Evaluating Automated Grammar Corrective Feedback Tools: A Comparative Study of Grammarly and QuillBot in ESL Expository Essays

The advent of artificial intelligence and the proliferation of automated grammar feedback applications have garnered great interest among ESL learners as tools to facilitate language acquisition. While ample studies have examined the utility of applications like Grammarly and Quillbot, scarce resear...

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Published in:AKADEMIKA
Main Authors: Radin, Najlaa' Nasuha Mohd; Mustapha, Aida; Adam, Aileen Farida Mohd
Format: Article
Language:English
Published: PENERBIT UNIV KEBANGSAAN MALAYSIA 2024
Subjects:
Online Access:https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001287422700027
author Radin
Najlaa' Nasuha Mohd; Mustapha
Aida; Adam
Aileen Farida Mohd
spellingShingle Radin
Najlaa' Nasuha Mohd; Mustapha
Aida; Adam
Aileen Farida Mohd
Evaluating Automated Grammar Corrective Feedback Tools: A Comparative Study of Grammarly and QuillBot in ESL Expository Essays
Social Sciences - Other Topics
author_facet Radin
Najlaa' Nasuha Mohd; Mustapha
Aida; Adam
Aileen Farida Mohd
author_sort Radin
spelling Radin, Najlaa' Nasuha Mohd; Mustapha, Aida; Adam, Aileen Farida Mohd
Evaluating Automated Grammar Corrective Feedback Tools: A Comparative Study of Grammarly and QuillBot in ESL Expository Essays
AKADEMIKA
English
Article
The advent of artificial intelligence and the proliferation of automated grammar feedback applications have garnered great interest among ESL learners as tools to facilitate language acquisition. While ample studies have examined the utility of applications like Grammarly and Quillbot, scarce research compares their effectiveness in identifying and classifying errors in Malaysian ESL student writing samples. This study aimed to conduct such a comparative analysis using expository essays authored by Malaysian ESL students. This study employs a descriptive quantitative approach to collect data and conduct data analysis. Five writing samples were examined using both applications to ascertain the frequencies of errors flagged and categorised mistakes based on James' (1998) error classification schemata. Results demonstrated that overall, Grammarly detected more errors compared to Quillbot. Additionally, both applications recognised substantially more grammatical and substance inaccuracies relative to other error types like lexical, syntactic, or semantic issues. Grammarly provided detailed descriptions and suggestions of each error identified, while Quillbot only highlighted the errors with brief explanations. These findings suggest both tools can meaningfully supplement ESL learners in their language learning process. However, further investigations into their respective strengths and limitations are merited given the nuances observed. Overall, this exploratory study highlights the promise of automated writing evaluation to enable self-directed editing to enhance the language learning process among ESL learners.
PENERBIT UNIV KEBANGSAAN MALAYSIA
0126-5008
0126-8694
2024
94
2
10.17576/akad-2024-9402-27
Social Sciences - Other Topics
gold
WOS:001287422700027
https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001287422700027
title Evaluating Automated Grammar Corrective Feedback Tools: A Comparative Study of Grammarly and QuillBot in ESL Expository Essays
title_short Evaluating Automated Grammar Corrective Feedback Tools: A Comparative Study of Grammarly and QuillBot in ESL Expository Essays
title_full Evaluating Automated Grammar Corrective Feedback Tools: A Comparative Study of Grammarly and QuillBot in ESL Expository Essays
title_fullStr Evaluating Automated Grammar Corrective Feedback Tools: A Comparative Study of Grammarly and QuillBot in ESL Expository Essays
title_full_unstemmed Evaluating Automated Grammar Corrective Feedback Tools: A Comparative Study of Grammarly and QuillBot in ESL Expository Essays
title_sort Evaluating Automated Grammar Corrective Feedback Tools: A Comparative Study of Grammarly and QuillBot in ESL Expository Essays
container_title AKADEMIKA
language English
format Article
description The advent of artificial intelligence and the proliferation of automated grammar feedback applications have garnered great interest among ESL learners as tools to facilitate language acquisition. While ample studies have examined the utility of applications like Grammarly and Quillbot, scarce research compares their effectiveness in identifying and classifying errors in Malaysian ESL student writing samples. This study aimed to conduct such a comparative analysis using expository essays authored by Malaysian ESL students. This study employs a descriptive quantitative approach to collect data and conduct data analysis. Five writing samples were examined using both applications to ascertain the frequencies of errors flagged and categorised mistakes based on James' (1998) error classification schemata. Results demonstrated that overall, Grammarly detected more errors compared to Quillbot. Additionally, both applications recognised substantially more grammatical and substance inaccuracies relative to other error types like lexical, syntactic, or semantic issues. Grammarly provided detailed descriptions and suggestions of each error identified, while Quillbot only highlighted the errors with brief explanations. These findings suggest both tools can meaningfully supplement ESL learners in their language learning process. However, further investigations into their respective strengths and limitations are merited given the nuances observed. Overall, this exploratory study highlights the promise of automated writing evaluation to enable self-directed editing to enhance the language learning process among ESL learners.
publisher PENERBIT UNIV KEBANGSAAN MALAYSIA
issn 0126-5008
0126-8694
publishDate 2024
container_volume 94
container_issue 2
doi_str_mv 10.17576/akad-2024-9402-27
topic Social Sciences - Other Topics
topic_facet Social Sciences - Other Topics
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url https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001287422700027
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