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研究生：	黃苑華 Huang, Yuan-Hua
論文名稱：	台灣工學院學生英語字彙知識之研究 A Study of the English Vocabulary of Engineering Students in Taiwan
指導教授：	鄒文莉 Tsou, Wen-Li
學位類別：	碩士 Master
系所名稱：	文學院 - 外國語文學系 Department of Foreign Languages and Literature
論文出版年：	2011
畢業學年度：	99
語文別：	英文
論文頁數：	112
中文關鍵詞：	工學院語料庫、工學院常用教科書、工學院專業英語學習單字表、台灣工學院大學生字彙量
外文關鍵詞：	Fundamental Engineering Corpus, Fundamental Engineering Wordlis, Engineering textbooks, Vocabulary Size of Taiwanese engineering majors
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研究指出，工學院學生認為字彙量不足是閱讀原文教科書時最大的障礙，而原文書又是大學求學階段最主要的閱讀教材，若無法掌握書中內容，將有礙專業能力的發展。因此如何幫助學子們擴充單字量，讓他們輕鬆應付大量的原文教材，是目前許多學術英語同業努力的目標。所以本研究之研究目的有三：(一)找出工學院學生在閱讀原文書時，必須要認識的高頻率單字，並建立一份工學院原文教科書常用字彙量表；(二)瞭解工學院大一大二學生對此份字彙量表的認識程度以及(三)台灣大學生對字表中，不同單字類別字彙習得之情形。藉此我們可以知道學生目前所具備的單字量，並針對不足的部分施予必要的協助。
本研究過程大致分為以下三個部分：(一)建立工學院原文書字彙量表；(二)根據字表編製單字測驗，實施測驗以找出大學工學院學生目前具備的字彙量；(三)比較大一和大二生在英語字彙表現上的差異。為了回應研究問題，本研究的研究方法如下：
首先，研究者針對成功大學大一、大二工學院學生所需閱讀的專業基礎科目為研究對象，建立了一個工學院基礎課程語料庫(FEC)，此語料庫共收錄了80多萬字、15,000多個字型(word types)。之前研究顯示，讀者在閱讀文章時，至少必須了解其中95%的文字，才能對該文有足夠程度的了解。以此標準(95%)為目標，鎖定前3,941個高頻率單字。我們認為這3,941個單字為工學院大一、大二生，在閱讀原文書時，必須認識的單字。這些單字被集結成一份工科原文教科書常用字彙量表(FEWL)。再來，我們根據Nation(2001)對單字的分類，將這份單字表中的單字，分成四個單字類別：(一)高頻率單字GSL、(二)學術英語用字AWL、(三)科技英語用字TECH以及(四)較低頻率單字 SUP[剩下不包含在前三類者，皆屬此類]。雖相對為較低頻率單字，但本質上SUP仍屬於工科原文教科書常用字彙。
其次，研究者根據FEWL和單字分類成果，設計了一份單字測驗來檢視大一、大二生目前具備的字彙量以及探究單字類別(GSL、AWL、TECH和SUP)對工學院大學生字彙習得的情形。共有124位大學工學院學生參與研究(73位大一新生和51位大二生)。研究結果顯示：(一)字彙量方面，學生整體而言對於此字表的認識達到60%，尚有40%的部分是需要加強的; (二) 大二生具有的字彙量顯著多於大一新生。(三)若探討單字類別對學生單字的表現，我們發現學生對於各類單字的表現如下：80% GSL, 60% AWL, 47% SUP 以及40% TECH。顯示至少在 the AWL, the SUP 以及the TECH的部分，學生還有許多進步的空間；(四)而大一與大二生字彙量差異上，其顯著性主要在於TECH 和SUP的表現，而不是GSL和AWL。表示大二生經過一年的大學教育在專業類別的單字成長迅速，但在一般英語方面則呈現緩慢甚至停滯成長的狀態。據了解，在英語課程方面，大一階段學生主要仍是接受一般英語課程的訓練(English for General Purposes)，課程利用不同主題，幫助學生增進其聽說讀寫的能力，其次，EGP課程雖然融入了部分學術英語單字(AWL by Coxhead, 2000)，但學生在此類單字表現上，卻進步有限，顯示大一英語課程對於工學院學生擴展工科常用單字的教學仍有改進工空間。本研究的結果以及結論所提出的建議可作為日後英語教師以及課程設計者規劃英語課程的參考。

