This study focuses on the exploration and development of an AI-based learning model to realize personalized education, which is tailored to the needs of individual students. Using a qualitative method with a case study approach, data was collected through interviews, observations, and document analysis. The study results indicate that adaptive algorithms and real-time feedback contribute significantly to the effectiveness of personalized learning. However, this study also found that AI and direct assistance from human resources or teachers proved more effective in supporting education, especially in aspects that require conceptual understanding. These findings highlight the importance of attention to how AI is used to increase learning effectiveness and student motivation. Implications in this study include recommendations for developing ethical and collaborative technology-based learning, with a balanced integration between the roles of technology and human resources in education.
                        
                        
                        
                        
                            
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