A comparison of various machine learning algorithms and execution of flask deployment on essay grading

This paper compares machine learning algorithms (including random forest, which achieved 97.67% accuracy) for automated essay scoring/grading and deploys the best model as a web application using Flask. The work addresses automated assessment of written responses to reduce teacher burden in grading essays.

Students’ performance can be assessed based on grading the answers written by the students during their examination. Currently, students are assessed manually by the teachers. This is a cumbersome task due to an increase in the student-teacher ratio. Moreover, due to coronavirus disease (COVID-19) pandemic, most of the educational institutions have adopted online teaching and assessment. To measure the learning ability of a student, we need to assess them. The current grading system works well f

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