T1 112012091 Full text
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VOCABULARY PROFILE OF ENGLISH TEXTBOOK USED
IN VOCATIONAL HIGH SCHOOL GRADE XI
THESIS
Submitted in Partial Fulfillment of the Requirement for the Degree of
Sarjana Pendidikan
Iwan Lugiyanto
112012091
ENGLISH LANGUAGE EDUCATION PROGRAM
FACULTY OF LANGUAGE AND ARTS
UNIVERSITAS KRISTEN SATYA WACANA
SALATIGA
2016
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VOCABULARY PROFILE OF ENGLISH TEXTBOOK USED
IN VOCATIONAL HIGH SCHOOL GRADE XI
THESIS
Submitted in Partial Fulfillment of the Requirement for the Degree of
Sarjana Pendidikan
Iwan Lugiyanto
112012091
ENGLISH LANGUAGE EDUCATION PROGRAM
FACULTY OF LANGUAGE AND ARTS
UNIVERSITAS KRISTEN SATYA WACANA
SALATIGA
2016
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COPYRIGHT STATEMENT
This thesis contains no such material as has been submitted for examination in any course or accepted for the fulfilment of any degree or diploma in any university. To the best of my knowledge and belief, this contains no material previously published or written by any other expect where due references is made in the text.
Copyright@ 2016. Iwan lugiyanto and Prof. Dr. Gusti Astika, M.A.
All rights reserved. No part of this thesis may be reproduced by any means without the permission of at least one of the copyright owners or the English Language Education Program, Fakultas Bahasa dan Sastra, Universitas Kristen Satya Wacana, Salatiga.
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Table of Contents
Abstract... 1
A. Introduction... 1
B. Literature Review... 4
1. Teaching and learning Vocabulary... 4
2. Vocabulary and L2 Frequency... 6
3. Vocabulary Profiler... 7
4. Vocabulary Clasification... 8
5. Previous Study of Vocabulary Profile... 9
C. The Study... 10
1. Method of research... 10
2. Material... 10
3. Research Instrument... 11
4. Data Collection... 11
5. Data Analysis... 11
D. Findings and Discussion... 12
The overall of vocabulary profile... 12
Negative vocabulary profiles of the textbook... 14
Negative vocabulary profile of K1... 15
Negative vocabulary profile of K2... 16
Negative vocabulary profile of K3 or AWL... 18
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Comparison across chapters of the textbook... 21
Comparison of chapter 1 vs. Chapter 4... 22
Comparison of chapter 2 vs. Chapter 5... 24
Conclusion... 26
References... 28
Acknowledgements... 32
Appendixes... 33
Appendix A... 33
Appendix B... 36
Appendix C... 42
Appendix D... 46
Appendix E... 61
Appendix F... . 69
List of Tables Table 1. The overall of vocabulary profile... . 13
Table 2. Negative Vocabulary Profile of K-1... 15
Table 3. Negative Vocabulary Profile of K-2... 17
Table 4. Negative Vocabulary Profile of K-3 or AWL... 18
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Table 6. Comparison of Word Frequency Level... 21 Table 7. Shared and Unique Words in Chapter 1 and Chapter 4.... 23 Table 8. Shared and Unique Words in Chapter 2 and Chapter 5.... 24
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VOCABULARY PROFILE OF ENGLISH TEXTBOOK USED IN VOCATIONAL
HIGH SCHOOL GRADE XI
Iwan Lugiyanto
Abstract
In teaching and learning English, vocabulary is an important element as it delivers the meaning of certain words. Problem might occur if the students are not familiar with the words given. Therefore, the aim of the study was to profile the vocabulary of the textbook used in vocational high school. The data were analyzed by using an electronic tool named The Compleat Lexical Tutor, v.4. There are 84.65% of K-1 and 6.55% of K-2 words in textbook. It indicates that the textbook is understandable for Vocational High School students. Thus, the rest 8.80% need much efforts in learning. There are 29.15% of K-1, 71.30% of K-2, and 72.06% of academic words that were not found in the textbook. The comparison analysis was done for Chapter 1 and Chapter 4, and Chapter 2 and Chapter 5. The comparison analysis’ result were 76.02% words in those chapters which similar in chapter 1 and 4. On the other hand, there were 78.55% words that are similar in Chapter 2 and Chapter 5.
Keywords: Vocabulary, Vocabulary Profile, Understandable, Textbook.
INTRODUCTION
English has become an important subject in education due to its global and international use in communication. It is taught as a compulsory course in educational institutions at different levels. Vocational high school is one of many
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institutions in Indonesia which used English in providing of world requirements: in preparing the vocational school students in a work field. That is why English textbook for vocational school students must be able to help teacher and students to master English according to their need in the work field.
However, in vocational high schools, learners might suffer a crucial problem in learning English, which is lack of vocabulary. The problem here is how people able to intemperance vocabularies as much as possible. Most of student has limited vocabulary as well as, in order to increase their ability in English we should find the better formula how to boost their vocabulary. As the researcher had experienced in teaching practicum in one of vocational high school in Salatiga, most of the students found difficulty in reading subject. Because reading spent a lot of time to know the meaning while to answer the questions, how they (students) able to answer the questions if they do not know the meaning. Reading test also included in English skill ability and reading also included in UAN, as we know most of them there are many questions about reading texts. As far as we know, the vocabulary is the key of mastering language especially in second language with mastery in vocabulary, the students will be able to increase and develop their English ability both in oral and written.
In learning process, there are many problems faced by students. According to Cahyono and Widiati (2008, as cited in Priyono, 2004:26) the main problem of Indonesian learners is that they lack of vocabulary. Students often face some difficulties in understanding the meaning of vocabulary, producing vocabulary, and using vocabulary in a appropriate context. The other problem that is teachers
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usually focus on teaching grammar rather than teaching vocabulary, this makes students lack in vocabulary. Kafipour (2009) said that many students have a limited range of vocabulary and this problem will influence their comprehension when producing the language.
Nation (2001) suggested that to understand texts, at least 95% of the running words are recognizable. Matsuoka and Hirsh (2010) also added that it is required to reach 95% in order to understand the text deeply. Therefore, vocabulary knowledge should be mastered by the foreign language learners. However, the
question for further discussion is how to measure students’ vocabulary input.
By knowing how important of vocabulary’s role in learning second language is, and it needs 95% of word order. Teachers should be able to choose suitable words for the students. Furthermore, vocabulary profile is important to help students understand tho words easily. According to Capel (2012), vocabulary profile gives information about a fully searchable listing of words and phrases in English at each level. It would be useful especially in teaching and learning vocabulary because the students and teachers have to understand which parts of vocabulary is used for suitable learners: beginner, intermediate or even advanced.
Based on those problem, The research question for this study was “What is the vocabulary profile of the English textbook used in vocational high school?” The main objective of this study was to profile the vocabulary of the textbook used in vocational high school. The significance of the study is to help teacher to choose which vocabulary which is used to explain the material for students in different levels.
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Vocabulary is one important element in learning English. By knowing the significant of vocabulary cannot be omitted in learning language, it might be beneficial for the teachers to teach the necessary vocabulary that was suitable for the learners based on the words order. Later on, this vocabulary profile might be useful to make certain about those are suitable for beginner, intermediate or even advanced learners. By knowing the vocabulary profile, students are able to understand lexical meaning easily and avoid some difficulties that might occur in learning process.
LITERATURE REVIEW
1. Teaching and Learning Vocabulary
Vocabulary is generally defined as “a set of lexeme, including single words, compound words, and idiom (Richard, 2010 p. 629). In the other hand, Olmos (2009) specifically stated that vocabulary is the basic tool for shaping and transmitting the meaning for language users. It indicates that the learners have to know well about the words. If they knew words without the denotation of the function, it would be less effective for the meaning. Learners with sufficient vocabulary knowledge will be able to express their own ideas, easy to learn new concepts, and will be able to communicate with others. In order to achieve the goal of learning, learners should recognize at least 95% of the running words (Nation, 2001).
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Vocabulary is accepted as very important element in learning language. As the learners know more vocabulary, they also know more capacity for uttering the phrases, clauses and sentences (Hassan & Abubakr, 2015). Richard and Renandya (2002) also added that vocabulary becomes the basic component of language proficiency. It shows that vocabulary has significant roles in the development of second language learning.
Due to the importance role in language learning, vocabulary needs to be learnt as to enrich their knowledge so that the students become proficient in English. However, there is a problem that the learners encounter relating vocabulary learning especially in Indonesian context; they have difficulties in understanding vocabulary and it affects on their second language proficiency. According to Cahyono and Widiati (2008), the main problem of Indonesian learners is that their vocabulary limitedness. For the other problem in learning vocabulary was coming from the students who were taught grammar was more important than vocabulary. It indicated that the learners had lack of vocabulary.
In learning process, vocabulary learning comes through use, both receptive and productive use (Nation, 1990). Therefore, teachers and learners are able to express new ideas provided in both receptive and productive. In vocabulary learning, there are some strategies that learners can use to cope with new vocabulary. According to Nation (1990) mentioned that the most useful and effective strategy is guessing from the context. It is worth spending time on this strategy until learners have mastered it. Guided practice will encourage learners to use them and give learners skill to use the language effectively.
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Studies have found that vocabulary is essential in the development of second language learning. Criado and Sanchez (2014) emphasized that vocabulary is the most important component that should be taught and learned in the classroom. In learning a word, learner should know its spelling, pronunciation, collocations; words which is co-occurs with, and appropriateness (Nation, 1990).
