Article | Proceedings of the third workshop on NLP for computer-assisted language learning at SLTC 2014, Uppsala University | Towards Automatic Scoring of Cloze Items by Selecting Low-Ambiguity Contexts
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Title:
Towards Automatic Scoring of Cloze Items by Selecting Low-Ambiguity Contexts
Author:
Tobias Horsmann: Language Technology Lab, University of Duisburg-Essen, Germany Torsten Zesch: Language Technology Lab, University of Duisburg-Essen, Germany
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Full text (pdf)
Year:
2014
Conference:
Proceedings of the third workshop on NLP for computer-assisted language learning at SLTC 2014, Uppsala University
Issue:
107
Article no.:
003
Pages:
33–42
No. of pages:
10
Publication type:
Abstract and Fulltext
Published:
2014-11-11
ISBN:
978-91-7519-175-1
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Series:
NEALT Proceedings Series
Publisher:
Linköping University Electronic Press, Linköpings universitet


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In second language learning, cloze tests (also known as fill-in-the-blank tests) are frequently used for assessing the learning progress of students. While preparation effort for these tests is low, scoring needs to be done manually, as there usually is a huge number of correct solutions. In this paper, we examine whether the ambiguity of cloze items can be lowered to a point where automatic scoring becomes possible. We utilize the local context of a word to collect evidence of low-ambiguity. We do that by seeking for collocated word sequences, but also taking structural information on sentence level into account. We evaluate the effectiveness of our method in a user study on cloze items ranked by our method. For the top-ranked items (lowest ambiguity) the subjects provide the target word significantly more often than for the bottom-ranked items (59.9% vs. 36.5%). While this shows the potential of our method, we did not succeed in fully eliminating ambiguity. Thus, further research is necessary before fully automatic scoring becomes possible.

Keywords: cloze tests; language proficiency tests; automatic scoring

Proceedings of the third workshop on NLP for computer-assisted language learning at SLTC 2014, Uppsala University

Author:
Tobias Horsmann, Torsten Zesch
Title:
Towards Automatic Scoring of Cloze Items by Selecting Low-Ambiguity Contexts
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Proceedings of the third workshop on NLP for computer-assisted language learning at SLTC 2014, Uppsala University

Author:
Tobias Horsmann, Torsten Zesch
Title:
Towards Automatic Scoring of Cloze Items by Selecting Low-Ambiguity Contexts
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