UKP-SQuARE: An Interactive Tool for Teaching Question Answering
This provides a tool for educators and students in NLP education to enhance learning through hands-on experience, though it is incremental as it applies existing QA models in a new educational context.
The paper tackles the challenge of teaching question answering (QA) in NLP courses by introducing UKP-SQuARE, an interactive platform that allows students to run, compare, and analyze QA models, with positive feedback from a postgraduate course survey showing its effectiveness.
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.