AI-Powered Education: Transforming Learning through Personalized and Scalable Solutions
DOI:
https://doi.org/10.63322/qm9dk118Keywords:
Artificial Intelligence in Education, Personalized Learning,, Scalable, Educational FrameworksAbstract
The rapid evolution of Artificial Intelligence (AI) has profoundly influenced various sectors, with education emerging as a pivotal area of transformation. The integration of AI into educational systems is redefining teaching methodologies, learning experiences, and administrative efficiencies. However, this intersection of AI and education faces significant challenges, including disparities in access, ethical concerns, and the lack of standardized frameworks for implementation. To address these challenges, this paper proposes a comprehensive AI-powered educational framework designed to personalize learning experiences and scale educational delivery efficiently. The framework incorporates a multi-layered architecture consisting of intelligent tutoring systems, adaptive learning platforms, and automated assessment tools. These components are designed to leverage AI algorithms such as natural language processing, predictive analytics, and machine learning to analyze student data, identify learning gaps, and deliver customized content. The proposed solution was evaluated through case studies and pilot implementations, demonstrating improved learner engagement, enhanced knowledge retention, and optimized resource utilization. Key findings include a 25% improvement in learning outcomes in personalized environments and increased teacher productivity by automating repetitive tasks. This research contributes to the field by offering a scalable and practical model for integrating AI into educational systems. It highlights ethical considerations, emphasizes the importance of inclusivity, and underscores the need for interdisciplinary collaboration. Finally, the paper presents actionable recommendations, including policy guidelines, strategies for addressing equity challenges, and a roadmap for future research. These recommendations aim to guide educators, technologists, and policymakers in harnessing the full potential of AI to create more equitable and effective learning ecosystems.
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