Researchers (see for example Laufer et al, 2004; Sun-Yeon & Yongsook, 2009) reported that the total amount of vocabulary influences students’ reading, writing, speaking, and listening skills. Moreover, recent studies (Farjami 2014; Keshavarz & Mohammadi 2009; Laufer & Eavenhors-Kalouski; 2010) found that vocabulary size can be used as a predictor for reading comprehension. Furthermore, Laufer (1997) decided the minimum vocabulary for understanding reading text in English i.e. 3000 words families. Another study (Zahar, Cobb, and Spada, 2001) claimed that the learner should have knowledge on functional vocabulary and mastery 5000 words families to read and (write) effectively. On the other hand, the recent studies (Laufer & Ravenhort-Kalovski; 2010) increased the standard that is 8000 words families.
These studies suggest that the total amount of vocabulary for L2 proficiency, especially reading proficiency is relative. Thus, the exact
measurement of the total amount of vocabulary for predicting students’ L2 proficiency is important. In order to figure out the students vocabulary proficiency, it is important to analyze the words order whether it is suitable or not.
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So, by identifying the vocabulary profile, it can be seen how far students have learned vocabulary from the textbook.
3. Vocabulary Profile
Concerning the measurement of the total amount of vocabulary above, Laufer and Nation (1997) introduced what so-called l\lexical frequency profile as
a new instrument to measure L2 learners’ vocabulary. They wrote that lexical frequency profile “shows the percentage of words a learner uses at different
vocabulary frequency level. (It also shows) the relative proportion of words from
different frequency levels” (p.311). In their following up study (1999), they
suggested to differentiate between high and low frequency words for knowing at what stage the learner in the development of vocabulary. In addition, Morris and Cobb (2004) studied vocabulary profile as a measurement of academic performance in teaching English as second language and concluded that vocabulary profile is an effective tool for predicting students’ language proficiency.
Due to its advantages of measuring vocabulary size, vocabulary profile is considered as a reliable instrument in vocabulary research. Sung-Yeon and Yongsook (2009) states that “vocabulary profiles provide instructor with two important characteristics of learner vocabulary. First, it allows [instructors] to
access information about L2 learners’ productive vocabulary profile. For instance, if a learner’s vocabulary profile demonstrates large proportion of high frequency
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has to learn more words. Second, knowing L2 learners vocabulary distribution also helps to check the progress learner have made in their vocabulary use.” (p.94) Thus, vocabulary profile gives teachers view about students’ vocabulary use; it indicates which words the students have mastered and which words students need to practice more.
4. Vocabulary Classification
Nation’s (1999) four classification of word frequency as mentioned in the beginning of literature review will be used as the instrument of this study, they are
“high frequency vocabulary (K1 and K2), academic vocabulary (AWL), technical vocabulary and low frequency vocabulary” (p. 19). High frequency vocabulary is vocabulary that is commonly used in the textbook. It includes language feature: article, pronoun, conjunction etc. In vocabulary profile, high frequency vocabulary is known as K1 (word range 1-1000) and K2 (word range 1001-2000). It covers about 80% in a particular text. High frequency vocabulary should include the most frequent 3,000 word families (Schmitt and Schmitt, 2012). Second is academic vocabulary. Academic words occur frequently in academic text and cover 10% of the running words in academic text (Coxhead, 2000). On the other hand, technical vocabulary only appears sometimes frequently in particular text and it covers 3% of the running words. different with the other type, low frequency vocabulary is words that uncommonly exist in a text and it covers only 4%. It also known Off-List Words.
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5. Previous Study of vocabulary profile in textbook
The previous study conducted by Argo Dea Galuh Kirana Ardyny in 2014. The study analyze the vocabulary profile of Introduction to Language Education (2013) course book. The textbook used by students of English Language Education Program in Faculty of Language and Literature, Satya Wacana Christian University, Salatiga. The findings of the study showed the vocabulary used in K-1 was 76.51%, K-2 was 4.30%, K-3 or AWL was 10.47%, and off-list was 8.72%. The results of the study showed that unit 1 of the course book could be relatively easy to comprehend because it had the highest proportion of 1000 word list (K1) and the lowest proportion of Academic Word List (AWL). On the other hand, unit 5 was considered hard to comprehend because of its lowest proportion of K1 and its highest proportion of AWL. Unit 7 considered hard as it had the third highest of AWL. From this study could conclude that teachers should be more aware with the words contained in the course book so that they can decide the choice of words in creating materials for the students.
The other previous study about vocabulary profile is a study from Della
Nathania 2014 entitled ‘Vocabulary Profile of English Textbook Used in Senior High School’. The findings of the study showed the total average of K1 words in grade 10 was 80.10%, grade 11 was 82.30%, and grade 12 was 79.20%. K2 words in grade 10 was 7.10%, grade 11 was 6.10%, and grade 12 was 7.40%. AWL words in grade 10 was 2.50%, grade 11 was 2.20%, and 12 was 2.50%. From this study could be assumed that those textbooks were easy to comprehend. The researcher suggested that teachers did not need to provide students with extensive
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list of vocabulary. In line with this study, the present research investigated a textbook for grade 11 in vocational high school in Salatiga.
THE STUDY
1. Method of Research
This study used descriptive method. According to Rivera, M. and Rivera, R. (2007) discover facts on which professional judgment could be based. Moreover, it involves description, analysis, and interpretation. By using a descriptive method, English textbook for Vocational High School was analyzed in order to figure out the texbook whether it is suitable or not. Therefore, the description will analyze the vocabulary included in the category of K1 words, K2 words, academic words, and off-list.
2. Material
The material of this study was English course textbook of Grade 11 used in vocational high school. The textbook was published by Kemendikbud in 2014 and the title was Bahasa Inggris. The book contains of five chapters. Each chapter has conversations for practicing speaking skill, writing skill, listening skill, and different types of reading text such as narrative and descriptive. For the exercise, there were also grammar including tenses and for reading exercise, there were reading comprehension, matching, synonym of vocabulary etc. The reasons of selection of this textbook as the sample of this study is the textbook is widely used in vocational high school and it is the primary English vocabulary input for the
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students of eleventh grade at their schools. Later on, it would be useful for the teachers in order to explain the material in different background knowledge. 3. Research Instrument
To analyze the data, this study used lextutor as vocabulary profiler. This program is used to examine the vocabulary profile that is used in the textbook. According to Astika (2014), vocabulary profiler is a program that can be used by copy the text into the program. On the other hand, the analysis will show the percentages of type words families according to the four frequency levels: K1 words, K2 words, academic words, and off-list.
4. Data Collection
In collecting the data, every chapter would be copied in word file. The data is just words in English. Thus, the data which is out of context will be omitted. Such as: number, proper noun, identification of book, etc. In order to analyze the data, open the vocabulary profiler from the website on http://www.lextutor.ca/ and choose VP Classic v.4. Then the next was upload the word files the Vocabulary profile to be analyzed.
5. Data Analysis
The analysis was automatically produced by the tool. The result of data analysis was presented in tables. The tables showed how many words the text contained from the following four frequency levels: K1 words, K2 words, academic words, and off-list.
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12 FINDINGS AND DISCUSSION
This section presents the results of the analysis. There were 14442 words analyzed using The Compleat Lexical Tutor, v.4. The vocabulary profile is presented in form of a table. The first part of this section presents the overall vocabulary profile of the textbook showing the proportions of the vocabulary frequency classifications. The second part shows the negative vocabulary profiles of K-1, K-2, K-3 (AWL) with lists of the vocabulary items that were not found in the three textbooks. The last part of this section shows the comparison of vocabulary profile across some chapters of the textbook.
1. The Overall of Vocabulary Profile
Table 1 shows the first row in Table 1 shows three terms; family, type and
token. Word family is head word, for example: the family or head word of
development and developing is develop. Type is different words, for example:
important and interesting are different words. While development and developed,
or developing are considered as the same type. Token is words in a text; the total
number of words in a text. For example, if in a text there are confirm [2], develop [3], since [5], and think [7], the number of token is 17.
Table 1 shows that the majority 84.65% of the vocabulary fell under the most frequently used 1000 words group (K-1). With the additional K-2 word coverage (6.55%) with the cumulative percentage of the word coverage was 91.20%, which indicate that it is close estimate for good comprehension of the texts in the books. By the cumulative percentage of K-1 and K-2 words, the
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textbook could be assumed that the textbook is understandable for Vocational High School students because the percentage of K-1 and K-2 words in the textbook are around 95% as the requirement of good understanding of the textbook.
Table 1. The Overall Vocabulary Profile of The Textbook
FAMILIES %
TYPES %
TOKENS %
CUMULATIVE %
K-1 WORDS
688 60.78%
1172 54.03%
12225 84.65%
84.65%
K-2 WORDS
284 25.09%
375 17.29%
946 6.55%
91.20%
AWL (570 fams tot: 2.570)
160 14.13%
200 9.22%
422 2.92%
94.12%
OFF-LIST ?? 421
19.41%
849 5.88%
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TOTAL 1132+? 2169
100%
14442 100%
In learning vocabulary, the most important thing is the comprehension of the words, sentences and paragraph. According to Hirsch (2003), in learning vocabulary in another language stated that an understanding of 90-95% of the words is necessary for comprehension. On the other hand, 2.92% of vocabulary fell under the academic words (AWL). Academic words are words that are commonly used in academic texts. Teacher need to select whether the academic words that amounted to 422 words used in the textbook need to be introduced to the students in Vocational High Schools. There were 849 words fell under off-list. Off list words are those words that did not include into other categories. This off-list word should not be ignored in teaching, because students at this level need to know about the vocabulary. Then, teachers have to be wise in selecting for useful words in this category. The rest percentage of AWL and off-list words were 5.88%, it means that students need efforts to get better comprehension.
2. Negative vocabulary profiles of the textbook
This section below presents the description of negative vocabulary profiles of the textbook. Negative vocabulary is vocabulary items that are not found in the textbook. The list of negative K-1 words below is useful for teachers in selecting vocabulary items that students may find useful to develop their vocabulary knowledge. For textbook writers, the list provides information in
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assessing the completeness of instructional materials at different grades or frequency levels.
