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    <abstract>Ontologies provide a structured representation of concepts and the relationships which connect them. This work investigates how a pre-existing educational Biology ontology can be used to generate useful practice questions for students by using the connectivity structure in a novel way. It also introduces a novel way to generate multiple-choice distractors from the ontology, and compares this to a baseline of using embedding representations of nodes. An assessment by an experienced science teacher shows a significant advantage over a baseline when using the ontology for distractor generation. A subsequent study with three science teachers on the results of a modified question generation algorithm finds significant improvements. An in-depth analysis of the teachers’ comments yields useful insights for any researcher working on automated question generation for educational applications.</abstract>
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%0 Conference Proceedings
%T Multiple Choice Question Generation Utilizing An Ontology
%A Stasaski, Katherine
%A Hearst, Marti A.
%Y Tetreault, Joel
%Y Burstein, Jill
%Y Leacock, Claudia
%Y Yannakoudakis, Helen
%S Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F stasaski-hearst-2017-multiple
%X Ontologies provide a structured representation of concepts and the relationships which connect them. This work investigates how a pre-existing educational Biology ontology can be used to generate useful practice questions for students by using the connectivity structure in a novel way. It also introduces a novel way to generate multiple-choice distractors from the ontology, and compares this to a baseline of using embedding representations of nodes. An assessment by an experienced science teacher shows a significant advantage over a baseline when using the ontology for distractor generation. A subsequent study with three science teachers on the results of a modified question generation algorithm finds significant improvements. An in-depth analysis of the teachers’ comments yields useful insights for any researcher working on automated question generation for educational applications.
%R 10.18653/v1/W17-5034
%U https://aclanthology.org/W17-5034/
%U https://doi.org/10.18653/v1/W17-5034
%P 303-312

Markdown (Informal)

[Multiple Choice Question Generation Utilizing An Ontology](https://aclanthology.org/W17-5034/) (Stasaski & Hearst, BEA 2017)

• Multiple Choice Question Generation Utilizing An Ontology (Stasaski & Hearst, BEA 2017)

ACL

• Katherine Stasaski and Marti A. Hearst. 2017. Multiple Choice Question Generation Utilizing An Ontology. In Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications, pages 303–312, Copenhagen, Denmark. Association for Computational Linguistics.