Second Language Acquisition Modeling
Burr Settles, Chris Brust, Erin Gustafson, Masato Hagiwara, Nitin Madnani
Abstract
We present the task of second language acquisition (SLA) modeling. Given a history of errors made by learners of a second language, the task is to predict errors that they are likely to make at arbitrary points in the future. We describe a large corpus of more than 7M words produced by more than 6k learners of English, Spanish, and French using Duolingo, a popular online language-learning app. Then we report on the results of a shared task challenge aimed studying the SLA task via this corpus, which attracted 15 teams and synthesized work from various fields including cognitive science, linguistics, and machine learning.- Anthology ID:
- W18-0506
- Volume:
- Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Editors:
- Joel Tetreault, Jill Burstein, Ekaterina Kochmar, Claudia Leacock, Helen Yannakoudakis
- Venue:
- BEA
- SIG:
- SIGEDU
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 56–65
- Language:
- URL:
- https://aclanthology.org/W18-0506
- DOI:
- 10.18653/v1/W18-0506
- Cite (ACL):
- Burr Settles, Chris Brust, Erin Gustafson, Masato Hagiwara, and Nitin Madnani. 2018. Second Language Acquisition Modeling. In Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 56–65, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- Second Language Acquisition Modeling (Settles et al., BEA 2018)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W18-0506.pdf
- Data
- Duolingo SLAM Shared Task