Modeling language learning using specialized Elo rating
Jue Hou, Koppatz Maximilian, José María Hoya Quecedo, Nataliya Stoyanova, Roman Yangarber
Abstract
Automatic assessment of the proficiency levels of the learner is a critical part of Intelligent Tutoring Systems. We present methods for assessment in the context of language learning. We use a specialized Elo formula used in conjunction with educational data mining. We simultaneously obtain ratings for the proficiency of the learners and for the difficulty of the linguistic concepts that the learners are trying to master. From the same data we also learn a graph structure representing a domain model capturing the relations among the concepts. This application of Elo provides ratings for learners and concepts which correlate well with subjective proficiency levels of the learners and difficulty levels of the concepts.- Anthology ID:
- W19-4451
- Volume:
- Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Helen Yannakoudakis, Ekaterina Kochmar, Claudia Leacock, Nitin Madnani, Ildikó Pilán, Torsten Zesch
- Venue:
- BEA
- SIG:
- SIGEDU
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 494–506
- Language:
- URL:
- https://aclanthology.org/W19-4451
- DOI:
- 10.18653/v1/W19-4451
- Cite (ACL):
- Jue Hou, Koppatz Maximilian, José María Hoya Quecedo, Nataliya Stoyanova, and Roman Yangarber. 2019. Modeling language learning using specialized Elo rating. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 494–506, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Modeling language learning using specialized Elo rating (Hou et al., BEA 2019)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/W19-4451.pdf