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Evaluation of automatically generated English vocabulary questions

This paper describes details of the evaluation experiments for questions created by an automatic question generation system. Given a target word and one of its word senses, the system generates a multiple-choice English vocabulary question asking for the closest in meaning to the target word in the...

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Detalles Bibliográficos
Autores principales: Susanti, Yuni, Tokunaga, Takenobu, Nishikawa, Hitoshi, Obari, Hiroyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6302865/
https://www.ncbi.nlm.nih.gov/pubmed/30613260
http://dx.doi.org/10.1186/s41039-017-0051-y
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author Susanti, Yuni
Tokunaga, Takenobu
Nishikawa, Hitoshi
Obari, Hiroyuki
author_facet Susanti, Yuni
Tokunaga, Takenobu
Nishikawa, Hitoshi
Obari, Hiroyuki
author_sort Susanti, Yuni
collection PubMed
description This paper describes details of the evaluation experiments for questions created by an automatic question generation system. Given a target word and one of its word senses, the system generates a multiple-choice English vocabulary question asking for the closest in meaning to the target word in the reading passage. Two kinds of evaluation were conducted considering two aspects: (1) measuring English learners’ proficiency and (2) their similarity to the human-made questions. The first evaluation is based on the responses from English learners obtained through administering the machine-generated and human-made questions to them, and the second is based on the subjective judgement by English teachers. Both evaluations showed that the machine-generated questions were able to achieve a comparable level with the human-made questions in both measuring English proficiency and similarity.
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spelling pubmed-63028652019-01-04 Evaluation of automatically generated English vocabulary questions Susanti, Yuni Tokunaga, Takenobu Nishikawa, Hitoshi Obari, Hiroyuki Res Pract Technol Enhanc Learn Research This paper describes details of the evaluation experiments for questions created by an automatic question generation system. Given a target word and one of its word senses, the system generates a multiple-choice English vocabulary question asking for the closest in meaning to the target word in the reading passage. Two kinds of evaluation were conducted considering two aspects: (1) measuring English learners’ proficiency and (2) their similarity to the human-made questions. The first evaluation is based on the responses from English learners obtained through administering the machine-generated and human-made questions to them, and the second is based on the subjective judgement by English teachers. Both evaluations showed that the machine-generated questions were able to achieve a comparable level with the human-made questions in both measuring English proficiency and similarity. Springer Singapore 2017-03-07 2017 /pmc/articles/PMC6302865/ /pubmed/30613260 http://dx.doi.org/10.1186/s41039-017-0051-y Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Susanti, Yuni
Tokunaga, Takenobu
Nishikawa, Hitoshi
Obari, Hiroyuki
Evaluation of automatically generated English vocabulary questions
title Evaluation of automatically generated English vocabulary questions
title_full Evaluation of automatically generated English vocabulary questions
title_fullStr Evaluation of automatically generated English vocabulary questions
title_full_unstemmed Evaluation of automatically generated English vocabulary questions
title_short Evaluation of automatically generated English vocabulary questions
title_sort evaluation of automatically generated english vocabulary questions
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6302865/
https://www.ncbi.nlm.nih.gov/pubmed/30613260
http://dx.doi.org/10.1186/s41039-017-0051-y
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