@inproceedings{chan-etal-2022-agree,
title = "{AGR}e{E}: A system for generating Automated Grammar Reading Exercises",
author = "Chan, Sophia and
Somasundaran, Swapna and
Ghosh, Debanjan and
Zhao, Mengxuan",
editor = "Che, Wanxiang and
Shutova, Ekaterina",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = dec,
year = "2022",
address = "Abu Dhabi, UAE",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.emnlp-demos.17",
doi = "10.18653/v1/2022.emnlp-demos.17",
pages = "169--177",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T AGReE: A system for generating Automated Grammar Reading Exercises
%A Chan, Sophia
%A Somasundaran, Swapna
%A Ghosh, Debanjan
%A Zhao, Mengxuan
%Y Che, Wanxiang
%Y Shutova, Ekaterina
%S Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F chan-etal-2022-agree
%X 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.
%R 10.18653/v1/2022.emnlp-demos.17
%U https://aclanthology.org/2022.emnlp-demos.17
%U https://doi.org/10.18653/v1/2022.emnlp-demos.17
%P 169-177
Markdown (Informal)
[AGReE: A system for generating Automated Grammar Reading Exercises](https://aclanthology.org/2022.emnlp-demos.17) (Chan et al., EMNLP 2022)
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.