Generating Adequate Distractors for Multiple-Choice Questions

Cheng Zhang, Yicheng Sun, Hejia Chen, Jie Wang

2020

Abstract

This paper presents a novel approach to automatic generation of adequate distractors for a given question-answer pair (QAP) generated from a given article to form an adequate multiple-choice question (MCQ). Our method is a combination of part-of-speech tagging, named-entity tagging, semantic-role labeling, regular expressions, domain knowledge bases, word embeddings, word edit distance, WordNet, and other algorithms. We use the US SAT (Scholastic Assessment Test) practice reading tests as a dataset to produce QAPs and generate three distractors for each QAP to form an MCQ. We show that, via experiments and evaluations by human judges, each MCQ has at least one adequate distractor and 84% of MCQs have three adequate distractors.

Paper Citation

in Harvard Style

Zhang C., Sun Y., Chen H. and Wang J. (2020). Generating Adequate Distractors for Multiple-Choice Questions. In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 1: KDIR; ISBN 978-989-758-474-9, SciTePress, pages 310-315. DOI: 10.5220/0010148303100315

in Bibtex Style

@conference{kdir20,
author={Cheng Zhang and Yicheng Sun and Hejia Chen and Jie Wang},
title={Generating Adequate Distractors for Multiple-Choice Questions},
booktitle={Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 1: KDIR},
year={2020},
pages={310-315},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010148303100315},
isbn={978-989-758-474-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 1: KDIR
TI - Generating Adequate Distractors for Multiple-Choice Questions
SN - 978-989-758-474-9
AU - Zhang C.
AU - Sun Y.
AU - Chen H.
AU - Wang J.
PY - 2020
SP - 310
EP - 315
DO - 10.5220/0010148303100315
PB - SciTePress