Enhancing English education with Natural Language Processing: Research and development of automated grammar checking, scoring systems, and dialogue systems

Jiazhen Zhang; Junhui Hu

doi:10.54254/2755-2721/102/20240956

Research Article

Open access

Published on 8 November 2024

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Zhang,J.;Hu,J. (2024). Enhancing English education with Natural Language Processing: Research and development of automated grammar checking, scoring systems, and dialogue systems. Applied and Computational Engineering,102,12-17.

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Enhancing English education with Natural Language Processing: Research and development of automated grammar checking, scoring systems, and dialogue systems

Jiazhen Zhang ¹, Junhui Hu *^,2,

¹ Liaoning Petrochemical University, Liaoning, China
² Shandong University, Shandong, China

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/102/20240956

Abstract

In this paper, we investigate the scope for transformational change that these technologies offer to English education. We examine how NLP can support English education through automated grammar checking having students’ text checked for grammatical errors in real time, automated scoring systems which evaluate written and verbal English against predefined criteria, and dialogue systems which interacts with learners in English to help develop their speaking and listening skills in an engaging and non-judgmental environment. We document the current status of these NLP applications, examine their educational benefits, highlight some of the challenges faced by the technologies and finally discuss the way forward for large-scale adoption of such technologies, bringing the research to a logical conclusion. We hope that this study will provide a comprehensive understanding of how NLP can be employed to transform education in English and also highlight some of the associated challenges and ethical dilemmas.

Keywords

Natural Language Processing, English Education, Automated Grammar Checking, Automated Scoring Systems, Dialogue Systems.

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References

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Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2nd International Conference on Machine Learning and Automation

Conference website: https://2024.confmla.org/

ISBN：978-1-83558-693-8(Print) / 978-1-83558-694-5(Online)

Conference date: 12 January 2025

Editor：Mustafa ISTANBULLU

Series: Applied and Computational Engineering

Volume number: Vol.102

ISSN：2755-2721(Print) / 2755-273X(Online)

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