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題名 Using lexical constraints for corpus-based generation of multiple-choice cloze items
作者 劉昭麟
Liu, Chao-lin; Wang, Chun-Hung; Gao, Zhao-Ming
貢獻者 國立政治大學資訊科學系
關鍵詞 lexical constraints;corpus-based generation;multiple-choice cloze items
Computer-assisted language learning; Computer-assisted item
     generation; Advanced authoring systems; Natural language processing; Word sense
     disambiguation; Collocations; Selectional preferences
日期 2004-08
上傳時間 27-May-2010 16:48:23 (UTC+8)
摘要 Multiple-choice cloze items constitute a prominent tool for assessing students` competency in using the vocabulary of a language correctly. Without a proper estimation of students` competency in using vocabulary, it will be hard for a computer-assisted language learning system to provide course material tailored to each individual student`s needs. Computer-assisted item generation allows the creation of large-scale item pools and further supports Web-based learning and assessment. With the abundant text resources available on the Web, one can create cloze items that cover a wide range of topics, thereby achieving usability, diversity and security of the item pool. One can apply keyword-based techniques like concordancing that extract sentences from the Web, and retain those sentences that contain the desired keyword to produce cloze items. However, such techniques fail to consider the fact that many words in natural languages are polysemous so that the recommended sentences typically include a non-negligible number of irrelevant sentences. In addition, a substantial amount of labor is required to look for those sentences in which the word to be tested really carries the sense of interest. We propose a novel word sense disambiguation-based method for locating sentences in which designated words carry specific senses, and apply generalized collocation-based methods to select distractors that are needed for multiple-choice cloze items. Experimental results indicated that our system was able to produce a usable cloze item for every 1.6 items it returned.
關聯 Computational Linguistics and Chinese Language Processing , Vol. 10, No. 3, September 2005, pp. 303-328
資料類型 conference
dc.contributor 國立政治大學資訊科學系en_US
dc.creator (作者) 劉昭麟zh_TW
dc.creator (作者) Liu, Chao-lin; Wang, Chun-Hung; Gao, Zhao-Ming-
dc.date (日期) 2004-08en_US
dc.date.accessioned 27-May-2010 16:48:23 (UTC+8)-
dc.date.available 27-May-2010 16:48:23 (UTC+8)-
dc.date.issued (上傳時間) 27-May-2010 16:48:23 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/39677-
dc.description.abstract (摘要) Multiple-choice cloze items constitute a prominent tool for assessing students` competency in using the vocabulary of a language correctly. Without a proper estimation of students` competency in using vocabulary, it will be hard for a computer-assisted language learning system to provide course material tailored to each individual student`s needs. Computer-assisted item generation allows the creation of large-scale item pools and further supports Web-based learning and assessment. With the abundant text resources available on the Web, one can create cloze items that cover a wide range of topics, thereby achieving usability, diversity and security of the item pool. One can apply keyword-based techniques like concordancing that extract sentences from the Web, and retain those sentences that contain the desired keyword to produce cloze items. However, such techniques fail to consider the fact that many words in natural languages are polysemous so that the recommended sentences typically include a non-negligible number of irrelevant sentences. In addition, a substantial amount of labor is required to look for those sentences in which the word to be tested really carries the sense of interest. We propose a novel word sense disambiguation-based method for locating sentences in which designated words carry specific senses, and apply generalized collocation-based methods to select distractors that are needed for multiple-choice cloze items. Experimental results indicated that our system was able to produce a usable cloze item for every 1.6 items it returned.-
dc.language en-USen_US
dc.language.iso en_US-
dc.relation (關聯) Computational Linguistics and Chinese Language Processing , Vol. 10, No. 3, September 2005, pp. 303-328en_US
dc.subject (關鍵詞) lexical constraints;corpus-based generation;multiple-choice cloze itemsen_US
dc.subject (關鍵詞) Computer-assisted language learning; Computer-assisted item
     generation; Advanced authoring systems; Natural language processing; Word sense
     disambiguation; Collocations; Selectional preferences
-
dc.title (題名) Using lexical constraints for corpus-based generation of multiple-choice cloze itemsen_US
dc.type (資料類型) conferenceen