@inproceedings{schaller-etal-2024-darius,
    title = "{DARIUS}: A Comprehensive Learner Corpus for Argument Mining in {G}erman-Language Essays",
    author = {Schaller, Nils-Jonathan  and
      Horbach, Andrea  and
      H{\"o}ft, Lars Ingver  and
      Ding, Yuning  and
      Bahr, Jan Luca  and
      Meyer, Jennifer  and
      Jansen, Thorben},
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2024.lrec-main.389/",
    pages = "4356--4367",
    abstract = "In this paper, we present the DARIUS (Digital Argumentation Instruction for Science) corpus for argumentation quality on 4589 essays written by 1839 German secondary school students. The corpus is annotated according to a fine-grained annotation scheme, ranging from a broader perspective like content zones, to more granular features like argumentation coverage/reach and argumentative discourse units like claims and warrants. The features have inter-annotator agreements up to 0.83 Krippendorff`s {\ensuremath{\alpha}}. The corpus and dataset are publicly available for further research in argument mining."
}