Negative vocabulary profile of K1
This section presents all the word families (=head words) from the K-1 level that were not found in the textbook. The summary of negative vocabulary profile for K-1 level is presented below.
K-1 Total word families: 964
K-1 families in input: 584 (70.95%) K-1 families not in input: 281 (29.15%)
These percentages do not refer to tokens in text but rather number of families. Based on the summary above, there were 70.95% of word families that were found in the textbook. It means that there were 29.15% of word families that were
‘missing’ or not found based on the words listed in New General Service List
(NGSL).
The followings are some of the word families that are not found in the input textbook. The complete word list has been put in Appendix A.
Table 2. Negative Vocabulary Profile of K-1
ABOVE ACCOUNT ACCOUNTABLE ADMIT
ADOPT AFFAIR AGENT ALTHOUGH
ANCIENT ANIMAL APPOINT ARM
ARMY ASSOCIATE ATTEMPT AVERAGE
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BELONG BESIDE BILL BIRD
BLOOD BLUE BRANCH BREAD
BRIDGE BROAD BURN BUSINESS
CAPITAL CAPTAIN CARRY CASTLE
CENTRE CHARGE CHIEF CHURCH
CLAIM COAL COAST COIN
COLONY COLOUR COMMAND COMMITTEE
CONDITION CONTAIN COTTON COUNCIL
COURT CROSS CROWD CURRENT
DARK DEFEAT DEGREE DEMAND
DEPARTMENT DISTINGUISH DOLLAR DRY
DUTY EAR EAST EFFICIENT
EGG ELECT ELEVEN EMPIRE
ENTER EQUAL ESCAPE EXCEPT
EXCHANGE EXERCISE EXPERIMENT EXTEND
Negative Vocabulary profile of K2
This section presents all the word families (=head words) from the K-2 level that were not found in the textbook. The summary of negative vocabulary profile for K-2 level is presented below.
K-2 Total word families: 986
K-2 families in input: 284 (28.80%) K-2 families not in input: 703 (71.30%)
It shows that overall of K-2 do not refer to tokens or number of words in the textbooks but rather number of word families. As the result, there were 28.80% of word families that were found in the textbooks. Furthermore, there were 71.30%
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of word families were ‘missing’ or not found based on the words listed in New General Service List (NGSL).
The followings are some of the word families K-2 that were not found in the input textbook. The complete word list has been put in Appendix B.
Table 3. Negative Vocabulary Profile of K-2
ABROAD ABSENCE ABSENT ABSOLUTELY
ACCUSE ACCUSTOM ACHE ADMIRE
ADVERTISE AEROPLANE AGRICULTURE AHEAD
AIM AIRPLANE ALIVE ALOUD
ALTOGETHER AMBITION AMUSE ANGLE
APART APOLOGY APPLAUD APPLAUSE
APPLE APPROVE ARCH ARREST
ARROW ARTIFICIAL ASH ASIDE
ATTRACT AUTUMN AVENUE AWAKE
AWKWARD AXE BABY BAG
BAGGAGE BAKE BAND BARBER
BARREL BASIN BASKET BATH
BATHE BAY BEAK BEAM
BEARD BEAST BEAT BELL
BELT BEND BERRY BICYCLE
BILLION BIND BIT BITE
BLADE BLAME BLIND BOAST
BOIL BOLD BONE BORDER
BOTTLE BOTTOM BOUND BOUNDARY
BOW BOWL BRAIN BRASS
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This section presents all the word families (=head words) from the K-3 or AWL level that were not found in the textbook. The summary of negative vocabulary profile for K-3 or AWL level is presented below.
AWL Total word families: 569
AWL families in input: 160 (28.12%) AWL families not in input: 410 (72.06%)
Based on the result, these percentages do not refer to tokens in text but rather number of families. As it had been shown, there were 28.12% of word families were found in the textbook. Because of that, there were 72.06% of word families
were ‘missing’ or not found based on the words listed in New General Service
List (NGSL).
The followings are some of the word families K-3 that were not found in the input textbook. The complete word list has been put in Appendix C.
Table 4. Negative Vocabulary Profile of K-3 or AWL
ABANDON ACCESS ACCOMMODATE ACCUMULATE
ACKNOWLEDGE ACQUIRE ADAPT ADEQUATE
ADJACENT ADJUST ADMINISTRATE ADULT
AGGREGATE AID ALBEIT ALLOCATE
ALTER ALTERNATIVE AMBIGUOUS AMEND
ANALOGY ANALYSE ANNUAL APPARENT
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ASSIGN ASSIST ASSURE ATTACH
ATTAIN ATTITUDE ATTRIBUTE AUTHOR
AUTHORITY AUTOMATE AVAILABLE BEHALF
BULK CAPABLE CAPACITY CEASE
CHALLENGE CHANNEL CHART CHEMICAL
CITE CIVIL CLARIFY CLAUSE
COHERENT COINCIDE COLLAPSE COLLEAGUE
COMMENCE COMMENT COMMODITY COMPATIBLE
COMPENSATE COMPILE COMPLEX COMPONENT
COMPOUND COMPREHENSIVE COMPRISE COMPUTE
CONCEIVE CONCENTRATE CONCEPT CONCURRENT
CONFINE CONFIRM CONFLICT CONFORM
CONSENT CONSEQUENT CONSIDERABLE CONSIST
CONSTITUTE CONSTRAIN CONSTRUCT CONSULT
CONTACT CONTEMPORARY CONTRACT CONTRADICT
CONTROVERSY CONVENE CONVERSE CONVERT
COOPERATE COORDINATE CORE CORPORATE
CORRESPOND COUPLE CREDIT CRITERIA
3. Block frequency output of off-list words.
This section presents the description of block frequency output of off-list words of the textbook. Off-list words are words that are not listed in K-1, K-2, or AWL. Using the vocabulary profiler tool, those words have been frequency-blocked per ten words and have been arranged from high to low frequency. This list of words below may be useful for teachers to use which words are necessary for teaching. Then, it also helps teachers to choose words from the list that are
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with 456 tokens and 267 types. In addition, RANK is ranking of words, FREQ is word occurrence frequency, COVERAGE is the percentage of word occurrence, individual or cumulative, and the last column is the vocabulary item. Table 5 below is the lost of blocked frequency output of off-list words. The complete list of blocked frequency has been put in Appendix 4.
Table 5. Block Frequency Output of Off-List Words
RANK FREQ COVERAGE
individ cumulative WORD
1. 1 0.24% 0.24% ABDOMEN
2. 1 0.24% 0.48% ABJECT
3. 1 0.24% 0.72% ABUSE
4. 1 0.24% 0.96% ACKNOWLEDGMENT
5. 1 0.24% 1.20% ADJECTIVE
6. 1 0.24% 1.44% ADVERB
7. 1 0.24% 1.68% AFFECTIONATELY
8. 1 0.24% 1.92% AGGRESSIVE
9. 1 0.24% 2.16% AH
10. 1 0.24% 2.40% AIRLINES
11. 1 0.24% 2.64% AISLE
12. 1 0.24% 2.88% ALAS
13. 1 0.24% 3.12% ALIEN
14. 1 0.24% 3.36% ALMIGHTY
15. 1 0.24% 3.60% ALRIGHT
16. 1 0.24% 3.84% AMAZING
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18. 1 0.24% 4.32% ANTIQUARIAN
19. 1 0.24% 4.56% APOLOGIZING
20. 1 0.24% 4.80% ARE
21. 1 0.24% 5.04% ARTIFACTS
22. 1 0.24% 5.28% ASPIRATIONS
23. 1 0.24% 5.52% ATMOSPHERE
24. 1 0.24% 5.76% ATTENDANTS
4. Comparison of Vocabulary frequency across chapters of the textbook
This section presents the comparison of vocabulary profile across chapters of the textbook. Table 2 below shows the comparison of vocabulary frequency across chapters of the textbook.
Table 6. Comparison of Word Frequency Level
K-1 WORDS (%)
K-2 WORDS (%)
AWL (%) Off-list (%)
CHAPTER 1 CUMULATIVE %
86.13 86.13
5.93 92.76
1.76 94.52
5.48 100
CHAPTER 2 CUMULATIVE %
84.39 84.39
4.45 88.84
4.24 88.24
6.92 100
CHAPTER 3 CUMULATIVE %
85.62 85.62
5.98 91.60
3.67 95.27
4.73 100
CHAPTER 4 CUMULATIVE
79.39 79.39
9.86 89.25
3.15 92.40
7.60 100
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CHAPTER 5 CUMULATIVE %
85.46 85.46
7.39 92.85
2.47 95.32
4.68 100
Based on Table 6 above, the differences of K-1, K-2, AWL, and Off-list words across chapters in the textbook were not very significant. In other words, the proportions of vocabulary items in each frequency level were relatively similar. However, students may have difficulty to learn the textbook because AWL words are usually used in academic texts. Its indicates that the students need much efforts to comprehend. The percentage of K-1 and K-2 words also provide information about difficulty of understanding the textbook as the percentage of K-1 and K-2 words in the textbook are around 95% as the requirement of good understanding of the textbook (Nation, 2001). It also can be said that the textbook is understandable.
Comparison of Chapter 1 vs. Chapter 4
This section shows the comparison across chapter of the book. The comparison presents the token recycling index of the chapter that already compared. Recycling index is the ratio between words that are shared by two chapters and the total number of words in the second chapter that already compared. The index provides important information about similar words in both chapters and unique word in the second chapter. The first comparison was chapter 1 and 4. Those chapters were compared because chapter 4 had the lowest
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percentage of K-1. Besides, Chapter 1 had the highest percentage of K-1. The comparison analysis presents that the token recycling index was 76.02%. It indicates that there were 76.02% similar words in Chapter 1 and Chapter 4. There were 23.98% unique words in Chapter 4. Table 7 below shows the similar and unique words in Chapter 1 and Chapter 4. The complete table has been put in Appendix 5.
