@inproceedings{behzad-etal-2024-assessing-online,
title = "Assessing Online Writing Feedback Resources: Generative {AI} vs. Good Samaritans",
author = "Behzad, Shabnam and
Kashefi, Omid and
Somasundaran, Swapna",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.144",
pages = "1638--1644",
abstract = "Providing constructive feedback on student essays is a critical factor in improving educational results; however, it presents notable difficulties and may demand substantial time investments, especially when aiming to deliver individualized and informative guidance. This study undertakes a comparative analysis of two readily available online resources for students seeking to hone their skills in essay writing for English proficiency tests: 1) essayforum.com, a widely used platform where students can submit their essays and receive feedback from volunteer educators at no cost, and 2) Large Language Models (LLMs) such as ChatGPT. By contrasting the feedback obtained from these two resources, we posit that they can mutually reinforce each other and are more helpful if employed in conjunction when seeking no-cost online assistance. The findings of this research shed light on the challenges of providing personalized feedback and highlight the potential of AI in advancing the field of automated essay evaluation.",
}
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%0 Conference Proceedings
%T Assessing Online Writing Feedback Resources: Generative AI vs. Good Samaritans
%A Behzad, Shabnam
%A Kashefi, Omid
%A Somasundaran, Swapna
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%Y Hoste, Veronique
%Y Lenci, Alessandro
%Y Sakti, Sakriani
%Y Xue, Nianwen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F behzad-etal-2024-assessing-online
%X Providing constructive feedback on student essays is a critical factor in improving educational results; however, it presents notable difficulties and may demand substantial time investments, especially when aiming to deliver individualized and informative guidance. This study undertakes a comparative analysis of two readily available online resources for students seeking to hone their skills in essay writing for English proficiency tests: 1) essayforum.com, a widely used platform where students can submit their essays and receive feedback from volunteer educators at no cost, and 2) Large Language Models (LLMs) such as ChatGPT. By contrasting the feedback obtained from these two resources, we posit that they can mutually reinforce each other and are more helpful if employed in conjunction when seeking no-cost online assistance. The findings of this research shed light on the challenges of providing personalized feedback and highlight the potential of AI in advancing the field of automated essay evaluation.
%U https://aclanthology.org/2024.lrec-main.144
%P 1638-1644
Markdown (Informal)
[Assessing Online Writing Feedback Resources: Generative AI vs. Good Samaritans](https://aclanthology.org/2024.lrec-main.144) (Behzad et al., LREC-COLING 2024)
ACL