Abstract
Second Language Acquisition Modeling is the task to predict whether a second language learner would respond correctly in future exercises based on their learning history. In this paper, we propose a neural network based system to utilize rich contextual, linguistic and user information. Our neural model consists of a Context encoder, a Linguistic feature encoder, a User information encoder and a Format information encoder (CLUF). Furthermore, a decoder is introduced to combine such encoded features and make final predictions. Our system ranked in first place in the English track and second place in the Spanish and French track with an AUROC score of 0.861, 0.835 and 0.854 respectively.- Anthology ID:
- W18-0546
- 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:
- 374–380
- Language:
- URL:
- https://aclanthology.org/W18-0546
- DOI:
- 10.18653/v1/W18-0546
- Cite (ACL):
- Shuyao Xu, Jin Chen, and Long Qin. 2018. CLUF: a Neural Model for Second Language Acquisition Modeling. In Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 374–380, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- CLUF: a Neural Model for Second Language Acquisition Modeling (Xu et al., BEA 2018)
- PDF:
- https://preview.aclanthology.org/naacl-24-ws-corrections/W18-0546.pdf