Advancements in intelligent assessment systems: Machine learning-driven automated scoring and feedback for English essays

This study explores the potential of developing intelligent assessment systems utilizing machine learning (ML) and natural language processing (NLP) technologies to enhance the efficiency of automated scoring and feedback for English essay writing. With the wide application of technology in the education sector, especially in language learning assessment, automated scoring systems not only optimize the allocation of teaching resources but also provide learners with immediate and objective feedback, facilitating the enhancement of their writing skills. Despite significant advancements in the application of ML and artificial intelligence (AI) in automated scoring systems, existing systems still face challenges in assessing the logic, coherence, and creativity of essay content, as well as in accurately identifying off-topic instances. This study aims to address these challenges through two main components: Firstly, an intelligent off-topic assessment mechanism for English essays is developed, utilizing text analysis techniques to accurately identify instances of deviation from the topic. Secondly, an automated scoring and feedback system for English essays based on a composite method is implemented, integrating various ML algorithms and NLP technologies to comprehensively assess the content, structure, and language usage of essays, providing practical writing improvement suggestions. Through these methods, not only is the accuracy of scoring and the effectiveness of feedback enhanced but the modernization process of English teaching and assessment is also advanced. This study aims to address the shortcomings of traditional automated scoring systems in assessing the logic and coherence of English essays, particularly in identifying off-topic responses and ensuring fairness and accuracy in scoring. By developing an intelligent assessment system that integrates multiple machine learning algorithms and natural language processing techniques, significant improvements have been achieved in the performance of automated scoring systems. These enhancements not only enhance the accuracy and consistency of scoring but also provide more specific and practical writing improvement suggestions for educational practices, thereby helping students enhance their writing skills.