Generative AI in Personalized Learning: Development Trajectory, Educational Applications, and Future Education

Generative Artificial Intelligence (GAI) has emerged as a disruptive force in personalized learning, offering unprecedented potential to meet the diverse needs of individual learners. Over its developmental trajectory, GAI has evolved from early neural networks like RNNs to advanced models such as GPT-4, powered by breakthrough technologies like transformers and multimodal systems, enabling adaptive and dynamic educational applications. This study examines GAI's practical applications in education, revealing its ability to transform traditional approaches by generating personalized teaching materials, providing real-time feedback, and enhancing problem-solving capabilities in specific subject areas. By tailoring learning experiences to individual strengths and weaknesses, GAI fosters deeper engagement and accelerates the mastery of knowledge and skills. Looking ahead, the integration of GAI with cutting-edge technologies such as smart classrooms, virtual reality, and mixed-reality environments is expected to create inclusive, efficient, and interactive learning ecosystems. By bridging the limitations of traditional education with the potential of future technologies, GAI is poised to redefine education, making it more personalized, collaborative, and impactful.