Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022)

<Previous Article In Volume
Next Article In Volume>

A Hybrid Automated Essay Scoring Using NLP and Random Forest Regression

Authors
Muhammad Zaim Azri Bin Azahar1, *, Khairil Imran Bin Ghauth1
1Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Selangor, Malaysia
*Corresponding author. Email: 1181101108@student.mmu.edu.my
Corresponding Author
Muhammad Zaim Azri Bin Azahar
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-094-7_35How to use a DOI?
Keywords
Automated Essay Scoring; Linear Regression; Random Forest; Deep Learning; Natural Language Processing
Abstract

Assessing the performance of students through subjective assessments namely essays is critical in measuring their achievement during the learning process in an educational system. The essay test will evaluate the student’s ability to remember and express their ideas or opinions toward certain topics. A teaching staff is usually required to assess and grade the students’ essays. This paper presents a hybrid Automated Scoring System based on Natural Language Processing (NLP) and Random Forest Regression. The model focused on regression task where the predicted score is in a continuous value. Natural Language Processing (NLP) has also been applied in this work to extract features from essays. Finally, all the proposed model is compared to Linear Regression and Deep Learning and are then evaluated to compare the performance of the models by using the Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE).

Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
27 December 2022
ISBN
10.2991/978-94-6463-094-7_35
ISSN
2589-4900
DOI
10.2991/978-94-6463-094-7_35How to use a DOI?
Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Muhammad Zaim Azri Bin Azahar
AU  - Khairil Imran Bin Ghauth
PY  - 2022
DA  - 2022/12/27
TI  - A Hybrid Automated Essay Scoring Using NLP and Random Forest Regression
BT  - Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022)
PB  - Atlantis Press
SP  - 448
EP  - 457
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-094-7_35
DO  - 10.2991/978-94-6463-094-7_35
ID  - Azahar2022
ER  -