Fine-grained essay scoring of a complex writing task for native speakers

Horbach, Andrea; Scholten-Akoun, Dirk; Ding, Yuning; Zesch, Torsten

doi:10.18653/v1/W17-5040

Tagungsbeitrag 2017 CC BY 4.0

Veröffentlicht

Fine-grained essay scoring of a complex writing task for native speakers

Horbach, Andrea ; Scholten-Akoun, Dirk ; Ding, Yuning ; Zesch, Torsten

Automatic essay scoring is nowadays successfully used even in high-stakes tests, but this is mainly limited to holistic scoring of learner essays. We present a new dataset of essays written by highly proficient German native speakers that is scored using a fine-grained rubric with the goal to provide detailed feedback. Our experiments with two state-of-the-art scoring systems (a neural and a SVM-based one) show a large drop in performance compared to existing datasets. This demonstrates the need for such datasets that allow to guide research on more elaborate essay scoring methods.

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Einordnung

Konferenz:: 12th Workshop on Innovative Use of NLP for Building Educational Applications, September 8, 2017 Copenhagen, Denmark
Datum der Veröffentlichung:: 2017
URN:: urn:nbn:de:hbz:464-20211130-095223-4
DOI:: 10.18653/v1/W17-5040
Sprache:: Englisch
Ressourcentyp:: Text
Kollektion:: E-Publikationen
Sachgruppen der Deutschen Nationalbibliographie:: 004 Informatik
Link URL:: https://www.aclweb.org/anthology/W17-5040
Einrichtung:: Fakultät für Ingenieurwissenschaften, Informatik und Angewandte Kognitionswissenschaft, Informatik, Sprachtechnologie
Abgrenzungspolitik:: Horbach, Andrea et al. (2017): Fine-grained essay scoring of a complex writing task for native speakers. In: Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications, pp. 357-366. Association for Computational Linguistics. DOI: 10.18653/v1/W17-5040