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Enhancing Education Systems for Personalized Learning
Abstract
This paper explores the enhancement of education systems for personalized learning through AI-driven engineering. Through case studies and research insights, it investigates how artificial intelligence is revolutionizing traditional education practices, including teaching, assessment, and student support. The study highlights the application of AI techniques such as adaptive learning algorithms, natural language processing, and educational data mining in tailoring learning experiences, providing immediate feedback, and identifying individual learning needs. Additionally, it discusses the integration of AI with learning management systems, virtual tutors, and educational games to promote engagement, motivation, and lifelong learning. The paper also addresses challenges such as privacy protection, algorithmic bias, and digital divide in the deployment of AI-driven engineering solutions in education. It emphasizes the importance of pedagogical innovation, teacher professional development, and equity in leveraging AI's potential to transform education and empower learners of all backgrounds.
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