AUTOMATED GRADING SYSTEM

Abstract

AUTOMATED GRADING SYSTEM for essays refers to the utilization of computer programs to evaluate and score essays written in response to specific prompts. It involves automating the assessment process, which offers benefits to both educators and learners by facilitating iterative improvements in students’ writing skills. In traditional grading methods, evaluators need to manually read and evaluate each paper, which can be a time-consuming process, especially when dealing with a large number of papers. Automated grading systems leverage the power of machine learning algorithms to analyze essays and provide accurate grades. By implementing these systems, institutions can significantly reduce the time required for grading papers, allowing teachers to focus on other important tasks such as providing feedback to students. The proposed grading system mentioned in the project aims to use machine learning algorithms such as Linear Regression, support vector regression (SVR), and Random Forest (RF) to automate the grading process. By analyzing various features extracted from essays and incorporating natural language processing techniques, the system aims to accurately predict scores for essays in a timely and efficient manner. The effectiveness of the system is evaluated using mean squared error as a performance metric. The results demonstrate the potential of machine learning models in automating the grading process and providing reliable feedback to students.