Abstract
The application of artificial intelligence (AI) in personalized learning has demonstrated remarkable advantages, including intelligent assessment, resource recommendation, and teaching optimization, effectively enhancing learning outcomes and engagement. However, this process has also revealed several issues. Firstly, technical challenges and limitations hinder AI's ability to fully adapt to each student's individual needs, requiring further improvements in algorithm accuracy and reliability. Secondly, data privacy and security issues have become increasingly prominent, necessitating robust measures to protect student data from misuse and leakage. Lastly, challenges in the educational system and mindset must be addressed, focusing on how to integrate AI technology into traditional education models while maintaining teaching quality. To address these issues, continuous research and development, enhanced data protection, and the updating of educational systems and mindsets are required to fully harness the potential of AI in personalized learning.
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