An Approach to Automate the Grading Process in IELTS Writing Task

This paper presents a novel approach to grading IELTS writing tasks using machine learning models, addressing the inherent limitations of the traditional manual grading method. The conventional approach, while widely accepted, suffers from several drawbacks including subjectivity, inconsistency, and scalability. Human graders, despite their expertise, may exhibit bias and variability in their assessments, leading to potential inconsistencies in grading. Furthermore, the manual method is time-consuming and labor-intensive, posing significant challenges in terms of scalability especially in the face of increasing numbers of IELTS test-takers globally. Our proposed machine learning model aims to mitigate these issues by providing an objective, consistent, and efficient method for grading IELTS writing tasks. Preliminary results indicate promising potential for the application of machine learning in this domain, paving the way for future research and practical applications.