Textual complexity as a predictor of difficulty of listening items in language proficiency tests
Anastassia Loukina, Su-Youn Yoon, Jennifer Sakano, Youhua Wei, Kathy Sheehan
Abstract
In this paper we explore to what extent the difficulty of listening items in an English language proficiency test can be predicted by the textual properties of the prompt. We show that a system based on multiple text complexity features can predict item difficulty for several different item types and for some items achieves higher accuracy than human estimates of item difficulty.- Anthology ID:
- C16-1306
- Volume:
- Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
- Month:
- December
- Year:
- 2016
- Address:
- Osaka, Japan
- Editors:
- Yuji Matsumoto, Rashmi Prasad
- Venue:
- COLING
- SIG:
- Publisher:
- The COLING 2016 Organizing Committee
- Note:
- Pages:
- 3245–3253
- Language:
- URL:
- https://aclanthology.org/C16-1306
- DOI:
- Cite (ACL):
- Anastassia Loukina, Su-Youn Yoon, Jennifer Sakano, Youhua Wei, and Kathy Sheehan. 2016. Textual complexity as a predictor of difficulty of listening items in language proficiency tests. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 3245–3253, Osaka, Japan. The COLING 2016 Organizing Committee.
- Cite (Informal):
- Textual complexity as a predictor of difficulty of listening items in language proficiency tests (Loukina et al., COLING 2016)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/C16-1306.pdf