Table 7. Shared and Unique Words in Chapter 1 and Chapter 4
Unique to first 872 tokens 340 families
001. fish 66 002. suggest 35 003. say 33 004. wife 24 005. folklore 14 006. enchant 11 007. cottage 10 008. movie 10 009. homework 9 010. live 9 011. emperor 8 012. again 7 013. another 7 014. eat 7 015. idea 7 016. sentence 7
Shared 1775 tokens 284 families
001. the 149 002. you 90 003. be 87 004. of 70 005. to 69 006. i 64 007. and 61 008. a 48 009. she 44 010. have 40 011. this 33 012. in 32 013. do 31 014. it 31 015. with 25 016. for 24
Unique to second 560 tokens 275 families
Freq first (then alpha) 001. invite 51 002. formal 16 003. play 13 004. necklace 9 005. madame 8 006. request 8 007. mister 7 008. mrs 7 009. oh 7 010. pleasure 7 011. wear 7 012. grace 6 013. occasion 6 014. replace 6
VP novel items
Same list
Alpha first 001. abject 1 002. absolute 1 003. accident 1 004. according 1 005. actual 1 006. afford 1 007. alike 1 008. amount 1 009. anniversary 2 010. annoy 1 011. answer 5 012. anxiety 1 013. appear 1
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24 017. water 7
018. before 6 019. get 6 020. hear 6
017. not 22 018. what 22 019. at 19 020. write 19
015. wed 6 016. answer 5 017. ceremony 5 018. dinner 5 019. gown 5 020. lose 5
014. auspicious 1 015. awful 1 016. ball 2 017. bare 1 018. bear 2 019. begin 3 020. believe 1
Comparison of Chapter 2 vs Chapter 5
The second comparison is between Chapter 2 and Chapter 5. Those chapters were compared because chapter 5 had the highest percentage of K-2 (92.85%). Besides, Chapter 2 had the lowest percentage of K-2 (88.84%). The comparison analysis presents that the token recycling index was 78.55%. It indicates that there were 78.55% similar words in Chapter 5 and Chapter 6. Thus, there were 21.45% (100-78.55%) unique words in the Chapter 5. Table 8 below shows the similar and unique words in Chapter 2 and Chapter 5. The complete table has been put in appendix 6.
Table 8. Shared and Unique Words in Chapter 2 and Chapter 5 Unique to first
621 tokens 321 families 001. bully 39 002. issue 16 003. school 13
Shared 2674 tokens 321 families 001. the 163 002. you 162 003. be 160
Unique to second 730 tokens 354 families Freq first (then alpha) 001. letter 70
VP novel items
Same list
Alpha first 001. accompany 1 002. accurate 1
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25 004. article 8
005. corrupt 8 006. fact 8 007. case 7 008. eradicate 7 009. movie 7 010. society 7 011. view 7 012. problem 6 013. social 6 014. aware 5 015. base 5 016. interview 5 017. major 5 018. year 5 019. car 4 020. fear 4
004. i 129 005. to 127 006. and 72 007. a 68 008. he 65 009. of 65 010. it 62 011. in 56 012. write 53 013. this 51 014. have 48 015. for 39 016. do 33 017. not 29 018. person 26 019. will 26 020. so 23
002. postmaster 9 003. rain 9 004. soon 9 005. thank 9 006. dear 8 007. start 8 008. destroy 7 009. happy 7 010. send 7 011. stamp 7 012. address 6 013. hear 6 014. house 6 015. last 6 016. office 6 017. reply 6 018. short 6 019. entire 5 020. faith 5
003. across 2 004. address 6 005. advance 1 006. advantage 1 007. adventure 1 008. advice 2 009. affection 1 010. ah 1 011. air 1 012. already 2 013. angry 2 014. anticipate 2 015. apology 3 016. around 1 017. arrive 1 018. art 2 019. assess 1 020. atmosphere 1
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26 CONCLUSION
This study aims to profile the vocabulary used in the textbook in Vocational High School, to produce list of vocabulary that are not covered in the textbook, and to produce the token (word) recycling index of the textbook.
This study has produced three major results. First, there are 84.65% of K-1 and 6.55% of K-2 words in textbook. By this result, it indicates that the textbook is understandable for Vocational High School students. However, the rest 8.80% of the words require deeper and much efforts in learning. Second, there are 29.15% of K-1, 71.30% of K-2, and 72.06% of academic words that were not found in the textbook. Third, the comparison analysis was done for chapter 1 and chapter 4, and chapter 2 and chapter 5. The comparison analysis of chapter 1 and chapter 4 shows that there are 76.02% words in those chapters that are similar. There are 78.55% words that are similar in chapter 2 and chapter 5. By knowing the analysis, it is useful for teachers to select vocabulary items that students may find useful to develop their vocabulary knowledge.
This study still has limitation, that is: it only used one textbook to analyze. Having more than one book to analyze would be more beneficial for the research about teaching and learning vocabulary.
For the recommendation, I suggest that the teacher need to have reference list of vocabulary in order to know which vocabulary to teach to their student. Teachers may also need to teach the academic words for students. It is important for the students to improve their vocabulary knowledge that will be useful for the students to face the next level of study. Another recommendation, teachers need to
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explore various techniques in the teaching vocabulary. They can use intensive and extensive reading activities as it will be more practical during the class session.
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Kafipour, R., & Naveh, M. H. (2011). Vocabulary learning strategies and their contribution to reading comprehension of EFL undergraduate students in Kerman Province. European Journal of Social Sciences, 23 (4), p. 626. Keshavarz, M. H., & Mohammadi, V. (2009). The effect of unknown
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Laufer, B. (1997). What’s in a word that makes it hard or easy: Some intralexical
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Laufer et al. (2004). Size and strength: do we need both to measure vocabulary knowledge?. Language Testing, 21, 202-226.
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Nation, P., and Ming-Tzu, K. W. (1999). Graded readers and vocabulary. Reading in Foreign Language 12(2): 355-380.
Olmos, C. (2009). An assessment of the Vocabulary Knowledge of Students in the Final Year of Secondary Education: Is Their Vocabulary Extensive Enough?. International Journal of English Studies, 9 (3),73-90 Richard, J. C. (2010). Longman dictionary of language teaching and applied
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Acknowledgements
This study would not have been acomplished without supports and help from many people. First of all, I would like to thank to Allah SWT for his blessing and guidance in finishing this study. I would like to express my sincere gratitude to my beloved Mom and Dad for the incredible efforts in supporting me. Moreover, my brothers and sisters who always remind me in order to finish my thesis. For my supervisor Prof. Dr. Gusti Astika, M.A. Thanks for the patience and guidance during the completion of this study. My best wishes in all your endeavors. Next to my examiner, Anne I. Timotius, M. Ed. Thanks for her suggestion and guidance in examining my thesis. Without their guidance, I would never been able to finish my thesis. I also want to say thank you to my friends; Hasta Pandu, Riki, Dani, Yulio, Mas Stefanus, Teduh and all member of 12’ers. They are extraordinary people.
