Research on Mistake Analysis and Personalized Learning Feedback System Based on the Qwen2 Model

This study developed a mistake analysis and personalized learning feedback system based on the Qwen2-7B model. Through LoRA technology fine-tuning, the system achieves efficient mistake analysis and the generation of learning suggestions. Experimental results show that students using this system improved their average scores by 13.4 points over 8 weeks, significantly outperforming the control group. The system's mistake analysis accuracy reached 87%, with a user satisfaction rate of 92%, and it can stably handle 2000 concurrent user accesses. The research results provide innovative solutions for the field of intelligent education and demonstrate the application potential of large language models in personalized education.