Abstract
We propose two novel manipulation strategies for increasing and decreasing the difficulty of C-tests automatically. This is a crucial step towards generating learner-adaptive exercises for self-directed language learning and preparing language assessment tests. To reach the desired difficulty level, we manipulate the size and the distribution of gaps based on absolute and relative gap difficulty predictions. We evaluate our approach in corpus-based experiments and in a user study with 60 participants. We find that both strategies are able to generate C-tests with the desired difficulty level.- Anthology ID:
- P19-1035
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Anna Korhonen, David Traum, Lluís Màrquez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 360–370
- Language:
- URL:
- https://aclanthology.org/P19-1035
- DOI:
- 10.18653/v1/P19-1035
- Cite (ACL):
- Ji-Ung Lee, Erik Schwan, and Christian M. Meyer. 2019. Manipulating the Difficulty of C-Tests. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 360–370, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Manipulating the Difficulty of C-Tests (Lee et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/P19-1035.pdf
- Code
- UKPLab/acl2019-ctest-difficulty-manipulation