Shintaro Sawada


2022

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TYPIC: A Corpus of Template-Based Diagnostic Comments on Argumentation
Shoichi Naito | Shintaro Sawada | Chihiro Nakagawa | Naoya Inoue | Kenshi Yamaguchi | Iori Shimizu | Farjana Sultana Mim | Keshav Singh | Kentaro Inui
Proceedings of the Thirteenth Language Resources and Evaluation Conference

Providing feedback on the argumentation of the learner is essential for developing critical thinking skills, however, it requires a lot of time and effort. To mitigate the overload on teachers, we aim to automate a process of providing feedback, especially giving diagnostic comments which point out the weaknesses inherent in the argumentation. It is recommended to give specific diagnostic comments so that learners can recognize the diagnosis without misinterpretation. However, it is not obvious how the task of providing specific diagnostic comments should be formulated. We present a formulation of the task as template selection and slot filling to make an automatic evaluation easier and the behavior of the model more tractable. The key to the formulation is the possibility of creating a template set that is sufficient for practical use. In this paper, we define three criteria that a template set should satisfy: expressiveness, informativeness, and uniqueness, and verify the feasibility of creating a template set that satisfies these criteria as a first trial. We will show that it is feasible through an annotation study that converts diagnostic comments given in a text to a template format. The corpus used in the annotation study is publicly available.