With the rapid development of educational informatization,this study innovatively proposes an efficient artificial intelligence educational auxiliary tool to address the difficulties in monitoring traditional classroom homework,the lack of timely tutoring,and the absence of personalized education.The research employs MEMS sensors combined with Kalman filtering algorithms to more accurately collect students'hand movement information.Through the fusion and calculation of multi-modal data,the tool achieves real-time recording of students'handwriting,effectively solving the current challenges in monitoring students'homework.By integrating artificial intelligence trained on analyzing students'learning data with voice recognition technology,students can resolve difficulties encountered during the learning process through immediate dialogue.This provides students with timely educational tutoring and enhances learning efficiency.
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