A Corpus for Argumentative Writing Support in German
Journal
International Conference on Computational Linguistics (COLING)
Type
conference paper
Date Issued
2020
Research Team
IWI6
Abstract
In this paper, we present a novel annotation approach to capture claims and premises of arguments and their relations in student-written persuasive peer reviews on business models in German language. We propose an annotation scheme based on annotation guidelines that allows to model claims and premises as well as support and attack relations for capturing the structure of argumentative discourse in student-written peer reviews. We conduct an annotation study with three annotators on 50 persuasive essays to evaluate our annotation scheme. The obtained inter-rater agreement of α = 0.57 for argument components and α = 0.49 for argumentative relations indicates that the proposed annotation scheme successfully guides annotators to moderate agreement. Finally, we present our freely available corpus of 1,000 persuasive student-written peer reviews on business models and our annotation guidelines to encourage future research on the design and development of argumentative writing support systems for students.
Language
English
Keywords
adaptive learning
argumentation learning
argumentation mining
corpus development
HSG Classification
contribution to scientific community
Event Title
International Conference on Computational Linguistics (COLING)
Event Location
Barcelona, Spain
Event Date
08.12.20. - 13.12.20
Subject(s)
Eprints ID
261296
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