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Candidate Evaluation Strategies for Improved Difficulty Prediction of Language Tests

Beinborn, Lisa ; Zesch, Torsten ; Gurevych, Iryna (2015)
Candidate Evaluation Strategies for Improved Difficulty Prediction of Language Tests.
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Language proficiency tests are a useful tool for evaluating learner progress, if the test difficulty fits the level of the learner. In this work, we describe a generalized framework for test difficulty prediction that is applicable to several languages and test types. In addition, we develop two ranking strategies for candidate evaluation inspired by automatic solving methods based on language model probability and semantic relatedness. These ranking strategies lead to significant improvements for the difficulty prediction of cloze tests.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2015
Autor(en): Beinborn, Lisa ; Zesch, Torsten ; Gurevych, Iryna
Art des Eintrags: Bibliographie
Titel: Candidate Evaluation Strategies for Improved Difficulty Prediction of Language Tests
Sprache: Englisch
Publikationsjahr: 2015
Buchtitel: Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications held in conjunction with NAACL 2015
URL / URN: http://aclweb.org/anthology/W15-0601
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Kurzbeschreibung (Abstract):

Language proficiency tests are a useful tool for evaluating learner progress, if the test difficulty fits the level of the learner. In this work, we describe a generalized framework for test difficulty prediction that is applicable to several languages and test types. In addition, we develop two ranking strategies for candidate evaluation inspired by automatic solving methods based on language model probability and semantic relatedness. These ranking strategies lead to significant improvements for the difficulty prediction of cloze tests.

Freie Schlagworte: Educational Natural Language Processing;UKP_a_WALL;UKP_reviewed;UKP_p_AutoExerGen
ID-Nummer: TUD-CS-2015-0066
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung
Hinterlegungsdatum: 31 Dez 2016 14:29
Letzte Änderung: 24 Jan 2020 12:03
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