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    <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.</abstract>
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%0 Conference Proceedings
%T Learning to Automatically Generate Fill-In-The-Blank Quizzes
%A Marrese-Taylor, Edison
%A Nakajima, Ai
%A Matsuo, Yutaka
%A Yuichi, Ono
%Y Tseng, Yuen-Hsien
%Y Chen, Hsin-Hsi
%Y Ng, Vincent
%Y Komachi, Mamoru
%S Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F marrese-taylor-etal-2018-learning
%X 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.
%R 10.18653/v1/W18-3722
%U https://aclanthology.org/W18-3722/
%U https://doi.org/10.18653/v1/W18-3722
%P 152-156

Markdown (Informal)

[Learning to Automatically Generate Fill-In-The-Blank Quizzes](https://aclanthology.org/W18-3722/) (Marrese-Taylor et al., NLP-TEA 2018)

• Learning to Automatically Generate Fill-In-The-Blank Quizzes (Marrese-Taylor et al., NLP-TEA 2018)

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.