Please use this identifier to cite or link to this item: http://rportal.lib.ntnu.edu.tw:80/handle/20.500.12235/97439
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dc.contributor陳浩然zh_TW
dc.contributorChen, Hao-Janen_US
dc.contributor.author王靖雯zh_TW
dc.contributor.authorWang, Ching-Wenen_US
dc.date.accessioned2019-09-03T12:23:18Z-
dc.date.available2024-07-27
dc.date.available2019-09-03T12:23:18Z-
dc.date.issued2019
dc.identifierG060221066L
dc.identifier.urihttp://etds.lib.ntnu.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=%22http://etds.lib.ntnu.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=id=%22G060221066L%22.&%22.id.&
dc.identifier.urihttp://rportal.lib.ntnu.edu.tw:80/handle/20.500.12235/97439-
dc.description.abstract先前的研究指出文步在學術期刊中的重要性,因為文步被視為是建構學術文章架構的重要核心。許多學者著重於對學術文章中不同文步的研究。然而,探討常用字串與文步關聯的研究卻很少。 有鑑於此,本研究回答以下三個研究問題:(一)、哪些是社會科學領域以及自然科學領域共同常用的字串?(二)、哪些是社會科學領域以及自然科學領域分別特有的字串?(三)、在學術文章中,字串以及文步在緒論中的關聯是什麼? 語料庫分析法乃本文探討常用字串的方式。研究者建置了由一千兩百篇由國際期刊論文所組成的學術寫作語料庫,一共一千三百多萬字,內容包含社會科學領域以及自然科學領域之學術期刊,各領域所包含的學科如下:化學、數學、物理學、經濟學、語言學、心理學。研究者採用關鍵字串以及檢索的方式找出學術文章緒論中的常用字串。 本研究結果共發現兩百一十一個的常用字串,其中社會科學領域及自然科學領域共有八十個常用字串,社會科學領域特有的常用字串共有七十六個,自然科學領域特有的常有字串共有五十五個。以字串的長度而言,在學術語料庫中,共有一百零四個四字常用字串、六十四個五字常用字串、二十個六字常用字串、十一個七字常用字串、以及十二個八字或以上的常用字串。 常用字串的結構性及功能性亦被檢視及歸類,就結構性而言,四字字串中含有較多名詞或介係詞,含有動詞的比例則較少,隨著字串長度的增加,字串中同時含有名詞及動詞的比率也隨之增加。針對字串的功能性,社會科學領域及自然科學領域的學者都傾向大量的篇章組織字串來組織學術文章。 研究者更進一步分析這些常用字串與文步之間的關聯,以回答第三個研究問題。有些字串只會在特定文步中被使用,有些則會在多於一個文步中被使用。在所有文步中,第一文步第三次要文步包含了最多的字串,共有九十七個的字串被用來協助回顧文獻,而第三文步第七次要文步中的字串則較具有專一性,共有四十八個字串只會在這個文步中被使用來協助概述學術文章的結構。 本文研究結果顯示,不同領域的期刊作者在文步的使用上有其異同之處。研究者建議學術英語教學者能將此研究所列的字串與文步關係引入課程,以期能為增進學習者與新手研究學者的學術寫作能力盡棉薄之力。zh_TW
dc.description.abstractPrevious studies have shed light on the importance of rhetorical moves in research articles, for moves are viewed as the core organization of constructing research articles. Many researchers have focused on investigating and exploring the different rhetorical moves in the different sections of the RAs. However, empirical findings that linked particular frequent lexical bundles to moves or steps in moves have been limited. Specifically, three research questions were proposed in this study. (1) What are the shared lexical bundles frequently used between social sciences and physical sciences? (2) What are the lexical bundles exclusively used in social sciences or physical sciences? (3) How do lexical bundles connect to the moves and steps in research article introductions? The corpus-based analysis was applied in the present study. The corpus is comprised of a total of 1200 published RA introductions in well-known international journals, including approximately 1.3 million words. The RA introduction sections are from a variety of academic disciplines, which are chemistry, mathematics, physics, economics, linguistics, and psychology. The wordlist and the concord function were employed to extract the frequent lexical bundles in the research article introductions. A total of 211 frequent lexical bundles were extracted and the bundle lists were compiled. There are a total of 80 lexical bundles commonly used both in social sciences and physical sciences. For social sciences, there are 76 bundles exclusively used. There are 55 bundles exclusively used in the field of physical sciences. In terms of the word length, there are 104 four-word bundles, 64 five-word bundles, 20 six-word bundles, 11 seven-word bundles, and 12 eight-word and longer bundles identified in the corpus. The structure and function of the identified bundles are also examined in the present study. For the structural classification, there are more four-word bundles incorporating noun phrase or prepositional phrase fragments in the structure. As the word length increase, bundles including noun phrase and verb phrase increase. As for functional classification, researchers in both disciplines tend to use discourse organizers to help construct the research. A further step in the analysis matched these lexical bundles to the moves and steps so as to answer the third research question. Some lexical bundles were exclusively linked to one move or step in a move while others occurred across more than one move and steps. Among all the moves, move 1 step 3 contains the most lexical bundles. There are 97 lexical bundles identified to review the items of previous literature. As for the bundles only used in the certain move or step, there are 48 bundles exclusively identified in move 3 step 7 for outlining the structure of the paper. The findings indicate that there are similarities and differences between the lexical bundles used by researchers from different disciplines. The researcher suggests that English instructors and teachers can introduce the list of lexical bundles and the corresponding moves and steps in the academic courses. Some pedagogical implications for future research are proposed.en_US
dc.description.sponsorship英語學系zh_TW
dc.language英文
dc.subject文步zh_TW
dc.subject字串zh_TW
dc.subject語料庫分析zh_TW
dc.subjectmovesen_US
dc.subjectlexical bundlesen_US
dc.subjectcorpus analysisen_US
dc.title以語料庫為本的跨領域學術英文期刊文步與字串之研究zh_TW
dc.titleA Corpus-Based Study on Connecting Lexical Bundles and Moves in Cross-Discipline Research Article Introductionsen_US
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