AI IN EDUCATION: PERSONALIZED LEARNING PATHWAYS USING MACHINE LEARNING ALGORITHMS
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Abstract
The integration of artificial intelligence (AI) in education has revolutionized the way personalized learning pathways are developed, offering tailored educational experiences that cater to individual student needs. This paper explores the application of machine learning algorithms to create adaptive learning systems that assess students’ unique strengths, weaknesses, and learning styles. By analyzing vast amounts of educational data, these algorithms can predict student performance, recommend customized learning materials, and adjust instructional strategies in real time. We present a comprehensive review of existing literature on personalized learning, highlighting the benefits and challenges associated with AI-driven educational tools. Case studies demonstrate successful implementations of machine learning in various educational contexts, showcasing improvements in student engagement, retention rates, and academic achievement. Furthermore, the paper discusses ethical considerations, data privacy concerns, and the importance of human oversight in the deployment of AI systems in education. Ultimately, our findings suggest that machine learning has the potential to significantly enhance the effectiveness of educational practices, paving the way for a more personalized and inclusive learning environment.
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