UNLOCKING THE POWER OF RECOMMENDATION SYSTEMS:PERSONALIZED LEARNING IN EDUCATION

Doniyor G’ulomov; Alpamis Kutlimuratov

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Doniyor G’ulomov Muallif
Alpamis Kutlimuratov Muallif

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The modern educational landscape is undergoing a significant transformation driven by the advent of technology, primarily through recommendation systems that harness artificial intelligence (AI) and machine learning (ML). These systems, pivotal in driving personalized learning, analyze vast amounts of student data, including academic performance, learning styles, and interests. Through this data-driven approach, they produce tailored recommendations, ensuring individualized learning pathways and resources, thus creating unique educational experiences for each student. This article delves into the benefits of such systems in fostering personalized learning, addressing the inherent diversity among learners, boosting engagement, and equipping students with crucial skills for the 21st century. The ultimate goal is to harmonize the capabilities of AI and human educators to craft a more engaging, inclusive, and effective educational landscape.

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