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Autor*innen: Beinborn, Lisa; Zesch, Torsten; Gurevych, Iryna
Titel: Predicting the difficulty of language proficiency tests
In: Transactions of the Association for Computational Linguistics, 2 (2014) , S. 517-529
URL: http://tacl2013.cs.columbia.edu/ojs/index.php/tacl/article/view/414/88
Dokumenttyp: 3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Sprache: Englisch
Schlagwörter: Computerlinguistik; Datenanalyse; Deutschland; Fremdsprache; Kenntnisse; Lernerfolg; Prognose; Schwierigkeit; Sprachfertigkeit; Sprachtest; Student; Verfahren
Abstract: Language proficiency tests are used to evaluate and compare the progress of language learners. We present an approach for automatic difficulty prediction of C-tests that performs on par with human experts. On the basis of detailed analysis of newly collected data, we develop a model for C-test difficulty introducing four dimensions: solution difficulty, candidate ambiguity, inter-gap dependency, and paragraph difficulty. We show that cues from all four dimensions contribute to C-test difficulty. (DIPF/Org.)
DIPF-Abteilung: Informationszentrum Bildung