Automated Grading of Essays: A Review

• Published in: Intelligent Human Computer Interaction Vol. 12615; pp. 238 - 249
• Main Authors: Borade, Jyoti G., Netak, Laxman D.
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2021; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Artificial neural networks (ANN); Automated Grading of Essay (AGE); Latent semantic analysis (LSA); Machine Learning (ML); Multidimensional long short term memory (MD-LSTM); Natural Language Processing (NLP); Recurrent neural networks (RNN)
• ISBN: 9783030684488; 3030684482
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-030-68449-5_25

Grading essay type of examinations is a kind of assessment where teachers have to evaluate descriptive answers written by students. Evaluating explanatory answers is a challenging task. Evaluating essay type questions are often laborious, requiring more time compared to multiple-choice questions. Also, the evaluation process is a subjective one leading to inaccuracies and considerable variation in grading. In recent times, many researchers have developed techniques for Automated Grading of Essays (AGE) using various machine learning methods. This paper reviews and summarizes the existing literature on methods for automated grading of essays. The paper reviews applications of approaches such as Natural Language Processing and Deep Learning for AGE. The paper identifies a few areas for further research in solving the problem of AGE.