Abstract
This paper addresses the issue of automated feedback generation for English language learners by presenting a corpus of English essays and their corresponding feedback, called LEAF, collected from the “essayforum” website. The corpus comprises approximately 6K essay-feedback pairs, offering a diverse and valuable resource for developing personalized feedback generation systems that address the critical deficiencies within essays, spanning from rectifying grammatical errors to offering insights on argumentative aspects and organizational coherence. Using this corpus, we present and compare multiple feedback generation baselines. Our findings shed light on the challenges of providing personalized feedback and highlight the potential of the LEAF corpus in advancing automated essay evaluation.- Anthology ID:
- 2024.naacl-short.36
- Volume:
- Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Kevin Duh, Helena Gomez, Steven Bethard
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 433–442
- Language:
- URL:
- https://aclanthology.org/2024.naacl-short.36
- DOI:
- Cite (ACL):
- Shabnam Behzad, Omid Kashefi, and Swapna Somasundaran. 2024. LEAF: Language Learners’ English Essays and Feedback Corpus. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers), pages 433–442, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- LEAF: Language Learners’ English Essays and Feedback Corpus (Behzad et al., NAACL 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2024.naacl-short.36.pdf