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33 Appendixes Appendix A
Negative Vocabulary Profile of K1
ABOVE ACCOUNT ACCOUNTABLE ADMIT
ADOPT AFFAIR AGENT ALTHOUGH
ANCIENT ANIMAL APPOINT ARM
ARMY ASSOCIATE ATTEMP AVERAGE
BANK BAR BATTLE BEHIND
BELONG BESIDE BILL BIRD
BLOOD BLUE BRANCH BREAD
BRIDGE BROAD BURN BUSINESS
CAPITAL CAPTAIN CARRY CASTLE
CENTRE CHARGE CHIEF CHURCH
CLAIM COAL COAST COIN
COLONY COLOUR COMMAND COMMITTEE
CONDITION CONTAIN COTTON COUNCIL
COURT CROSS CROWD CURRENT
DARK DEFEAT DEGREE DEMAND
DEPARTMENT DISTINGUISH DOLLAR DRY
DUTY EAR EAST EFFICIENT
EGG ELECT ELEVEN EMPIRE
ENTER EQUAL ESCAPE EXCEPT
EXCHANGE EXERCISE EXPERIMENT EXTEND
FACTORY FAIR FELLOW FIT
FIX FOREIGN FOREST FORMER
FRIDAY FURNISH GAIN GARDEN
GAS GOD GREEN GROUND
GROW HARDLY HOLD HONOUR
HORSE HOT INCH INDEED
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34
JOINT JOINTED JUDGE JUSTICE
KILL LACK LAKE LAND
LARGE LAUGH LAW LAY
LEAD LIFT LIGHT LIP
LOSS MACHINE MANUFACTURE MARKET
MASS MASTER MEASURE MEMORY
MERE METAL MILE MILK
MILLION MINER MONDAY MOREOVER
MOTOR MOUTH NATIVE NECESSITY
NINE NONE NOR NUMERICAL
NUMEROUS OBSERVE OFFICIAL OIL
OPERATE OPPORTUNITY ORDER ORDINARY
OWE PAGE PAINT PER
PLAIN POPULATION POSITION POSSESS
POUND PRESS PRIVATE PRODUCE
PRODUCT PROFIT PROMISE PROOF
PROPERTY PROVE PROVISION QUANTITY
QUARTER QUEEN RACE RANK
RATE REACH RECEIPT RECORD
REDUCE REGARD RELATION RELATIVE
RELIGION REMARK REPRESENT REPUBLIC
RESERVE RESPECT RICH RIDE
RING ROAD ROUGH ROYAL
RUN SAIL SALE SALT
SCARCE SEASON SECRET SECRETARY
SENSE SENSITIVE SHADOW SHIP
SHOOT SHOULDER SILVER SIR
SIZE SNOW SOFT SOLDIER
SORT SOUL SOUND SPIRIT
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35
SQUARE STAGE STANDARD STATION
STEEL STOCK STONE STRANGE
STRIKE STRUGGLE SUBSTANCE SUPPLY
SUPPOSE SURROUND SWORD SYSTEM
TAX TEMPLE THIRTEEN THIRTY
THOUSAND THURSDAY TON TOUCH
TOWN TRAIN TRAVEL TUESDAY
TWELVE UNION UNIVERSITY UNLESS
UNTIL VARIETY VARIOUS VESSEL
VICTORY VIRTUE VOTE WAGE
WAR WEALTH WEST WESTERN
WIDE WINTER WISE WOOD
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36 Appendix B
Negative Vocabulary Profile of K2
ABROAD ABSENCE ABSENT ABSOLUTELY
ACCUSE ACCUSTOM ACHE ADMIRE
ADVERTISE AEROPLANE AGRICULTURE AHEAD
AIM AIRPLANE ALIVE ALOUD
ALTOGETHER AMBITION AMUSE ANGLE
APART APOLOGY APPLAUD APPLAUSE
APPLE APPROVE ARCH ARREST
ARROW ARTIFICIAL ASH ASIDE
ATTRACT AUTUMN AVENUE AWAKE
AWKWARD AXE BABY BAG
BAGGAGE BAKE BAND BARBER
BARREL BASIN BASKET BATH
BATHE BAY BEAK BEAM
BEARD BEAST BEAT BELL
BELT BEND BERRY BICYCLE
BILLION BIND BIT BITE
BLADE BLAME BLIND BOAST
BOIL BOLD BONE BORDER
BOTTLE BOTTOM BOUND BOUNDARY
BOW BOWL BRAIN BRASS
BRAVE BREAKFAST BREATHE BRIBE
BRICK BROADCAST BROWN BRUSH
BUCKET BUNDLE BURIAL BURST
BUS BUSH BUTTER BUTTON
CAGE CALCULATE CALM CAMERA
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CARRIAGE CART CAT CATTLE
CAUTION CAVE CENT CENTIMETRE
CHAIN CHALK CHEAP CHEER
CHEESE CHEQUE CHEST CHICKEN
CHIMNEY CHRISTMAS CIVILISE CLAY
CLEVER CLIFF CLIMB COARSE
COLLAR COMB COMMERCE COMPANION
COMPETE COMPLAIN COMPLICATE COMPOSE
CONFESS CONFUSE CONQUER CONSCIENCE
CONVENIENCE COOK COOL COPPER
COPY CORK CORNER COUGH
COURAGE COW COWARD CRACK
CRASH CREAM CREEP CRIMINAL
CRITIC CRUSH CULTIVATE CUPBOARDS
CURE CURL CURSE CURVE
CUSHION DAMP DARE DEAF
DECAY DECREASE DEED DEER
DEFEND DELAY DESCEND DESK
DESPAIR DEVIL DIAMOND DICTIONARY
DIG DIP DISCIPLINE DISGUST
DISH DISMISS DITCH DIVE
DONKEY DOT DOUBLE DOZEN
DRAWER DROWN DRUM DUCK
DULL DUST EARN EARNEST
EDGE ELASTIC ELDER ELECTRIC
ELEPHANT EMPTY ENCLOSE ENCOURAGE
ENGINE ENTERTAIN ENVY ESSENCE
ESSENTIAL EXACT EXAMINING EXCESS
EXPLODE EXPLORE EXTRA EXTRAORDINARY
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FANCY FASHION FASTEN FAT
FATE FAULT FEAST FEATHER
FEVER FIERCE FILM FINGER
FIRM FLAG FLAME FLASH
FLAT FLAVOUR FLESH FLOUR
FOLD FOND FORBID FORK
FREQUENT FRUIT FRY FUNERAL
FUR GALLON GAP GARAGE
GAY GENEROUS GLORY GOAT
GRADUAL GRAIN GRAM GRASS
GRAVE GREASE GREY GRIND
GUEST GUIDE GUILTY GUN
HAIR HALL HAMMER HANDKERCHIEF
HARBOR HASTE HAT HATE
HAY HEAL HEAP HESITATE
HIDE HINDER HIRE HIT
HOLE HOLLOW HOLY HOOK
HORIZON HOSPITAL HUNT HURRAH
HURRY IDEAL IDLE IMITATE
INFORMALLY INN INQUIRE INSECT
INSTANT INSTRUMENT INSULT INSURE
INTERFERE INTERNATIONAL INTERRUPT INWARD
ISLAND JAW JEWEL JOKE
JOURNEY KEY KICK KILOGRAM
KILOMETRE KISS KITCHEN KNEE
KNEEL KNIFE KNOCK KNOT
LADDER LAMP LAZY LEAF
LEAN LEATHER LEG LIBERTY
LID LIMB LIQUID LITRE
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LOOSE LOYAL LUCK LUMP
LUNG MAD MAP MAT
MEANTIME MEANWHILE MEAT MECHANIC
MEDICINE MELT MEND MERCHANT
MERRY MESSENGER METRE MILD
MILL MILLIGRAM MILLILITRE MILLIMETRE
MINERAL MIX MODERATE MODEST
MONKEY MOTION MOUSE MUD
MULTIPLY MURDER MYSTERY NAIL
NEAT NECK NEEDLE NEGLECT
NEPHEW NEST NET NIECE
NOISE NOON NOSE NUISANCE
NURSE NUT OAR OBEY
OMIT ONWARDS OPPOSE OPPOSITE
ORANGE ORGAN ORIGIN ORNAMENT
OUTLINE PACK PALE PAN
PARCEL PARDON PASSAGE PASSENGER
PASTE PATH PATIENT PATRIOTIC
PATTERN PAUSE PAW PECULIAR
PENCIL PERMANENT PERSUADE PET
PHOTOGRAPH PIG PIGEON PILE
PIN PINCH PINK PINT
PIPE PITY PLANE PLASTER
PLATE PLENTY PLOUGH PLURAL
POCKET POEM POISON POLICE
POLISH POOL POSTPONE POT
POUR POWDER PRAISE PREACH
PREFER PREJUDICE PRETEND PRIEST
PRISON PROBABLE PROCESSION PROFESSION
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PUNCTUAL PUNISH PUPIL PURE
PURPLE PUZZLE QUALIFY QUARREL
QUART QUIET RABBIT RADIO
RAIL RAKE RARE RAT
RAW RAY RAZOR REFRESH
REGULAR REJOICE RELIEVE REMEDY
RENT REPAIR REPRODUCE REPUTATION
RESCUE RESIGN RETIRE REVENGE
REVIEW REWARD RICE RISK
RIVAL ROAR ROAST ROB
ROOF ROOT ROPE ROT
RUB RUBBER RUBBISH RUG
RUST SACRED SACRIFICE SADDLE
SAKE SAND SAUCE SAUCER
SAWS SCALE SCATTER SCENT
SCISSORS SCOLD SCORN SCRAPE
SCRATCH SCREEN SCREW SEIZE
SELDOM SELF SEW SHADE
SHALLOW SHAME SHAVE SHEEP
SHEET SHELF SHELL SHELTER
SHIELD SHILLING SHOCK SHOUT
SHOWER SHUT SICK SILK
SINK SKIRT SLAVE SLIDE
SLIP SLOPE SLOW SMOOTH
SNAKE SOAP SOCK SOIL
SOLEMN SOUP SOUR SOW
SPADE SPARE SPILL SPIN
SPIT SPLENDID SPLIT SPOIL
SPOON SPORT STAIN STAIRS
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STEER STEM STICK STIFF
STING STIR STOCKING STOMACH
