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@article{170654,
        author = {Vyalla Anjali and Nalla Shriya and Ramisetti Naga Sravanthi and Dasari Sandeep and Ms Richa Tiwari},
        title = {AUTOMATED ESSAY SCORING SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {7},
        pages = {1404-1408},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=170654},
        abstract = {Assessment within the Education system is playing a very important role judging the student performance. The current evaluation system has occurred by human assessment. As the number of students per teacher ratio is slowly increasing, the manual process of evaluation becomes complex. The main disadvantage of the manual process is that it consumes much time and lacks reliability and many more. This association online examination system has emerged to be the alternative tool for pen and paper-based methods. Present Computer-based evaluation system works only for multiple-choice questions, but there is no proper evaluation system for grading essays and short answers. We examine the Artificial Intelligence and combine natural language processing techniques with machine learning algorithms wherein the system analyzes the key aspects of essays including grammar, coherence, relevance, and structural organization. This study is used to evaluate automatic essay scoring and analyzed the limitations of current studies and research trends. The system will be trained on a comprehensive dataset of pre-scored essays to learn the subtle patterns associated with each level of scoring.},
        keywords = {Short answer scoring, Essay grading, Natural Language Processing, deep learning.},
        month = {December},
        }