Deep Grading: Incorporating Argument Strength into Neural Essay Evaluation
Document Type
Conference Proceeding
Source of Publication
Proceedings of the 2024 16th International Conference on Education Technology and Computers
Publication Date
1-21-2025
Abstract
The automation of essay grading poses a significant challenge, especially when evaluating the aspects of argument strength in essays designed for discussion, debating and argumentation. Addressing this challenge, we developed a methodology for calculating argument strength, effectively reducing the impact of essay length variations. Leveraging this argument strength scoring methodology, we built a deep neural network model aimed at learning enhanced embedding representations for essays, capable of capturing the intricate nuances of argumentation, which encompass information beyond textual and structural characteristics. Our results demonstrate competitive performance, surpassing traditional and deep learning embedding baselines.
DOI Link
ISBN
9798400717819
Publisher
ACM
First Page
275
Last Page
279
Disciplines
Computer Sciences
Keywords
Argument strength, Neural network, Essay grading, Argumentation, Deep learning
Recommended Citation
Kohail, Sarah and Alfandi, Omar, "Deep Grading: Incorporating Argument Strength into Neural Essay Evaluation" (2025). All Works. 7052.
https://zuscholars.zu.ac.ae/works/7052
Indexed in Scopus
no
Open Access
no