STOVE STRAIGHT STRAP STRAW
STRETCH STRICT STRING STRIP
STRIPE STUFF STUPID SUCK
SUGAR SUPPER SUSPECT SWALLOW
SWEAR SWEAT SWEEP SWING
SYMPATHY TAIL TAILOR TAME
TAP TAXI TELEGRAPH TELEPHONE
TEMPER TEMPERATURE TEMPT TENDER
TENT TERRIBLE THICK THIN
THIRST THORN THOROUGH THREAD
THROAT THUMB THUNDER TIDE
TIDY TIE TIGHT TIN
TIP TIRE TITLE TOBACCO
TOE TONGUE TOOL TOOTH
TOUGH TOUR TOWEL TOY
TRACK TRANSLATE TRAY TREMBLE
TRIBE TRUNK TUBE TUNE
TWIST TYPICAL UMBRELLA UNIVERSE
UPPER UPRIGHT UPSET UPWARDS
URGE VAIN VEIL VERSE
VOWEL VOYAGE WAIST WANDER
WARN WASTE WAX WEAK
WEAPON WEAVE WEED WEIGH
WHEAT WHEEL WHIP WHISPER
WHISTLE WICKED WIDOW WINE
WING WIPE WIRE WOOL
WORM WORSHIP WRAP WRECK
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42 Appendix C
Negative Vocabulary Profile of K3 or AWL
ABANDON ACCESS ACCOMMODATE ACCUMULATE
ACKNOWLEDGE ACQUIRE ADAPT ADEQUATE
ADJACENT ADJUST ADMINISTRATE ADULT
AGGREGATE AID ALBEIT ALLOCATE
ALTER ALTERNATIVE AMBIGUOUS AMEND
ANALOGY ANALYSE ANNUAL APPARENT
APPEND APPROXIMATE ARBITRARY ASSEMBLE
ASSIGN ASSIST ASSURE ATTACH
ATTAIN ATTITUDE ATTRIBUTE AUTHOR
AUTHORITY AUTOMATE AVAILABLE BEHALF
BULK CAPABLE CAPACITY CEASE
CHALLENGE CHANNEL CHART CHEMICAL
CITE CIVIL CLARIFY CLAUSE
COHERENT COINCIDE COLLAPSE COLLEAGUE
COMMENCE COMMENT COMMODITY COMPATIBLE
COMPENSATE COMPILE COMPLEX COMPONENT
COMPOUND COMPREHENSIVE COMPRISE COMPUTE
CONCEIVE CONCENTRATE CONCEPT CONCURRENT
CONFINE CONFIRM CONFLICT CONFORM
CONSENT CONSEQUENT CONSIDERABLE CONSIST
CONSTITUTE CONSTRAIN CONSTRUCT CONSULT
CONTACT CONTEMPORARY CONTRACT CONTRADICT
CONTROVERSY CONVENE CONVERSE CONVERT
COOPERATE COORDINATE CORE CORPORATE
CORRESPOND COUPLE CREDIT CRITERIA
CRUCIAL CURRENCY CYCLE DATA
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DERIVE DESPITE DETECT DEVIATE
DEVICE DEVOTE DIFFERENTIATE DIMENSION
DIMINISH DISCRETE DISCRIMINATE DISPLACE
DISPOSE DISTINCT DISTORT DISTRIBUTE
DIVERSE DOCUMENT DOMAIN DOMESTIC
DOMINATE DRAFT DURATION DYNAMIC
ELEMENT EMERGE EMPHASIS EMPIRICAL
ENABLE ENCOUNTER ENERGY ENFORCE
ENHANCE ENORMOUS ENSURE ENTITY
EQUATE EQUIP EQUIVALENT ERODE
ESTATE ETHNIC EVALUATE EVIDENT
EVOLVE EXCEED EXCLUDE EXHIBIT
EXPERT EXPLICIT EXPORT EXPOSE
EXTERNAL EXTRACT FACILITATE FACTOR
FEATURE FEDERAL FEE FILE
FINANCE FINITE FLEXIBLE FLUCTUATE
FORMULA FORTHCOMING FOUNDED FRAMEWORK
FUNDAMENTAL FURTHERMORE GENDER GENERATE
GRANT GUARANTEE GUIDELINE HENCE
HIERARCHY HYPOTHESIS IDENTICAL IGNORANT
IMAGE IMMIGRATE IMPACT IMPLEMENT
IMPLICATE IMPLICIT IMPLY IMPOSE
INCLINE INCORPORATE INDEX INDUCE
INEVITABLE INFER INFRASTRUCTURE INHERENT
INHIBIT INITIAL INITIATE INNOVATE
INPUT INSERT INSIGHT INSPECT
INSTITUTE INTEGRAL INTEGRATE INTEGRITY
INTELLIGENCE INTENSE INTERACT INTERMEDIATE
INTERNAL INTERVAL INTERVENE INTRINSIC
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LABEL LAYER LECTURE LEGAL
LEGISLATE LEVY LIBERAL LICENCE
LIKEWISE LINK LOGIC MAINTAIN
MANIPULATE MARGIN MATURE MAXIMISE
MECHANISM MEDIATE MEDIUM METHOD
MIGRATE MILITARY MINIMAL MINIMISE
MINIMUM MODE MODIFY MONITOR
MOTIVE MUTUAL NEGATE NETWORK
NEUTRAL NEVERTHELESS NONETHELESS NOTION
NOTWITHSTAND NUCLEAR OBTAIN OBVIOUS
OFFSET ONGOING ORIENT OUTPUT
OVERALL OVERLAP OVERSEAS PANEL
PARADIGM PARAGRAPH PARALLEL PARAMETER
PASSIVE PERCEIVE PERCENT PERSIST
PHASE PHENOMENON PHILOSOPHY PLUS
PORTION POSE POSITIVE POTENTIAL
PRACTITIONER PRECEDE PRECISE PREDOMINANT
PRELIMINARY PRESUME PRIME PRINCIPAL
PRIORITY PROCESS PROFESSIONAL PROHIBIT
PROMOTE PROPORTION PROSPECT PROTOCOL
PUBLICATION PURSUE QUALITATIVE QUOTE
RADICAL RANDOM RANGE RATIO
RATIONAL RECOVER REFINE REGIME
REGION REGISTER REGULATE REINFORCE
REJECT RELAX RELEVANT RELUCTANCE
RELY REMOVE RESIDE RESTORE
RESTRAIN RETAIN REVENUE REVERSE
REVISE REVOLUTION RIGID SCENARIO
SCHEME SCOPE SECTION SECTOR
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SEX SHIFT SIGNIFICANT SIMULATE
SITE SO-CALLED SOMEWHAT SPECIFIC
SPECIFY SPHERE STRAIGHTFORWARD STRATEGY
STRESS SUBSEQUENT SUBSIDY SUBSTITUTE
SUCCESSOR SUFFICIENT SUM SUMMARY
SUPPLEMENT SURVIVE SUSPEND SYMBOL
TARGET TASK TEAM TEMPORARY
TENSE TERMINATE THEME THEREBY
THESIS TRACE TRANSFER TRANSFORM
TRANSIT TRANSMIT TRANSPORT TREND
TRIGGER ULTIMATE UNDERGO UNDERLIE
UNDERTAKE UNIFORM UNIFY UTILISE
VALID VEHICLE VERSION VIA
VIOLATE VIRTUAL VISION VISUAL
VOLUME VOLUNTARY WELFARE WHEREAS
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46 Appendix D
Block Frequency Output of Off-List Words
RANK FREQ COVERAGE
individ cumulative WORD
1. 1 0.24% 0.24% ABDOMEN
2. 1 0.24% 0.48% ABJECT
3. 1 0.24% 0.72% ABUSE
4. 1 0.24% 0.96% ACKNOWLEDGMENT
5. 1 0.24% 1.20% ADJECTIVE
6. 1 0.24% 1.44% ADVERB
7. 1 0.24% 1.68% AFFECTIONATELY
8. 1 0.24% 1.92% AGGRESSIVE
9. 1 0.24% 2.16% AH
10. 1 0.24% 2.40% AIRLINES 11. 1 0.24% 2.64% AISLE 12. 1 0.24% 2.88% ALAS 13. 1 0.24% 3.12% ALIEN
14. 1 0.24% 3.36% ALMIGHTY
15. 1 0.24% 3.60% ALRIGHT 16. 1 0.24% 3.84% AMAZING 17. 1 0.24% 4.08% ANNIVERSARY 18. 1 0.24% 4.32% ANTIQUARIAN 19. 1 0.24% 4.56% APOLOGIZING
20. 1 0.24% 4.80% ARE
21. 1 0.24% 5.04% ARTIFACTS 22. 1 0.24% 5.28% ASPIRATIONS
23. 1 0.24% 5.52% ATMOSPHERE
24. 1 0.24% 5.76% ATTENDANTS
25. 1 0.24% 6.00% AUSPICIOUS
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47 27. 1 0.24% 6.48% AWFUL 28. 1 0.24% 6.72% BALI
29. 1 0.24% 6.96% BANNED
30. 1 0.24% 7.20% BANNING
31. 1 0.24% 7.44% BARK
32. 1 0.24% 7.68% BARKS 33. 1 0.24% 7.92% BEACH 34. 1 0.24% 8.16% BEATINGS 35. 1 0.24% 8.40% BLANKET 36. 1 0.24% 8.64% BLANKS 37. 1 0.24% 8.88% BLOOM
38. 1 0.24% 9.12% BOMB
39. 1 0.24% 9.36% BOOKSTORE 40. 1 0.24% 9.60% BOSS
41. 1 0.24% 9.84% BOTHER 42. 1 0.24% 10.08% BOUNTY 43. 1 0.24% 10.32% BROADWAYS 44. 1 0.24% 10.56% BRUISES 45. 1 0.24% 10.80% BULLIED 46. 1 0.24% 11.04% BULLY
47. 1 0.24% 11.28% BULLYING[NUMBER 48. 1 0.24% 11.52% BYE
49. 1 0.24% 11.76% CALENDAR 50. 1 0.24% 12.00% CAMPAIGNS 51. 1 0.24% 12.24% CANCER 52. 1 0.24% 12.48% CAREER 53. 1 0.24% 12.72% CASH 54. 1 0.24% 12.96% CASTE
55. 1 0.24% 13.20% CELEBRATING 56. 1 0.24% 13.44% CIGARETTES
(58)
48
57. 1 0.24% 13.68% CLASSMATE
58. 1 0.24% 13.92% CLASSMATES[NUMBER 59. 1 0.24% 14.16% CLASSROOM
60. 1 0.24% 14.40% CLUTCHES 61. 1 0.24% 14.64% CO
62. 1 0.24% 14.88% COINED
