A Systematic Review of Pretrained Models in Automated Essay Scoring
Automated essay scoring (AES) uses artificial intelligence and machine learning methods to grade student essays and produce human-like scores. AES research has witnessed significant advancements over time by adopting diverse machine learning models. This evolution started with traditional techniques...
Saved in:
Main Authors: | Ahmed M. Elmassry, Nazar Zaki, Negmeldin Alsheikh, Mohammed Mediani |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/11062635/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
SynergyScore: Leveraging Pretrained Language Models for Effective Evaluation of Code-Switched Sentences
by: S. R. Mithun Kumar, et al.
Published: (2025-01-01) -
Is generative AI ready to replace human raters in scoring EFL writing? Comparison of human and automated essay evaluation
by: Arif Cem Topuz, Mine Yıldız, Elif Taşlıbeyaz, Hamza Polat and Engin Kurşun
Published: (2025-07-01) -
Learner behavior modeling: an interpretable knowledge tracking model based on pretrained model
by: ZHOU Tao, et al.
Published: (2025-01-01) -
Deep Learning Approach for Pneumonia Prediction from X-Rays using A Pretrained Densenet Model
by: Ahmad Zein Al Wafi, et al.
Published: (2025-06-01) -
Chinese Sequence Labeling Based on Stack Pre-training Model
by: LIU Yu-peng, et al.
Published: (2022-02-01)