Automated Grading Systems
S. C. Vetrivel, V. P. Arun, Ramya Ambikapathi, T. P. Saravanan · 2025
Automated grading systems, powered by artificial intelligence (AI), have emerged as transformative tools in higher education, revolutionizing the assessment landscape. This chapter explores the implementation and impact of automated grading systems in enhancing efficiency and consistency in student assessments. As the demand for scalable and objective evaluation methods grows, these AI-driven systems offer a promising solution to address the challenges faced by educators and institutions. The study begins by examining the technological foundations of automated grading systems, including natural language processing (NLP), machine learning (ML) algorithms, and data analytics. These technologies enable the systems to evaluate various forms of student work, from multiple-choice tests to complex essays, with remarkable accuracy and speed. By analyzing large datasets of student responses, AI algorithms learn to identify patterns and apply grading criteria consistently, minimizing the subjectivity and biases often associated with human grading. A key advantage of automated grading systems is their ability to process and provide feedback on a vast number of student submissions within a significantly reduced timeframe. This efficiency not only alleviates the grading burden on educators but also allows for timely feedback, which is crucial for student learning and improvement.