Abstract

Abstract: With the onset of the technological revolution, the efficiency of the current manual systems has been improved drastically and the accuracy of the products produced are also increasing. The most affected of the fields from this technological change is Education. The combination of Education with technology has been coined as a new term of edtech. Assessment in the Education system plays a significant role in judging student performance. Humans are becoming more interested in using automated tools. Consequently, in the last few years, the use of automatic assessment methods in the education system and student response evaluation has increased significantly. There is currently no adequate evaluation mechanism for grading essays and short responses; the computer-based evaluation system only works for multiple-choice questions. For the past few decades, many researchers have been working on automated essay grading and short answer scoring, but evaluating an essay while taking into account all the criteria, such as the content's relevance to the prompt, the development of ideas, cohesion, and coherence, is still a difficult task. We examined the limits of the most recent studies and research trends while studying the Artificial Intelligence and Machine Learning approaches used to assess computerized essay grading. In this project, we have studied different uses of Machine Learning and how we can improve the efficiency of the Essay Scoring using AI and other algorithms. In this project we also aim to highlight the problems faced by teachers and the possible solution which could be designed to overcome the problem.

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