TYPIC: A Corpus of Template-Based Diagnostic Comments on Argumentation
This addresses the time-consuming task of providing specific feedback for learners to develop critical thinking skills, but it is incremental as it focuses on feasibility rather than a full solution.
The paper tackles the problem of automating feedback on argumentation by formulating diagnostic comment generation as template selection and slot filling, and demonstrates feasibility through an annotation study with a publicly available corpus.
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.