Authors:
Yuni Susanti
1
;
Ryu Iida
2
and
Takenobu Tokunaga
1
Affiliations:
1
Tokyo Institute of Technology, Japan
;
2
National Institute of Informations and Communication Technology, Japan
Keyword(s):
Automatic Question Generation, English Vocabulary Test, Word Sense Disambiguation, Multiple-choice Question, TOEFL Vocabulary Test.
Related
Ontology
Subjects/Areas/Topics:
Authoring Tools and Content Development
;
Computer-Supported Education
;
e-Learning
;
Information Technologies Supporting Learning
Abstract:
This paper presents a novel method for automatically generating English vocabulary tests using TOEFL vocabulary
questions as a model. English vocabulary questions in TOEFL is a multiple-choice question consisting
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 reading
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 t
hem can be used for English test.
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