Summary of Dress: Dataset For Rubric-based Essay Scoring on Efl Writing, by Haneul Yoo et al.
DREsS: Dataset for Rubric-based Essay Scoring on EFL Writing
by Haneul Yoo, Jieun Han, So-Yeon Ahn, Alice Oh
First submitted to arxiv on: 21 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces a large-scale dataset called DREsS, designed specifically for rubric-based automated essay scoring in English as a Foreign Language (EFL) writing education. The dataset, comprising three sub-datasets (DREsS_New, DREsS_Std., and DREsS_CASE), includes 2.3K real-classroom essays authored by EFL undergraduate students and scored by English education experts. To further enhance the dataset’s capabilities, the authors suggest a corruption-based augmentation strategy called CASE, which generates 40.1K synthetic samples of DREsS_CASE. This improves the baseline results by 45.44%. The DREsS dataset has the potential to enable more accurate and practical automated essay scoring systems for EFL writing education. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Automated essay scoring is a tool that helps students and teachers in English as a Foreign Language (EFL) writing classes. But previous tools didn’t use the right kind of data or scores, so they weren’t very useful. This paper makes a big change by creating a huge dataset called DREsS, which has three parts: real essays from actual EFL students and teachers, standard datasets that already exist, and fake but realistic essay examples. The paper also shows how to make the fake examples better match what real essays look like, which helps the scoring system work more accurately. This new dataset will let researchers create a better automated essay scoring system for EFL writing education. |
