ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TECHNOLOGIES IN FORMING ONLINE EDUCATION SYSTEMS

Аннотация

This article presents a methodology for creating a system to form individual learning paths in online education based on artificial intelligence (AI) and machine learning (ML) technologies, the proposed model considers the learner’s cognitive level, learning style, ability, and learning intensity, enabling personalized education, the stages of data collection, analysis, recommendation systems, and learning process monitoring are detailed, the system aims to improvethequality ofeducation and enhance learning outcomes. Key words: Artificial intelligence, machine learning, individual learning path, personalized learning, educational technologies, learning analytics, recommendation system, knowledge level, digital footprints, big dataineducation. Anotatsiya: Mazkur maqolada sun’iy intellekt va mashinaviy o‘qitish texnologiyalaridan foydalangan holda individual o‘quv yo‘nalishini shakllantirish tizimini yaratish metodologiyasi taqdim etiladi, taklif etilgan yondashuv o‘quvchining bilim darajasi, o‘rganish uslubi, qobiliyati va intensivligini hisobga olgan holda shaxsiylashtirilgan ta’limni yo‘lga qo‘yishga qaratilgan, yaratilgan model asosida ma’lumotlarni yig‘ish, tahlil qilish, tavsiya tizimlari va monitoring qilish bosqichlari amalga oshiriladi, tizim ta’lim sifatini oshirish, o‘quvchilarning faolligini kuchaytirish vanatijalarni yaxshilash imkoniniberadi. Kalit so‘zlar: Sun’iy intellekt, mashinaviy o‘qitish, individual o‘quv yo‘nalishi, shaxsiylashtirilgan ta’lim, ta’lim texnologiyalari, o‘quv analitikasi, tavsiya tizimi, bilim darajasi, raqamliizlar, kattahajmdagi ta’limma’lumotlari. Aннотация: В статье представлена методология создания системы формирования индивидуальной траектории онлайн-обучения на основе технологий искусственного интеллекта и машинного обучения, предлагаемая модель учитывает уровень знаний, стиль обучения, способности и интенсивность ученика, что позволяет внедрить персонализированное обучение, раскрываются этапы сбора и анализа данных, использования рекомендательных систем и мониторинга учебного процесса, система способствует повышению качества образованияи улучшениюучебных результатов. Ключевые слова: искусственный интеллект, машинное обучение, индивидуальная траектория обучения, персонализированное обучение, образовательные технологии, учебная аналитика, рекомендательная система, уровень знаний, цифровые следы, большие данныевобразовании. The modern education system is undergoing a fundamental transformation through the use of artificial intelligence (AI) and machine learning (ML) technologies. In particular, these technologies have made it possible to deliver personalized educational content tailored to learners’ knowledge levels, learning styles, and individual needs in the development of personalized learning pathways. This article outlines a methodology for creating a system to shape individualized online learning pathways based on AI and ML. It presents the main stages, algorithms, and practical applications oftheproposed system. 230 INTERNATIONAL MULTIDISCIPLINARY JOURNAL FOR RESEARCH & DEVELOPMENT SJIF2019:5.2222020:5.5522021:5.6372022:5.4792023:6.5632024:7,805 eISSN:2394-6334 https://www.ijmrd.in/index.php/imjrd Volume12,issue04(2025) With the help of AI-powered tools, educators can gain deeper insights into their students' strengths and weaknesses and design personalized learning plans that support each learner’s academic success. As a result, early identification of learning gaps plays a vital role in building a solid foundation for future development. AI serves as a powerful tool for detecting these gaps and delivering targeted support. AI-based platforms collect and analyze data on student interaction with educational materials, timespent ontasks, test results, and overall learning performance, helping to better understand the needs and engagement levels of each learner. For instance, if the AI system identifies that a student is struggling with a specific assignment (including tests and exercises), it can recommend additional learning resources. Simultaneously, the system may offer self-assessment quizzes based onthematerial already covered bythestudent. Analyses show that in forming individualized learning pathways (ILPs), AI and ML technologies makeuse oflarge volumes ofeducational data—commonlyreferred toas Big Data in Education. Big Data is radically transforming the educational environment by providing valuable insights into students' behaviors, learning styles, and academic achievements. Through the analysis of Big Data, it is now possible to develop personalized learning plans tailored to the individual needs of each student, improve communication between teachers and students, and enhance overall student engagement (Figure 1). Figure 2. Block Diagram of the Algorithm for Forming a Personalized Learning Pathway Using Artificial Intelligence Mechanisms Thealgorithm consists ofthefollowing stages: Stage 1.Creating a Skills Matrix To identify the learner's knowledge