63. 1 0.24% 15.12% COLLOCATIONS 64. 1 0.24% 15.36% COLONIALISM 65. 1 0.24% 15.60% COLUMN 66. 1 0.24% 15.84% COLUMNISTS 67. 1 0.24% 16.08% COMEDY 68. 1 0.24% 16.32% COMIC 69. 1 0.24% 16.56% COMICAL 70. 1 0.24% 16.80% COMPELLED 71. 1 0.24% 17.04% COMPLIMENTARY 72. 1 0.24% 17.28% CONCIERGE
73. 1 0.24% 17.52% CONDONE
74. 1 0.24% 17.76% CONSERVATION 75. 1 0.24% 18.00% CONTINENTS 76. 1 0.24% 18.24% CONTRACTIONS 77. 1 0.24% 18.48% CONVERSATIONAL 78. 1 0.24% 18.72% COOKIE
79. 1 0.24% 18.96% CORAL 80. 1 0.24% 19.20% CORDIALLY 81. 1 0.24% 19.44% CORRODED 82. 1 0.24% 19.68% CORRUPTION 83. 1 0.24% 19.92% COUNTER 84. 1 0.24% 20.16% COZY 85. 1 0.24% 20.40% CRAMPED 86. 1 0.24% 20.64% CRITICISM
(59)
49
87. 1 0.24% 20.88% CUMULATIVE 88. 1 0.24% 21.12% CUTE
89. 1 0.24% 21.36% CYBER 90. 1 0.24% 21.60% DARLING 91. 1 0.24% 21.84% DETESTATION 92. 1 0.24% 22.08% DIALOGUE 93. 1 0.24% 22.32% DIALOGUES 94. 1 0.24% 22.56% DIARY 95. 1 0.24% 22.80% DIGNIFIED 96. 1 0.24% 23.04% DILEMMA 97. 1 0.24% 23.28% DIORAMA 98. 1 0.24% 23.52% DISGRACED 99. 1 0.24% 23.76% DISILLUSION 100. 1 0.24% 24.00% DISILLUSIONED 101. 1 0.24% 24.24% DISTASTEFUL 102. 1 0.24% 24.48% DISTRACTS 103. 1 0.24% 24.72% DISTRESSING 104. 1 0.24% 24.96% DIVORCE 105. 1 0.24% 25.20% DOWNRIGHT 106. 1 0.24% 25.44% DREADFUL 107. 1 0.24% 25.68% DRUG 108. 1 0.24% 25.92% DYNAMISM 109. 1 0.24% 26.16% ECSTATIC 110. 1 0.24% 26.40% EFFORTLESS 111. 1 0.24% 26.64% ELEGANCE 112. 1 0.24% 26.88% ELEGANT 113. 1 0.24% 27.12% ELEMENTARY 114. 1 0.24% 27.36% ELEVATED 115. 1 0.24% 27.60% EMAILS 116. 1 0.24% 27.84% EMOTIONS
(60)
50
117. 1 0.24% 28.08% EMPATHETIC 118. 1 0.24% 28.32% EMPEROR 119. 1 0.24% 28.56% EMPOWERING 120. 1 0.24% 28.80% ENACT
121. 1 0.24% 29.04% ENCHANTED 122. 1 0.24% 29.28% ENDURE 123. 1 0.24% 29.52% ENGAGED 124. 1 0.24% 29.76% ENGAGEMENT 125. 1 0.24% 30.00% ENTERPRISES 126. 1 0.24% 30.24% ENVELOP 127. 1 0.24% 30.48% ERADICATE 128. 1 0.24% 30.72% ERADICATED 129. 1 0.24% 30.96% ERADICATING 130. 1 0.24% 31.20% ERASE
131. 1 0.24% 31.44% ESSAY 132. 1 0.24% 31.68% ETC
133. 1 0.24% 31.92% EVAPORATE 134. 1 0.24% 32.16% EXCLAIMING 135. 1 0.24% 32.40% EXHILARATED 136. 1 0.24% 32.64% FABLES
137. 1 0.24% 32.88% FACIAL 138. 1 0.24% 33.12% FAIRY 139. 1 0.24% 33.36% FAKE
140. 1 0.24% 33.60% FANTASTIC 141. 1 0.24% 33.84% FARCE 142. 1 0.24% 34.08% FLUENT 143. 1 0.24% 34.32% FOAM 144. 1 0.24% 34.56% FOLKLORE 145. 1 0.24% 34.80% FOLKLORES 146. 1 0.24% 35.04% FOLKLORISTIC
(61)
51
147. 1 0.24% 35.28% FOLKLORISTS 148. 1 0.24% 35.52% FOREVER 149. 1 0.24% 35.76% FORMATIVE 150. 1 0.24% 36.00% FORTS 151. 1 0.24% 36.24% FOUNTAIN 152. 1 0.24% 36.48% FRANCS 153. 1 0.24% 36.72% FRANTIC 154. 1 0.24% 36.96% FRANTICALLY 155. 1 0.24% 37.20% FULFILL
156. 1 0.24% 37.44% GAMBITS 157. 1 0.24% 37.68% GAMING 158. 1 0.24% 37.92% GASPS 159. 1 0.24% 38.16% GAZE 160. 1 0.24% 38.40% GAZED 161. 1 0.24% 38.64% GAZING 162. 1 0.24% 38.88% GENRE 163. 1 0.24% 39.12% GESTURES 164. 1 0.24% 39.36% GHASTLY 165. 1 0.24% 39.60% GLAMOROUS 166. 1 0.24% 39.84% GONNA 167. 1 0.24% 40.08% GOWN
168. 1 0.24% 40.32% GRADUATION 169. 1 0.24% 40.56% GRAE
170. 1 0.24% 40.80% GRAMMATICAL 171. 1 0.24% 41.04% GRAPHIC
172. 1 0.24% 41.28% GRAPHICS 173. 1 0.24% 41.52% GRATITUDE 174. 1 0.24% 41.76% GRUDGINGLY 175. 1 0.24% 42.00% GUISES
(62)
52 177. 1 0.24% 42.48% HAIL
178. 1 0.24% 42.72% HAILSTORM 179. 1 0.24% 42.96% HANDWRITTEN 180. 1 0.24% 43.20% HARASS
181. 1 0.24% 43.44% HOMEWORK 182. 1 0.24% 43.68% HORROR 183. 1 0.24% 43.92% HOSTEL 184. 1 0.24% 44.16% HUGE 185. 1 0.24% 44.40% HUMILIATE 186. 1 0.24% 44.64% HUMILIATED 187. 1 0.24% 44.88% HUN
188. 1 0.24% 45.12% HYDROGEN 189. 1 0.24% 45.36% ID
190. 1 0.24% 45.60% IM
191. 1 0.24% 45.84% IMPOLITE 192. 1 0.24% 46.08% INAUGURATE 193. 1 0.24% 46.32% INDONESIAN 194. 1 0.24% 46.56% INEDIBLE 195. 1 0.24% 46.80% INFERIOR 196. 1 0.24% 47.04% ING
197. 1 0.24% 47.28% INGLISH 198. 1 0.24% 47.52% INITIALS 199. 1 0.24% 47.76% INKLING 200. 1 0.24% 48.00% INNOCENT 201. 1 0.24% 48.24% INSISTED 202. 1 0.24% 48.48% INSPIRED 203. 1 0.24% 48.72% INSTINCTIVE 204. 1 0.24% 48.96% INTELLECT 205. 1 0.24% 49.20% INTELLECTUAL 206. 1 0.24% 49.44% INTERVIEW
(63)
53
207. 1 0.24% 49.68% INTERVIEWING 208. 1 0.24% 49.92% INTIMIDATE 209. 1 0.24% 50.16% INTIMIDATING 210. 1 0.24% 50.40% INTIMIDATION 211. 1 0.24% 50.64% INTRICACY 212. 1 0.24% 50.88% IRONING 213. 1 0.24% 51.12% JEWELRY 214. 1 0.24% 51.36% JUNIOR 215. 1 0.24% 51.60% KIDNEY
216. 1 0.24% 51.84% LABORATORY 217. 1 0.24% 52.08% LAUNDRY 218. 1 0.24% 52.32% LEGEND 219. 1 0.24% 52.56% LEGENDS 220. 1 0.24% 52.80% LES 221. 1 0.24% 53.04% LEST 222. 1 0.24% 53.28% LIABILITY 223. 1 0.24% 53.52% LIMELIGHT 224. 1 0.24% 53.76% LOFTY 225. 1 0.24% 54.00% LONGING 226. 1 0.24% 54.24% LOOT 227. 1 0.24% 54.48% LUGGAGE 228. 1 0.24% 54.72% LUXURIOUS 229. 1 0.24% 54.96% LUXURY 230. 1 0.24% 55.20% MADAME 231. 1 0.24% 55.44% MAGAZINE 232. 1 0.24% 55.68% MAGAZINES 233. 1 0.24% 55.92% MAGIC 234. 1 0.24% 56.16% MAGICAL 235. 1 0.24% 56.40% MAILBOX 236. 1 0.24% 56.64% MANS
(64)
54 237. 1 0.24% 56.88% MARIA
238. 1 0.24% 57.12% MARVELOUS 239. 1 0.24% 57.36% MERCILESS 240. 1 0.24% 57.60% MESSES
241. 1 0.24% 57.84% METEOROLOGISTS 242. 1 0.24% 58.08% MISTREATED 243. 1 0.24% 58.32% MONSTERS 244. 1 0.24% 58.56% MOVIE 245. 1 0.24% 58.80% MOVIES 246. 1 0.24% 59.04% NARRATE 247. 1 0.24% 59.28% NARRATOR 248. 1 0.24% 59.52% NASTY 249. 1 0.24% 59.76% NECKLACE 250. 1 0.24% 60.00% NIMBLE 251. 1 0.24% 60.24% NIMBLENESS 252. 1 0.24% 60.48% NNUMBERT 253. 1 0.24% 60.72% NOTEBOOK 254. 1 0.24% 60.96% NOTT
255. 1 0.24% 61.20% NOVEL 256. 1 0.24% 61.44% OK 257. 1 0.24% 61.68% OKAY 258. 1 0.24% 61.92% ONLINE 259. 1 0.24% 62.16% ORAL
260. 1 0.24% 62.40% ORGANIZER 261. 1 0.24% 62.64% OUTSTRIPPED 262. 1 0.24% 62.88% OVERLOOKED 263. 1 0.24% 63.12% OVERRATED 264. 1 0.24% 63.36% OVERWEIGHT 265. 1 0.24% 63.60% PACES
(65)
55
267. 1 0.24% 64.08% PASSERBY 268. 1 0.24% 64.32% PELLETS 269. 1 0.24% 64.56% PERSONALITY 270. 1 0.24% 64.80% PESOS
271. 1 0.24% 65.04% PHRASE 272. 1 0.24% 65.28% PHRASES 273. 1 0.24% 65.52% PHRASING 274. 1 0.24% 65.76% PINNACLE 275. 1 0.24% 66.00% PLAYWRIGHT 276. 1 0.24% 66.24% PLEA
277. 1 0.24% 66.48% PLIGHT 278. 1 0.24% 66.72% PLOT 279. 1 0.24% 66.96% PLOTS 280. 1 0.24% 67.20% PM 281. 1 0.24% 67.44% POLL
