Develop a Generic Essay Scorer for Practice Writing Tests of Statewide Assessments

Yi Gui


Abstract
This study examines whether NLP transfer learning techniques, specifically BERT, can be used to develop prompt-generic AES models for practice writing tests. Findings reveal that fine-tuned DistilBERT, without further pre-training, achieves high agreement (QWK ≈ 0.89), enabling scalable, robust AES models in statewide K-12 assessments without costly supplementary pre-training.
Anthology ID:
2025.aimecon-main.8
Volume:
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
Month:
October
Year:
2025
Address:
Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States
Editors:
Joshua Wilson, Christopher Ormerod, Magdalen Beiting Parrish
Venue:
AIME-Con
SIG:
Publisher:
National Council on Measurement in Education (NCME)
Note:
Pages:
58–81
Language:
URL:
https://aclanthology.org/2025.aimecon-main.8/
DOI:
Bibkey:
Cite (ACL):
Yi Gui. 2025. Develop a Generic Essay Scorer for Practice Writing Tests of Statewide Assessments. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 58–81, Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):
Develop a Generic Essay Scorer for Practice Writing Tests of Statewide Assessments (Gui, AIME-Con 2025)
Copy Citation:
PDF:
https://aclanthology.org/2025.aimecon-main.8.pdf