Computer-aided generation of multiple-choice tests
HLT-NAACL-EDUC '03 Proceedings of the HLT-NAACL 03 workshop on Building educational applications using natural language processing - Volume 2
Applications of lexical information for algorithmically composing multiple-choice cloze items
EdAppsNLP 05 Proceedings of the second workshop on Building Educational Applications Using NLP
A real-time multiple-choice question generation for language testing: a preliminary study
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GenERRate: generating errors for use in grammatical error detection
EdAppsNLP '09 Proceedings of the Fourth Workshop on Innovative Use of NLP for Building Educational Applications
Bootstrapping multiple-choice tests with THE-MENTOR
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part I
A cloze test authoring system and its automation
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AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
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This paper introduces a method for the semi-automatic generation of grammar test items by applying Natural Language Processing (NLP) techniques. Based on manually-designed patterns, sentences gathered from the Web are transformed into tests on grammaticality. The method involves representing test writing knowledge as test patterns, acquiring authentic sentences on the Web, and applying generation strategies to transform sentences into items. At runtime, sentences are converted into two types of TOEFL-style question: multiple-choice and error detection. We also describe a prototype system FAST (Free Assessment of Structural Tests). Evaluation on a set of generated questions indicates that the proposed method performs satisfactory quality. Our methodology provides a promising approach and offers significant potential for computer assisted language learning and assessment.