Effects of Graded Texts on EFL College Students' Incidental ...

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3.3.3 Sequencing <strong>of</strong> reading texts After suitable reading texts and word lists were chosen, we then began to arrange and sequence reading texts in an order that is able to provide learners with comprehensible input and increase chances <strong>of</strong> exposure to target words. Visual FoxPro 7.0 was again used. Our programming steps are as follows. First, for the reason <strong>of</strong> providing learners with chances <strong>of</strong> reading longer texts and at the same time not to overwhelm learners by lengthy texts, from the 5008 texts in Sinorama, we selected only the texts that contained between 1500 and 3000 running words for sequencing procedures. A total <strong>of</strong> 959 texts met this criterion. Second, the 959 texts were reexamined with the four word lists that we selected, texts unable to reach 95% coverage were excluded. This sifting process left us with 856 reading texts. It should be noted that at this point, each <strong>of</strong> the remaining 856 text would contain different proportion <strong>of</strong> words from the familiar word lists, words from the target word lists, and other unfamiliar words not included in the familiar word and target word lists. The 95% cut <strong>of</strong>f point in the second step ensured that the average coverage <strong>of</strong> words from the familiar word lists and the target word lists together was able to reach 95% <strong>of</strong> the running words in these 856 texts. Third, running words in the qualified 856 texts were compared to those in the familiar word lists, GSL and HSF, and the target word lists, UWL and SHF. Visual FoxPro 7.0 sifted through the texts and sequenced texts according to vocabulary difficulty. The one text that contained the highest number <strong>of</strong> familiar words and smallest number <strong>of</strong> target words was placed first on the sequence. So far, the order arranging procedures are similar to those used in Ghadirian’s (2003). We added the following steps in order to increase the encounters <strong>of</strong> target words. First, to find the second appropriate text, the program did not immediately add the target words in the first text into the familiar word lists like that in Ghadirian’s 33
TextLadder; instead, our program put exposed target words in another newly created word list, the Exposed Word List. With this new word list, our program then sifted through texts again looking for the text that contained the highest number <strong>of</strong> familiar words and the least number <strong>of</strong> target words, but this time a third standard was added by using the Exposed Word List. The program searched for a text which not only contained the highest number <strong>of</strong> familiar words and the least number <strong>of</strong> target words, but a text that also contained the highest number <strong>of</strong> words from the Exposed Word list (target words from previous texts on the sequence). That is, if the first text on the sequence order had four target words computer, international, assist, and advantage, after learners read this text, these four target words would be taken out <strong>of</strong> the target word list and included into the Exposed Word List. After the first text was put in order, the program then went through the remaining texts looking for the next easiest text by comparing familiar words and target words to texts, and also with one more screening guideline, seeking for a particular text that contained the highest number <strong>of</strong> words from the Exposed Word List. The second text selected then might have its new sets <strong>of</strong> target words, for example, qualify, situation, and paragraph, but also include target words from the first text, computer, international, assist, and advantages. Compared to other texts, the second text was the second easiest text and the text that had the most number <strong>of</strong> first text target words. To select the third text, the program automatically included the target words in the second text into the Exposed Word List (now the Exposed Word List would contain the following words, computer, international, assist, advantages, qualify, situation, and paragraph, which are target words from the first text and the second text) and again went through the same sifting process for the next text. In other words, the program ensured that the target words appearing in the previous texts again reappear in the following texts. After sequencing, the target words in each reading text were highlighted in red to 34
Page 1 and 2: 國立清華大學碩士論文英
Page 3 and 4: Abstract Incidental vocabulary lear
Page 5 and 6: implicit learning for learners’ q
Page 7 and 8: 4.3. Discussion 70 4.3.1. The Feasi
Page 9 and 10: List of Figure Fig
Page 11 and 12: competence (Elley, 1991; Hafiz & Tu
Page 13 and 14: EFL classes, and determining the am
Page 15 and 16: consultation for second language le
Page 17 and 18: vastly reinforced with the ease and
Page 19 and 20: learning to occur. 2. Word meaning
Page 21 and 22: inging learners who are competent <
Page 23 and 24: (1993) suggested a required 5,000 w
Page 25 and 26: words in this set of</stron
Page 27 and 28: Besides the above potential limitat
Page 29 and 30: immediately after reading, one week
Page 31 and 32: 2.6. Measuring Incidental Vocabular
Page 33 and 34: 2.7. Summary We incorporated the em
Page 35 and 36: 3.1. Overview Chapter Three METHODO
Page 37 and 38: The Sinorama magazine is dedicated
Page 39 and 40: Word List (鄭恆雄, 2002; 2003),
Page 41: for the cut off po
Page 45 and 46: target words within each text. Afte
Page 47 and 48: Table 3.2 Target word rate and targ
Page 49 and 50: 7. into the Exposed Word List Selec
Page 51 and 52: Table 3. 5. A comparison between Gh
Page 53 and 54: 3.3.4 Glossing of
Page 55 and 56: participants were required put a ch
Page 57 and 58: score of 2. If a t
Page 59 and 60: Table 3.9 Instruments used in the s
Page 61 and 62: had finished all sixteen texts. The
Page 63 and 64: technical feasibility of</s
Page 65 and 66: a result, valid subjects dropped fr
Page 67 and 68: Table 4.2 Learners’ perspectives
Page 69 and 70: estimation of lear
Page 71 and 72: words from known words. The provisi
Page 73 and 74: vocabulary level, on the other hand
Page 75 and 76: 4.2.4 The results of</stron
Page 77 and 78: Table 4.11 shows learners’ respon
Page 79 and 80: 4.3 Discussion 4.3.1. The feasibili
Page 81 and 82: direct phonetic translations <stron
Page 83 and 84: on gloss suggested that they still
Page 85 and 86: measurement tool for its function <
Page 87 and 88: learners’ processing of</
Page 89 and 90: not be untangled without considerin
Page 91 and 92: 5.1. Overview Chapter Five Conclusi
Page 93 and 94:
with the same group of</str
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also accelerate sequencing time wit
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esponsible for connecting the two b
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REFERENCES Berman, R.A. (1984 ). Sy
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Hulstijn, J. H., Hollander, M., & G
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Rationale for Pedagogy (pp. 174-200
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第 1-6 題電腦方面 Appendix A
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Student Post□ 其他□__________
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26. optimistic 27. consumption 28.
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1. entrepreneur: VI. 我對這個
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21.calligraphy: I. 我對這個字
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41.insufficient: I. 我對這個字
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3 points entrepreneur: (item three
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Appendix F The In-class Evaluation
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Appendix H The Introductory Page on
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Appendix J A Search Example <strong
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Appendix L Student Reading Process
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第 1-6 題電腦方面 Appendix N
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13(2). 英文雜誌 41.7% (28/67) (
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Appendix P Results of</stro
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