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題名 英文聽力字彙與聽寫練習題輔助出題系統之研究
Computer-Assisted Item Generation for Listening Cloze and Dictation Practice in English
作者 黃上銘
Huang, Shang-Ming
貢獻者 劉昭麟
Liu, Chao-Lin
黃上銘
Huang, Shang-Ming
關鍵詞 電腦輔助教學
自然語言處理
線上測驗
聽力克漏字
聽寫測驗
Computer-Assited Learning
Natural language processing
Web-based test
listening cloze
dictatioin test
日期 2004
上傳時間 17-Sep-2009 13:54:11 (UTC+8)
摘要 以Web為基礎的語言測驗（Web-based language test）目前多為靜態網頁或是互動性低的動態網頁，如何提昇測驗系統的互動性，仍有待探討。目前已有學者利用自然語言處理技術來自動產生試題，並分析學生的作答錯誤。然而，相關研究仍多著重於字彙測驗與文法評量上。本研究針對聽力測驗，發展一套線上練習系統，並運用自然語言處理技術來自動產生聽力選擇題，以及分析學生的聽寫錯誤。我們分析語料庫中的詞彙，將發音相近的單字歸為一類，系統要產生聽力選擇題時，即從單字所屬的群組中，隨機挑選其他發音相近的單字當作誘答選項。而在分析聽寫錯誤方面，我們從語尾變化、拼字、拼音三種層次來分析學生的作答；系統批改完後，會按照學生的錯誤類型，提供不同種類的練習。本練習系統共有聽寫測驗、單字聽力選擇題、單字組聽力選擇題三種題型。系統可以輔助教師大量地編製試題與測驗，並輔助批改學生的作答。學生則可透過網路來接受測驗，並針對自己的弱點單字來作練習。
Most Web-based language tests are presently static pages or dynamic pages with low interactivity. How to enhance the interactivity of the test systems is still under development. Today some researchers have utilized natural language processing techniques for automatic item generation and intelligent error analysis of students’ answers. However, most known research works put more emphases on vocabulary tests and grammar correction. In this paper, we propose a Web-based practice system for English dictation and listening cloze. We use natural language processing techniques to automatically generate multiple-choice item and analyze students’ dictation errors. First, we analyze the words in the corpus and group them based on the similarity of the phones. When the system generates multiple-choice items, it will search the matched cluster and randomly pick other words with similar phones. Second, we analyze students’ dictation from three aspects: inflected form, spelling errors and phoneme structures. After analyzing students’ answers, the system will provide different practice items according to the error types. Our practice system has three item types: one for dictation and two for multiple-choice listening cloze. The system can assist teachers in authoring items and grading the test results. Students can take the test through the Internet and practice on their weak words.
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[2] 王美燕，國中學生英語字彙測驗錯誤分析，國立高雄師範大學教育研究所碩士論文，民國82年。
[3] 王俊弘，電腦輔助克漏詞多選題出題系統之研究，國立政治大學資訊科學研究所碩士論文，民國93年。
[4] 光華雜誌，http://www.sinorama.com.tw/。
[5] 何榮桂，「電腦化題庫設計的基本架構」，教育研究月刊，第20期，21-26頁，民國80年。
[6] 周文正，「WWW上電腦輔助測試系統之研製」，中華民國第七屆電腦輔助教學研討會，http://thccx5.cc.nthu.edu.tw/wjchou/tecpaper/w3cat/index.html，民國87年。
[7] 林裕集，適用於電腦教室之網路測驗系統：以國小英語科為例，國立台中師範學院教育測驗統計研究所碩士論文，民國90年6月。
[8] 國立暨南大學網路多媒體教室，http://english.csie.ncnu.edu.tw/index.php。
[9] 張心怡，英語線上適性測驗於企業徵才之探討，義守大學資訊管理研究所碩士論文，民國92年7月。
[10] 經典傳訊編輯部，再造英語大革命－聽力，經典傳訊，民國90年2月。
[11] 謝欽舜，自然發音的十個規則，凱信企業管理顧問有限公司，民國91年12月。
[12] AT&T Natural Voice, http://www.naturalvoices.att.com/.
[13] Bellman, R., Holland, J. & Kalaba, R. (1959). On an application of dynamic programming to the synthesis of logical systems. Journal of the ACM, 6(4), 486-493.
[14] Berger, A. L., Della Pietra, S. A. & Della Pietra, V. J. (1996). A maximum entropy approach to natural language processing. Computational Linguistics, 22(1), 39-71.
[15] Berk, E. J. & Ananian, C. S. (2003) JLex: A Lexical Analyzer Generator for JAVA™. http://www.cs.princeton.edu/~appel/modern/java/JLex/.