A large number of engineering students at National Cheng Kung University (NCKU) complain about their lack of vocabulary when reading content area textbooks written in English. Studies have shown that the content-area textbooks are the main learning resource used by students in college. It was assumed that a lack of vocabulary may lead to an inadequate level of comprehension, which would directly influence the development of their professional knowledge. In order to help engineering students expand their vocabularies to a satisfactory level (a 95% text coverage was suggested as the minimum threshold for reading comprehension), the purpose of the study is to investigate the gaps between students’ current vocabulary level and the vocabulary level required for reading textbooks (also known as the FEWL later). The exploration of engineering students’ English vocabulary can help language teachers in designing curriculums.
In order to answer the research questions, a fundamental engineering corpus (FEC) was compiled. It included 10 textbooks commonly used in the School of Engineering. The 3,941 highest-frequency word types in the FEC were selected. These words had up 95% text coverage of the textbooks. The 3,941 word FEWL was further divided into General Service Word List (GSL), the Academic Word List (AWL), Technical Words (TECH) and low-frequency words, which were words not included in the GSL, the AWL, or the TECH. The last category was named Supplementary (SUP) in this study because the occurrences of the words are not infrequent in engineering textbooks. The classification, afterwards, gave us a clear idea of how the FEWL was structured.
Following the structure of the FEWL, we designed a yes-no vocabulary test to explore first-year and second-year students’ vocabularies as they related to the FEWL. Participants included 124 Engineering undergraduate students (73 freshmen and 51 sophomores). The exploration focused not only on the size of their vocabularies, but also on their percentage performance in each category of vocabulary. The results of the study revealed that (1) overall students recognized 60% of the words in the FEWL, leaving 40% unknown; (2) there were significant differences in the sizes of freshmen and sophomores’ vocabularies; (3) in terms of word categories, the participants were able to recognize 80% of the GSL, 60% of the AWL, 47% of the SUP and 40% of the TECH, on average, and (4) the main difference between first-year and second-year students was their knowledge of subject-related vocabularies (the SUP and the TECH), rather on that of non-subject-related vocabularies (the AWL and the GSL). This may imply that wide-focus general English courses have limited effect on helping engineering majors expand their understanding of the required vocabulary in reading content-area textbooks. Based on the findings, some implications for future English curriculum designs are presented at the end of the study.

Table of Content
Acknowledgements	i
Chinese Abstract	iii
English Abstract	v
Table of Content	vii
Table of Figures and Tables	xii

Chapter 1 Introduction	1
1. Introduction	1
1.1. Vocabulary Requirement	2
1.2. Students’ Vocabulary Knowledge	4
1.2.1. The Quantity of Students’ Vocabulary Knowledge	4
1.2.2. The Quality of Vocabulary Knowledge	5
2. The purpose of the study	7
3. Research Questions	8
4. The Contribution of the Study	8
5. Important Terminology	8
6. Organization of this Thesis	9

Chapter 2 Literature Review	11
1. Vocabulary Requirements for Reading a Text	11
2. Discussions about various Engineering Wordlists	14
2.1. BEL by Ward (2009)	14
2.2. EWL by Ward (1999) and SEEC by Mudraya (2004, 2006)	15
3. Arguments about Word Family and Word Lemma	19
3.1. Definitions of Four Kinds of Word Counting Units	19
3.2. Arguments against Word Families	20
3.3. Arguments against Word Lemma	22
4. Characteristics of the Four Categories of Vocabulary	23
4.1. General Service Words (GSL)	24
4.2. Academic Wordlist (AWL)	24
4.3. Technical words	25
4.4. Low-frequency words	26
5. EFL Students’ Vocabulary Knowledge	27
5.1. EFL Students’ Knowledge of a Specialized Wordlist	27
5.2. Effects of the Four Word Categories on Vocabulary Learning	28

Chapter 3 Methodology	31
1. Participants	31
2. Corpus Design	33
2.1. Textbook Selection Criteria	33
2.2. Corpus Compiling Procedures	35
3. Procedures of Vocabulary Classifications	37
3.1. Defining technical words	37
3.2. Steps employed to sort out technical words	38
3.2.1. Phase 1: Technical Word Classification	38
3.2.2. Phase 2: Technical Word Confirmation	42
3.3. Classification of the GSL, AWL, and SUP	43
4. Test Instrument	45
4.1. Yes/No Vocabulary Test	45
4.2. Real Words and Pseudo-Words	47
4.2.1. Sampling of the Read Words	47
4.2.2. Invention of Pseudo-Words	49
5. Test Administration	50
6. Data Analysis Framework	51
6.1. Item response	51
6.2. Scoring Method for the Yes-No Vocabulary Test	52
6.3. The Performance on the Four Categories of Vocabulary	54
6.4. Reliability of the Yes-No Vocabulary Tests	55
6.5. Analysis of the Raw Data	55

Chapter 4 Results	56
1. Results	56
1.1. How many words are required in order to reach an adequate level of reading comprehension?	56
1.2. How is the FEWL composed in terms of the four categories of vocabulary?	57
1.3. How many words in the FEWL do the participants know?	58
1.4. Is there any difference between freshmen and sophomore students in terms of their knowledge of FEWL vocabulary?	58
1.5. How does their knowledge of FEWL vocabulary differ with respect to the four word categories?	59
2. A brief summary of the findings from the results	61

Chapter 5 Discussion	62
1. Vocabulary Requirement	62
1.1. FEWL of the 3,941 Word Types	62
1.2. Structure of the FEWL	63
2. Students’ Vocabulary Knowledge	65
2.1. Students’ Vocabulary Size of the FEWL	65
2.2. Students’ Vocabulary Performances on Four Word Categories	66
2.3. The Effect of the Courses Offered at the First Year of College	67
2.3.1. Effect of the Specialized Courses on the Development of Subject-related Vocabulary	68
2.3.2. Effect of the EGP on the Development of Non-subject-related Vocabulary	69

Chapter 6 Conclusion	73
1. Summary	73
2. Pedagogical Implication	75
3 Limitations and Recommendations for Further Studies	78

References	81
Appendix A: Engineering Textbooks in the Fundamental Engineering Corpus	85
Appendix B: Fundamental Engineering Wordlist	86
Appendix C: The Yes/no Vocabulary Test (Version 1)	106
Appendix D: The Yes/no Vocabulary Test (Version 2)	110


                                    

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