Distractor Generation for Fill-in-the-Blank Exercises by Question Type

Nana Yoshimi, Tomoyuki Kajiwara, Satoru Uchida, Yuki Arase, Takashi Ninomiya

Abstract
This study addresses the automatic generation of distractors for English fill-in-the-blank exercises in the entrance examinations for Japanese universities. While previous studies applied the same method to all questions, actual entrance examinations have multiple question types that reflect the purpose of the questions. Therefore, we define three types of questions (grammar, function word, and context) and propose a method to generate distractors according to the characteristics of each question type. Experimental results on 500 actual questions show the effectiveness of the proposed method for both automatic and manual evaluation.
Anthology ID:
2023.acl-srw.38
Volume:
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Vishakh Padmakumar, Gisela Vallejo, Yao Fu
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
276–281
Language:
URL:
https://aclanthology.org/2023.acl-srw.38
DOI:
10.18653/v1/2023.acl-srw.38
Bibkey:
Cite (ACL):
Nana Yoshimi, Tomoyuki Kajiwara, Satoru Uchida, Yuki Arase, and Takashi Ninomiya. 2023. Distractor Generation for Fill-in-the-Blank Exercises by Question Type. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop), pages 276–281, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Distractor Generation for Fill-in-the-Blank Exercises by Question Type (Yoshimi et al., ACL 2023)
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PDF:
https://preview.aclanthology.org/dois-2013-emnlp/2023.acl-srw.38.pdf
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