Design and Implementation of a Chinese Language Educational Support System Based on Natural Language Processing

With the rapid development of Natural Language Processing (NLP) technologies, intelligent assistance systems for education have become a research hotspot. This paper presents the design and implementation of a Chinese educational assistance system aimed at addressing challenges in essay grading and personalized learning guidance for primary and secondary students. The system utilizes advanced automatic text analysis, semantic understanding, and personalized learning suggestions to provide real-time feedback on student essays. By employing NLP techniques such as grammar analysis, semantic matching, and error correction, the system enhances both learning efficiency and the overall quality of feedback provided to students. The system provides automatic grading for Chinese essays and generates personalized feedback, thereby improving learning efficiency. This paper details the system’s design architecture, implementation methods, and key algorithms, with experimental verification of its effectiveness in real educational scenarios. The results show that this system not only improves grading accuracy but also offers a scalable solution that can be adapted for broader educational contexts.