Abstract
We present our submission to the 2018 Duolingo Shared Task on Second Language Acquisition Modeling (SLAM). We focus on evaluating a range of features for the task, including user-derived measures, while examining how far we can get with a simple linear classifier. Our analysis reveals that errors differ per exercise format, which motivates our final and best-performing system: a task-wise (per exercise-format) model.
Cite
CITATION STYLE
Klerke, S., Alonso, H. M., & Plank, B. (2018). Grotoco@SLAM: Second language acquisition modeling with simple features, learners and task-wise models. In Proceedings of the 13th Workshop on Innovative Use of NLP for Building Educational Applications, BEA 2018 at the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HTL 2018 (pp. 206–211). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w18-0523
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
