Retrieval Method of Online English Grammar Questions Based on Natural Language Processing

Background: With the rapid development of information technology, natural language processing has become an important branch, which has received widespread attention and application. The rise of this technology has brought revolutionary changes to the field of education, especially in achieving the Sustainable Development Goal (SDG) of quality education. In the field of online English education, Multiple Choice Questions (MCQs) are a common assessment method, and their accuracy directly affects students’ learning outcomes and feedback quality. Purpose: In order to improve the accuracy and effectiveness of MCQs, an innovative search method based on fuzzy tree matching is proposed. Methodology: This method effectively captures the core features of grammar problems and calculates the similarity between problems by introducing the Parse-key tree structure. The Parse-key tree consists of subtrees and positional information. The subtree structure reduces the impact of noise on the target grammar structure information and inserts spatial position information to determine grammar knowledge points. Findings: The experimental results showed that in incomplete queries, the Mean Reciprocal Rank (MRR) value of the grammar MCQs problem was improved by 7.9% compared with the existing methods. When the recall rate was 0.1, the precision of our method remained above 0.4, while that of other methods was below 0.4. In complete queries, the MRR value of the proposed method was 29.6% higher than that of the traditional part of speech-sorting algorithms, and the precision usually remained between 0.2 and 1. However, when other methods reached 0.2, the precision of our method dropped below 0.2, demonstrating significant performance advantages. Based on the above results, the research method not only improves the efficiency and quality of knowledge acquisition, but also optimises the organisational structure of knowledge, enhances the sharing ability of knowledge, promotes innovation and application of knowledge and provides new ideas and technical support for the development of online education. Contribution: This research proposes an innovative search method based on fuzzy tree matching, which can effectively improve the accuracy and effectiveness of MCQs assessment in online English education.