[16] Binet, A. & Simon (1905). Méthodes nouvelles pour le diagnostic du niveau intellectual des anormaux. Année psychol, 11, 91-244.
[17] Bouma, G. (2000). A finite state and data-oriented method for grapheme to phoneme conversion. Proceedings of the 1st conference on North American chapter of the Association for Computational Linguistics, 303-310.
[18] Brill, E. (1995). Transformation-based error-driven learning and natural language processing: A case study in part-of-speech tagging. Computational Linguistics, 21, 543-566.
[19] Brusilovsky, P. (1999). Adaptive and intelligent technologies for Web-based education. KI - Kunstliche Intelligenz, 13(4), 19-25.
[20] China Post, http://www.chinapost.com.tw/
[21] Coniam, D. (1997). A preliminary inquiry into using corpus word frequency data in the automatic generation of English cloze tests. CALICO Journal, 16(2-4), 15-33.
[22] Conaim, D. (1998). Interactive evaluation of listening comprehension: How the context may help. Computer Assisted Language Learning, 11(1), 35-53.
[23] Daelemans, W., Bosh, A. van den. (2001). TreeTalk: memory-based word phonemisation. R. I. Damper (Ed.) Data-Driven Techniques in Speech Synthesis, Kluwer Academic Publishers, 149-172.
[24] Deane, P., Sheehan, K. Automatic item generation via frame semantics. Education Testing Service, http://www.ets.org/research/dload/ncme03-deane.pdf.
[25] Fromkin, V., Rodman, R. (2002). An Introduction to Language. Thomson Learning, 7th Edition.
[26] Gao, Z. M., Liu, C. L. (2003). A Web-based assessment and profiling system for college English. Proceedings of the 11th International Conference on Computer Assisted Instruction, CD-ROM.
[27] International Phonetic Association, http://www2.arts.gla.ac.uk/IPA/ipa.html.
[28] International Phonetic Association. (1999). Handbook of the International Phonetic Association: A guide to the use of the International Phonetic Alphabet. Cambridge University Press.
[29] Irvine, S. H., Kyllonen, P. C. (2002). Item Generation for Test Development. Lawrence Erlbaum Associates.
[30] Jones, D. (1997). English pronouncing dictionary. Cambridges, U. K..
[31] Kim, B. G., Lee, J. H. (2002). Morpheme-based grapheme to phoneme conversion using phonetic patterns and morphophonemic connectivity information. ACM Transactions on Asian Language Information Processing, 1(1), 65-82.
[32] Lange, M. (2000). From orthography to phonology: Nature of grapheme-phoneme conversion processes in written words recognition. http://www.psy.unsw.edu.au/Users/mlange/GPC/.
[33] Leacock, C., Chodorow, M. (2001). Automatic assessment of vocabulary usage without negative evidence. Educational Testing Service, Princeton, NJ.
[34] Levenshtein, V. I. (1966). Binary codes capable of correcting deletions, insertions, and reversals. Cybernetics and Control Theory, 10(8), 707-710.
[35] Levine, J. R., Mason, T., Brown, D. (1992). lex & yacc, O’Reilly, 2nd Edition.
[36] Linacre, J. M. (2000). Computer-adaptive testing: a methodology whose time has come. Development of Computerized Middle School Achievement Test.
[37] Manning, C. D., Schütze, H. (1999). Foundations of statistical natural language processing. MIT Press.
[38] Martin, B., Mitrovic, A. (2002). Automatic problem generation in constraint-based tutors. Proceedings of the Conference on Intelligent Tutoring System, 388-398.
[39] Merriam-Webster OnLine, http://www.m-w.com/dictionary.htm.
[40] Michaud, L. N., McCoy, K. F., Stark, L. A. (2001). Modeling the acquisition of English: an intelligent CALL approach. User Modeling 2001, LNAI 2109, 14-23.
[41] Mitkov, R., Ha, L. A. (2003). Computer-aided generation of multiple-choice tests. Proceedings of the HLT-NAACL 2003 Workshop on Building Educational Applications Using Natural Language Processing, 17-22.
[42] Oranje, A. (2003). Automatic Item Generation Applied to the National Assessment of Educational Progress: Exploring a Multilevel Structural Equation Model for Categorized Variables. Education Testing Service.
[43] Poel, C. J., Weatherly, S. D. (1997). A cloze look at placement testing. Shiken: JALT (Japanese Assoc. for Language Teaching) Testing & Evaluation SIG Newsletter, 1(1), 4-10.
[44] Porter, M. F. (1980). An algorithm for suffix stripping. Program, 14(3), 130-137.
[45] Project Gutenburg, http://promo.net/pg/.
[46] Randall’s ESL Cyber Listening Lab, http://www.esl-lab.com.
