Dinghe Li

With the rapid advancement of artificial intelligence (AI), personalized learning platforms have become increasingly prominent in transforming educational practices. This study investigates the adaptability and effectiveness of AI-driven personalized learning platforms within the context of secondary education in Hong Kong and Macao. Employing a mixed-methods research design, the study combines quantitative data from student performance metrics with qualitative insights from teacher and student interviews across multiple pilot schools. The findings reveal that while the integration of AI tools significantly enhances individualized learning outcomes and student engagement, contextual factors such as curriculum structure, teacher training, and digital infrastructure play critical roles in the successful adoption of such technologies. This research provides practical implications for policymakers and educators aiming to bridge the gap between technological innovation and educational equity in the Greater Bay Area.

Artificial Intelligence in Education; Personalized Learning; Secondary Education; Educational Technology Adaptation; Hong Kong and Macao Schools

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