Transformation of Artificial Intelligent-Based Education: Towards More Personalized and Effective Learning
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Abstract
Artificial intelligence (AI)-based education transformation has become a global trend to enhance learning effectiveness. AI enables personalized learning by adapting materials, methods, and pace according to each student's needs. Technologies such as intelligent tutoring systems, learning analytics, and educational chatbots have been widely adopted to improve the learning experience. This study aims to analyze the role of AI in learning personalization and its effectiveness in improving student outcomes, while also examining the challenges and opportunities of its implementation. The research method is a systematic literature review of recent studies on AI in education, with data gathered from academic journals, research reports, and industry publications. The results show that AI increases student engagement and independence through adaptive feedback and educator support, and presents opportunities for AI-driven blended learning development. However, challenges such as limited access to technology, ethical and data privacy concerns, and educators’ readiness remain significant barriers. The study concludes that while AI holds great potential in education, its implementation must be accompanied by well-planned strategies and appropriate policy support to maximize its benefits.
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