[47] Reynar, J. C., Ratnaparkhi, A. (1997). A maximum entropy approach to identifying sentence boundaries. Proceedings of the Conference on Applied Natural Language Processing, 16-19.
[48] Roever, C. (2001). Web-based language testing. Language Learning & Technology, 5(2), 84-94.
[49] Sheehan, K. M., Deane, P., Kostin, I. (2003). A partially automated system for generating passage-based multiple-choice verbal reasoning items. National Council on Measurement in Education Annual Meeting.
[50] Sinclair, J. (2000). Collins Cobuild English Guides: 2.Word Formation. HarperCollins.
[51] Schneider, D., McCoy, K. F. (1998). Recognizing syntactic errors in the writing of second language learners. Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and the 17th International Conference on Computational Linguistics, 2, 1198-1204.
[52] Stevens, V. (1991). Classroom concordancing: vocabulary materials derived from relevant authentic text. English for Specific Purposes Journal, 10, 35-46.
[53] Stock, M. L. (1988). Some consideration in maintaining adaptive test item pools (Research Report RR-88-33). Educational Testing Service, Princeton, NJ.
[54] Studio Classroom, http://www.studioclassroom.com/.
[55] Taiwan Journal, http://taiwanjournal.nat.gov.tw/.
[56] Taiwan Review, http://publish.gio.gov.tw/fcr/.
[57] The English Listening Lounge, http://www.englishlistening.com.
[58] TOEFL, http://www.ets.org/toefl/index.html
[59] Tsiriga, V., Virvou, M. (2002). Diagnosing language transfer in a Web-based ICALL that self-improves its student modeler. Proceedings of the 2nd IEEE International Conference on Advanced Learning Technologies: Media and the Culture of Learning, 349-543.
[60] Wells, J. C. (1990). Longman pronunciation dictionary. Longman.
[61] Wilson, E. (1997). The automatic generation of CALL exercises from general corpora. Wichman et al. (eds.) Teaching and Language Corpora, Longman, 116-130.
[62] WordNet, http://www.cogsci.princeton.edu/~wn/.
描述 碩士
國立政治大學
資訊科學學系
91753006
93
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0091753006
資料類型 thesis
dc.contributor.advisor 劉昭麟zh_TW
dc.contributor.advisor Liu, Chao-Linen_US
dc.contributor.author (Authors) 黃上銘zh_TW
dc.contributor.author (Authors) Huang, Shang-Mingen_US
dc.creator (作者) 黃上銘zh_TW
dc.creator (作者) Huang, Shang-Mingen_US
dc.date (日期) 2004en_US
dc.date.accessioned 17-Sep-2009 13:54:11 (UTC+8)-
dc.date.available 17-Sep-2009 13:54:11 (UTC+8)-
dc.date.issued (上傳時間) 17-Sep-2009 13:54:11 (UTC+8)-
dc.identifier (Other Identifiers) G0091753006en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/32635-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學學系zh_TW
dc.description (描述) 91753006zh_TW
dc.description (描述) 93zh_TW
dc.description.abstract (摘要) 以Web為基礎的語言測驗（Web-based language test）目前多為靜態網頁或是互動性低的動態網頁，如何提昇測驗系統的互動性，仍有待探討。目前已有學者利用自然語言處理技術來自動產生試題，並分析學生的作答錯誤。然而，相關研究仍多著重於字彙測驗與文法評量上。本研究針對聽力測驗，發展一套線上練習系統，並運用自然語言處理技術來自動產生聽力選擇題，以及分析學生的聽寫錯誤。我們分析語料庫中的詞彙，將發音相近的單字歸為一類，系統要產生聽力選擇題時，即從單字所屬的群組中，隨機挑選其他發音相近的單字當作誘答選項。而在分析聽寫錯誤方面，我們從語尾變化、拼字、拼音三種層次來分析學生的作答；系統批改完後，會按照學生的錯誤類型，提供不同種類的練習。本練習系統共有聽寫測驗、單字聽力選擇題、單字組聽力選擇題三種題型。系統可以輔助教師大量地編製試題與測驗，並輔助批改學生的作答。學生則可透過網路來接受測驗，並針對自己的弱點單字來作練習。zh_TW
