Discussion Tracker: Supporting Teacher Learning about Students’ Collaborative Argumentation in High School Classrooms

Luca Lugini, Christopher Olshefski, Ravneet Singh, Diane Litman, Amanda Godley


Abstract
Teaching collaborative argumentation is an advanced skill that many K-12 teachers struggle to develop. To address this, we have developed Discussion Tracker, a classroom discussion analytics system based on novel algorithms for classifying argument moves, specificity, and collaboration. Results from a classroom deployment indicate that teachers found the analytics useful, and that the underlying classifiers perform with moderate to substantial agreement with humans.
Anthology ID:
2020.coling-demos.10
Volume:
Proceedings of the 28th International Conference on Computational Linguistics: System Demonstrations
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Editors:
Michal Ptaszynski, Bartosz Ziolko
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics (ICCL)
Note:
Pages:
53–58
Language:
URL:
https://aclanthology.org/2020.coling-demos.10
DOI:
10.18653/v1/2020.coling-demos.10
Bibkey:
Cite (ACL):
Luca Lugini, Christopher Olshefski, Ravneet Singh, Diane Litman, and Amanda Godley. 2020. Discussion Tracker: Supporting Teacher Learning about Students’ Collaborative Argumentation in High School Classrooms. In Proceedings of the 28th International Conference on Computational Linguistics: System Demonstrations, pages 53–58, Barcelona, Spain (Online). International Committee on Computational Linguistics (ICCL).
Cite (Informal):
Discussion Tracker: Supporting Teacher Learning about Students’ Collaborative Argumentation in High School Classrooms (Lugini et al., COLING 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.coling-demos.10.pdf