Automated Grading of Essays: A Review

被引：5
|
作者：
Borade, Jyoti G. [1 ]
Netak, Laxman D. [1 ]
机构：
[1] Dr Babasaheb Ambedkar Technol Univ Lonere, Raigad 402103, MS, India
来源：
INTELLIGENT HUMAN COMPUTER INTERACTION, PT I | 2021年 / 12615卷
关键词：
Automated Grading of Essay (AGE); Machine Learning (ML); Latent semantic analysis (LSA); Natural Language Processing (NLP); Artificial neural networks (ANN); Multidimensional long short term memory (MD-LSTM); Recurrent neural networks (RNN);
D O I：
10.1007/978-3-030-68449-5_25
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：238 / 249
页数：12
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