process included the selection of relevant articles, analysis of their content, and systematiza