dc.description.abstract (摘要) Most Web-based language tests are presently static pages or dynamic pages with low interactivity. How to enhance the interactivity of the test systems is still under development. Today some researchers have utilized natural language processing techniques for automatic item generation and intelligent error analysis of students’ answers. However, most known research works put more emphases on vocabulary tests and grammar correction. In this paper, we propose a Web-based practice system for English dictation and listening cloze. We use natural language processing techniques to automatically generate multiple-choice item and analyze students’ dictation errors. First, we analyze the words in the corpus and group them based on the similarity of the phones. When the system generates multiple-choice items, it will search the matched cluster and randomly pick other words with similar phones. Second, we analyze students’ dictation from three aspects: inflected form, spelling errors and phoneme structures. After analyzing students’ answers, the system will provide different practice items according to the error types. Our practice system has three item types: one for dictation and two for multiple-choice listening cloze. The system can assist teachers in authoring items and grading the test results. Students can take the test through the Internet and practice on their weak words.en_US
dc.description.tableofcontents 目 錄 V
圖 目 錄 VII
表 目 錄 IX
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究方法 5
1.3 研究成果 7
1.4 論文結構 9
第二章 文獻回顧探討 11
2.1 自動產生試題之回顧探討 11
2.2 智慧型英語錯誤分析之回顧 14
2.3 網路英語測驗系統之研究回顧 16
2.4 自然語言處理技術之回顧 20
2.4.1 最短編輯距離演算法 20
2.4.2 從拼字轉換為音標 23
第三章 系統概觀 26
3.1 題型概觀 26
3.2 系統架構 29
3.3 語料蒐集與前處理 30
3.4 音標系統 31
3.5 語音合成技術 32
第四章 聽力選擇題自動產生 34
4.1 自動產生誘答選項 34
4.2 建立發音差距相近的詞彙清單 36
4.3 建立子母音結構相同的詞彙群組 42
第五章 聽寫錯誤分析 44
5.1 聽寫錯誤類型 44
5.2 語尾變化錯誤分析 46
5.3 拼字錯誤分析 47
5.4 拼音錯誤分析 49
5.5 試題回饋 58
5.6 多字聽寫之訊息提示 62
第六章 聽寫測驗 64
6.1 聽寫測驗流程 64
6.2 編製聽寫試題 65
6.3 編製聽寫測驗試卷 68
6.4 選擇聽寫測驗 70
6.5 進行聽寫測驗 71
6.6 聽寫試題練習 73
第七章 單字聽力選擇題測驗 76
7.1 單字聽力選擇題測驗流程 76
7.2 編製單字聽力選擇題 77
7.3 編製單字聽力選擇題測驗 79
7.4 選取單字聽力選擇題測驗 81
7.5 進行單字聽力選擇題測驗 82
7.6 單字聽力選擇題練習 84
第八章 單字組聽力選擇題測驗 86
8.1 單字組聽力選擇題測驗流程 86
8.2 編製單字組聽力選擇題 87
8.3 編製單字組聽力選擇題測驗 89
8.4 選取單字組聽力選擇題測驗 92
8.5 進行單字組聽力選擇題測驗 93
8.6 單字組聽力選擇題練習 94
第九章 結論 96
附錄一 音標剖析器之規格檔 100
附錄二 詞綴清單 103
附錄三 音標轉換函式 105
參考文獻 108		zh_TW
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dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0091753006en_US
dc.subject (關鍵詞) 電腦輔助教學zh_TW
dc.subject (關鍵詞) 自然語言處理zh_TW
dc.subject (關鍵詞) 線上測驗zh_TW
dc.subject (關鍵詞) 聽力克漏字zh_TW
dc.subject (關鍵詞) 聽寫測驗zh_TW
dc.subject (關鍵詞) Computer-Assited Learningen_US
dc.subject (關鍵詞) Natural language processingen_US
dc.subject (關鍵詞) Web-based testen_US
dc.subject (關鍵詞) listening clozeen_US
dc.subject (關鍵詞) dictatioin testen_US
dc.title (題名) 英文聽力字彙與聽寫練習題輔助出題系統之研究zh_TW
dc.title (題名) Computer-Assisted Item Generation for Listening Cloze and Dictation Practice in Englishen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) [1] 大學入學考試中心，大考中心高中英文參考詞彙表編修研究計畫報告（第二期），http://www.ceec.edu.tw/service/ce23/ce23.htm，民國91年。zh_TW
dc.relation.reference (參考文獻) [2] 王美燕，國中學生英語字彙測驗錯誤分析，國立高雄師範大學教育研究所碩士論文，民國82年。zh_TW
dc.relation.reference (參考文獻) [3] 王俊弘，電腦輔助克漏詞多選題出題系統之研究，國立政治大學資訊科學研究所碩士論文，民國93年。zh_TW
dc.relation.reference (參考文獻) [4] 光華雜誌，http://www.sinorama.com.tw/。zh_TW
dc.relation.reference (參考文獻) [5] 何榮桂，「電腦化題庫設計的基本架構」，教育研究月刊，第20期，21-26頁，民國80年。zh_TW
dc.relation.reference (參考文獻) [6] 周文正，「WWW上電腦輔助測試系統之研製」，中華民國第七屆電腦輔助教學研討會，http://thccx5.cc.nthu.edu.tw/wjchou/tecpaper/w3cat/index.html，民國87年。zh_TW
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