Multiple choice question generation utilizing an ontology

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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.

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APA

Stasaski, K., & Hearst, M. (2017). Multiple choice question generation utilizing an ontology. In EMNLP 2017 - 12th Workshop on Innovative Use of NLP for Building Educational Applications, BEA 2017 - Proceedings of the Workshop (pp. 303–312). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w17-5034

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