Multiple Choice Question Generation Utilizing An Ontology

Katherine Stasaski, Marti A. Hearst


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.
Anthology ID:
W17-5034
Volume:
Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Editors:
Joel Tetreault, Jill Burstein, Claudia Leacock, Helen Yannakoudakis
Venue:
BEA
SIG:
SIGEDU
Publisher:
Association for Computational Linguistics
Note:
Pages:
303–312
Language:
URL:
https://aclanthology.org/W17-5034
DOI:
10.18653/v1/W17-5034
Bibkey:
Cite (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.
Cite (Informal):
Multiple Choice Question Generation Utilizing An Ontology (Stasaski & Hearst, BEA 2017)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingest-acl-2023-videos/W17-5034.pdf
Attachment:
 W17-5034.Attachment.zip