COLING 2024main4 citations

Assessing Online Writing Feedback Resources: Generative AI vs. Good Samaritans

Shabnam Behzad, Omid Kashefi, Swapna Somasundaran

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.

BibTeX
@inproceedings{behzad-etal-2024-assessing,
    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"
}
Assessing Online Writing Feedback Resources: Generative AI vs. Good Samaritans · COLING 2024