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Autor:
Beinborn, Lisa; Zesch, Torsten; Gurevych, Iryna:

Titel:
Predicting the difficulty of language proficiency tests

Quelle:
In: Transactions of the Association for Computational Linguistics, 2 (2014) , 517-529

URL des Volltextes:
http://tacl2013.cs.columbia.edu/ojs/index.php/tacl/article/view/414/88

Sprache:
Englisch

Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)

Schlagwörter:
Computerlinguistik, Datenanalyse, Deutschland, Fremdsprache, Kenntnisse, Lernerfolg, Prognose, Schwierigkeit, Sprachfertigkeit, Sprachtest, Student, Verfahren


Abstract(original):
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.)


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last modified Nov 11, 2016