Learning to Automatically Generate Fill-In-The-Blank Quizzes
Edison Marrese-Taylor, Ai Nakajima, Yutaka Matsuo, Ono Yuichi
Abstract
In this paper we formalize the problem automatic fill-in-the-blank question generation using two standard NLP machine learning schemes, proposing concrete deep learning models for each. We present an empirical study based on data obtained from a language learning platform showing that both of our proposed settings offer promising results.- Anthology ID:
- W18-3722
- Volume:
- Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Editors:
- Yuen-Hsien Tseng, Hsin-Hsi Chen, Vincent Ng, Mamoru Komachi
- Venue:
- NLP-TEA
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 152–156
- Language:
- URL:
- https://aclanthology.org/W18-3722
- DOI:
- 10.18653/v1/W18-3722
- Cite (ACL):
- Edison Marrese-Taylor, Ai Nakajima, Yutaka Matsuo, and Ono Yuichi. 2018. Learning to Automatically Generate Fill-In-The-Blank Quizzes. In Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications, pages 152–156, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- Learning to Automatically Generate Fill-In-The-Blank Quizzes (Marrese-Taylor et al., NLP-TEA 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W18-3722.pdf