2015 · 32 citations · 11 references
ComputingComputer ScienceEnglishNatural Language ProcessingTest ConstructionTest DevelopmentLanguage AssessmentLanguage ModelingQuestion AnsweringSecond Language AcquisitionText GenerationVocabulary AssessmentMultiple-choice Question AnsweringQuestion Answering SystemsQuestion Answering Systems EvaluationQuestion GenerationVocabulary Test Development
This paper presents a novel method for automatically generating English vocabulary tests using TOEFL vo- cabulary questions as a model. English vocabulary questions in TOEFL is a multiple-choice question con- sisting of four components: a target word, a reading passage, a correct answer and distractors. Given a target word, we generate a reading passage from Web texts retrieved from the Internet, and then employ that read- ing passage and the WordNet lexical dictionary for generating question options, both the correct answer and distractors. Human evaluation indicated that 45% of the responses from English teachers mistakenly judged the automatically generated questions by the proposed method to be human-generated questions. In addition, half of the machine-generated questions were received average rating more than or equals than 3 in 5 point scale. This suggests that our machine-generated questions succeeded in capturing some characteristics of the human-generated questions, and half of them can be used for English test.
11
George A. Miller · Communications of the ACM · 1995 · 14.1K citations · Full text
Verbs semantics and lexical selection
Zhibiao Wu, Martha Palmer · 1994 · 3.1K citations · Full text
Automatic sense disambiguation using machine readable dictionaries
Michael Lesk · 1986 · 1.8K citations · Full text