UKP-SQuARE: An Interactive Tool for Teaching Question Answering

Haishuo Fang, Haritz Puerto, Iryna Gurevych


Abstract
The exponential growth of question answering (QA) has made it an indispensable topic in any Natural Language Processing (NLP) course. Additionally, the breadth of QA derived from this exponential growth makes it an ideal scenario for teaching related NLP topics such as information retrieval, explainability, and adversarial attacks among others. In this paper, we introduce UKP-SQuARE as a platform for QA education. This platform provides an interactive environment where students can run, compare, and analyze various QA models from different perspectives, such as general behavior, explainability, and robustness. Therefore, students can get a first-hand experience in different QA techniques during the class. Thanks to this, we propose a learner-centered approach for QA education in which students proactively learn theoretical concepts and acquire problem-solving skills through interactive exploration, experimentation, and practical assignments, rather than solely relying on traditional lectures. To evaluate the effectiveness of UKP-SQuARE in teaching scenarios, we adopted it in a postgraduate NLP course and surveyed the students after the course. Their positive feedback shows the platform’s effectiveness in their course and invites a wider adoption.
Anthology ID:
2023.bea-1.17
Volume:
Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Ekaterina Kochmar, Jill Burstein, Andrea Horbach, Ronja Laarmann-Quante, Nitin Madnani, Anaïs Tack, Victoria Yaneva, Zheng Yuan, Torsten Zesch
Venue:
BEA
SIG:
SIGEDU
Publisher:
Association for Computational Linguistics
Note:
Pages:
195–204
Language:
URL:
https://aclanthology.org/2023.bea-1.17
DOI:
10.18653/v1/2023.bea-1.17
Bibkey:
Cite (ACL):
Haishuo Fang, Haritz Puerto, and Iryna Gurevych. 2023. UKP-SQuARE: An Interactive Tool for Teaching Question Answering. In Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023), pages 195–204, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
UKP-SQuARE: An Interactive Tool for Teaching Question Answering (Fang et al., BEA 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.bea-1.17.pdf
Video:
 https://aclanthology.org/2023.bea-1.17.mp4