Abstract:

Essay grading is an essential aspect of the educational system as it plays a significant role in evaluating students' comprehension, critical thinking, and communication skills. Essays also allow teachers to gauge a student's ability to articulate ideas, analyze information, and present arguments coherently. However, grading them is a time-consuming and resource-intensive process. Recently, thanks to the rapid advances in ICT, automated essay evaluation has started gaining popularity as a means to overcome these challenges. In this study, we propose an artificial intelligence model that can automatically assess essays by predicting scores for various aspects, namely grammar, syntax, vocabulary, cohesion and conventions. The proposed model, which leverages the power of machine learning and Natural Language Processing techniques, was trained on more than two thousand essays that have been graded by teachers based on different linguistic features. The performance of this artificial intelligence model was evaluated through comprehensive experiments on a distinct dataset of essays. The results have demonstrated the model's ability to accurately predict scores for different aspects of essays, showcasing its potential as a scalable and efficient method for essay evaluation.

Keywords:

Education, Assessment, Artificial Intelligence, Essays.