AGReE: A system for generating Automated Grammar Reading Exercises
Sophia Chan, Swapna Somasundaran, Debanjan Ghosh, Mengxuan Zhao
Abstract
We describe the AGReE system, which takes user-submitted passages as input and automatically generates grammar practice exercises that can be completed while reading. Multiple-choice practice items are generated for a variety of different grammar constructs: punctuation, articles, conjunctions, pronouns, prepositions, verbs, and nouns. We also conducted a large-scale human evaluation with around 4,500 multiple-choice practice items. We notice for 95% of items, a majority of raters out of five were able to identify the correct answer, for 85% of cases, raters agree that there is only one correct answer among the choices. Finally, the error analysis shows that raters made the most mistakes for punctuation and conjunctions.- Anthology ID:
- 2022.emnlp-demos.17
- Volume:
- Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, UAE
- Editors:
- Wanxiang Che, Ekaterina Shutova
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 169–177
- Language:
- URL:
- https://aclanthology.org/2022.emnlp-demos.17
- DOI:
- 10.18653/v1/2022.emnlp-demos.17
- Cite (ACL):
- Sophia Chan, Swapna Somasundaran, Debanjan Ghosh, and Mengxuan Zhao. 2022. AGReE: A system for generating Automated Grammar Reading Exercises. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 169–177, Abu Dhabi, UAE. Association for Computational Linguistics.
- Cite (Informal):
- AGReE: A system for generating Automated Grammar Reading Exercises (Chan et al., EMNLP 2022)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2022.emnlp-demos.17.pdf