Development of English Composition Correction and Scoring System Based on Text Similarity Algorithm

Abstract

This study focuses on creating an innovative system that leverages a text similarity algorithm to provide accurate correction and scoring of English compositions. By harnessing advanced computational techniques, the system aims to streamline the grading process and offer more consistent feedback to students. The research methodology involves the design and implementation of the text similarity algorithm, which analyzes various linguistic aspects such as vocabulary usage, grammar, coherence, and organization. This algorithm is then integrated into a comprehensive scoring system that evaluates student compositions against reference texts and provides detailed feedback on areas for improvement. The effectiveness of the system is validated through rigorous testing using a diverse set of English compositions and comparison with human grading. The results of this investigation show how well the system that was created can automatically correct and score English papers with a high degree of correctness and dependability. By reducing the burden of manual grading and providing immediate feedback to students, the system has the potential to enhance the teaching and learning process in English language education. Overall, by developing a scalable and effective method for compositional assessment based on text similarity algorithms, this research advances educational technology.