Diverse Content Selection for Educational Question Generation
Amir Hadifar, Semere Kiros Bitew, Johannes Deleu, Veronique Hoste, Chris Develder, Thomas Demeester
Abstract
Question Generation (QG) systems have shown promising results in reducing the time and effort required to create questions for students. Typically, a first step in QG is to select the content to design a question for. In an educational setting, it is crucial that the resulting questions cover the most relevant/important pieces of knowledge the student should have acquired. Yet, current QG systems either consider just a single sentence or paragraph (thus do not include a selection step), or do not consider this educational viewpoint of content selection. Aiming to fill this research gap with a solution for educational document level QG, we thus propose to select contents for QG based on relevance and topic diversity. We demonstrate the effectiveness of our proposed content selection strategy for QG on 2 educational datasets. In our performance assessment, we also highlight limitations of existing QG evaluation metrics in light of the content selection problem.- Anthology ID:
- 2023.eacl-srw.13
- Volume:
- Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
- Month:
- May
- Year:
- 2023
- Address:
- Dubrovnik, Croatia
- Editors:
- Elisa Bassignana, Matthias Lindemann, Alban Petit
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 123–133
- Language:
- URL:
- https://aclanthology.org/2023.eacl-srw.13
- DOI:
- 10.18653/v1/2023.eacl-srw.13
- Cite (ACL):
- Amir Hadifar, Semere Kiros Bitew, Johannes Deleu, Veronique Hoste, Chris Develder, and Thomas Demeester. 2023. Diverse Content Selection for Educational Question Generation. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop, pages 123–133, Dubrovnik, Croatia. Association for Computational Linguistics.
- Cite (Informal):
- Diverse Content Selection for Educational Question Generation (Hadifar et al., EACL 2023)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2023.eacl-srw.13.pdf