282. 1 0.24% 67.68% POLLUTION 283. 1 0.24% 67.92% POORNESS 284. 1 0.24% 68.16% POSTAGE 285. 1 0.24% 68.40% POSTCARD 286. 1 0.24% 68.64% POSTMAN 287. 1 0.24% 68.88% POSTMASTER 288. 1 0.24% 69.12% POSTMASTERS 289. 1 0.24% 69.36% POSTSCRIPT 290. 1 0.24% 69.60% POUTING 291. 1 0.24% 69.84% POWERPOINT 292. 1 0.24% 70.08% PREFERABLY 293. 1 0.24% 70.32% PREREADING 294. 1 0.24% 70.56% PRETEXT 295. 1 0.24% 70.80% PREVALENT 296. 1 0.24% 71.04% PRINCE
(66)
56
297. 1 0.24% 71.28% PRIVACY 298. 1 0.24% 71.52% PRIVILEGE 299. 1 0.24% 71.76% PRIVILEGED 300. 1 0.24% 72.00% PROLIFERATION 301. 1 0.24% 72.24% PRONOUNS
302. 1 0.24% 72.48% PRONUNCIATION 303. 1 0.24% 72.72% PUNISHABLE 304. 1 0.24% 72.96% QUEUE
305. 1 0.24% 73.20% QUIZ
306. 1 0.24% 73.44% RACIALISM 307. 1 0.24% 73.68% RAG
308. 1 0.24% 73.92% RAINFALL 309. 1 0.24% 74.16% RANCHO 310. 1 0.24% 74.40% RAVISHING 311. 1 0.24% 74.64% RECKON 312. 1 0.24% 74.88% REEFS 313. 1 0.24% 75.12% REEL 314. 1 0.24% 75.36% REENACT 315. 1 0.24% 75.60% REFUND
316. 1 0.24% 75.84% RELENTLESSLY 317. 1 0.24% 76.08% REMOTE
318. 1 0.24% 76.32% RESOW 319. 1 0.24% 76.56% REUNION 320. 1 0.24% 76.80% REWRITE 321. 1 0.24% 77.04% ROMANTIC 322. 1 0.24% 77.28% SACKS 323. 1 0.24% 77.52% SAKURA 324. 1 0.24% 77.76% SALUTATION 325. 1 0.24% 78.00% SALUTATIONS 326. 1 0.24% 78.24% SAM
(67)
57 327. 1 0.24% 78.48% SATIRE 328. 1 0.24% 78.72% SCANNING 329. 1 0.24% 78.96% SCARED 330. 1 0.24% 79.20% SCOURGES 331. 1 0.24% 79.44% SCRIPTED 332. 1 0.24% 79.68% SCRUBBING 333. 1 0.24% 79.92% SEASHORE 334. 1 0.24% 80.16% SENIOR 335. 1 0.24% 80.40% SEQUEL 336. 1 0.24% 80.64% SHIVER 337. 1 0.24% 80.88% SHIVERING 338. 1 0.24% 81.12% SIBLINGS 339. 1 0.24% 81.36% SILLY 340. 1 0.24% 81.60% SKILLFUL 341. 1 0.24% 81.84% SKIT 342. 1 0.24% 82.08% SLANG 343. 1 0.24% 82.32% SMASHING 344. 1 0.24% 82.56% SMOOTHNESS 345. 1 0.24% 82.80% SNIFFS
346. 1 0.24% 83.04% SNORKELING 347. 1 0.24% 83.28% SNUG
348. 1 0.24% 83.52% SOFTWARE 349. 1 0.24% 83.76% SOOTHED 350. 1 0.24% 84.00% SOUVENIRS 351. 1 0.24% 84.24% SPARKLING 352. 1 0.24% 84.48% STATESMANSHIP 353. 1 0.24% 84.72% STIMULATION 354. 1 0.24% 84.96% SUBJECTIVE 355. 1 0.24% 85.20% SUITCASE
(68)
58
357. 1 0.24% 85.68% SURPASSED 358. 1 0.24% 85.92% SWEETHEART 359. 1 0.24% 86.16% SWEETIE 360. 1 0.24% 86.40% SWIFTLY 361. 1 0.24% 86.64% SYMPATHIZE 362. 1 0.24% 86.88% TAG
363. 1 0.24% 87.12% TALES 364. 1 0.24% 87.36% TASTY 365. 1 0.24% 87.60% TATTERED 366. 1 0.24% 87.84% TAUNTING 367. 1 0.24% 88.08% TAUNTS 368. 1 0.24% 88.32% TEASED 369. 1 0.24% 88.56% TEASING
370. 1 0.24% 88.80% TECHNOLOGIES 371. 1 0.24% 89.04% TEENAGERS 372. 1 0.24% 89.28% TEMPLATE 373. 1 0.24% 89.52% TENSES 374. 1 0.24% 89.76% TERRIFIC 375. 1 0.24% 90.00% TEXTURE 376. 1 0.24% 90.24% THATS 377. 1 0.24% 90.48% THEATER 378. 1 0.24% 90.72% THIRSTY
379. 1 0.24% 90.96% THOUGHTLESS 380. 1 0.24% 91.20% THOUGHTLESSLY 381. 1 0.24% 91.44% THRONE
382. 1 0.24% 91.68% THY 383. 1 0.24% 91.92% TICK 384. 1 0.24% 92.16% TING 385. 1 0.24% 92.40% TONE 386. 1 0.24% 92.64% TOSSES
(1)
72 130. background 1
131. balance 1 132. bare 1 133. beat 1 134. behave 1 135. below: 1 136. bias 1 137. bother 1 138. bruise 1 139. campaign 1 140. category 1 141. certain 1 142. chair 1 143. cheat 1 144. cigarette 1 145. circumstance 1
146. club 1 147. collocate 1 148. column 1 149. columnist 1 150. commission 1
151. common 1 152. conserve 1 153. context 1 154. contrary 1 155. cramp 1 156. criticism 1 157. cumulative 1 158. cut 1
159. cyber 1 160. damage 1 161. deal 1 162. declare 1 163. deep 1 164. define 1 165. demonstrate 1
166. deny 1 167. depress 1 168. dilemma 1 169. discover 1 170. disease 1 171. distaste 1 172. distract 1
130. block 3 131. build 3 132. choose 3 133. closes 3 134. contribute 3 135. die 3
136. difficult 3 137. etc 3 138. ever 3 139. express 3 140. extreme 3 141. feel 3 142. find 3 143. food 3 144. forward 3 145. front 3 146. fun 3 147. important 3 148. inform 3 149. interest 3 150. long 3 151. miss 3 152. mistake 3 153. name 3 154. new 3 155. other 3 156. over 3 157. question 3 158. react 3 159. really 3 160. reason 3 161. right 3 162. sentence 3 163. show 3 164. since 3 165. there 3 166. while 3 167. who 3 168. yes 3 169. act 2 170. another 2 171. away 2 172. begin 2 173. big 2 174. buy 2 175. call 2
128. smell 2 129. son 2 130. storm 2 131. style 2 132. suggest 2 133. tape 2 134. thief 2 135. type 2 136. valley 2 137. wait 2 138. world 2 139. worry 2 140. accompany 1 141. accurate 1 142. advance 1 143. advantage 1 144. adventure 1 145. affection 1 146. ah 1 147. air 1 148. around 1 149. arrive 1 150. assess 1 151. atmosphere 1 152. aunt 1
153. before 1 154. benefit 1 155. birth 1 156. blanket 1 157. blow 1 158. board 1 159. body 1 160. bond 1 161. brief 1 162. bring 1 163. brother 1 164. busy 1 165. caf� 1 166. calendar 1 167. career 1 168. chance 1 169. check 1 170. close 1 171. cloud 1 172. coffee 1 173. combine 1
128. grudge 1 129. hail 2 130. hailstorm 3 131. happy 7 132. harvest 3 133. hear 6 134. heart 1 135. heaven 2 136. heavy 2 137. hill 2 138. holiday 1 139. hope 5 140. hostel 1 141. hour 1 142. house 6 143. however 1 144. hullo 3 145. hunger 4 146. ice 1 147. id 1 148. ill 1 149. illustrate 1 150. imagine 3 151. immediate 2 152. include 1 153. income 1 154. indicate 1 155. individual 1 156. informal 2 157. initial 2 158. inkling 3 159. inside 1 160. insist 1 161. inspire 1 162. intent 1 163. introduce 2 164. invent 1 165. job 1 166. kidney 2 167. knowledge 1 168. lady 1 169. language 3 170. last 6 171. late 2 172. latter 1 173. leave 1
(2)
73 173. dog 1
174. drink 1 175. drug 1 176. edible 1 177. effect 1 178. either 1 179. elementary 1 180. eliminate 1 181. emotion 1 182. enemy 1 183. engage 1 184. especial 1 185. ethical 1 186. eventual 1 187. explain 1 188. exploit 1 189. fail 1 190. fast 1 191. father 1 192. female 1 193. fight 1 194. figure 1 195. force 1 196. fort 1 197. fright 1 198. function 1 199. half 1 200. hand 1 201. handle 1 202. heat 1 203. honest 1 204. hurt 1 205. impolite 1 206. inferior 1 207. innocent 1 208. instance 1 209. intend 1 210. interpret 1 211. king 1 212. liable 1 213. line 1 214. list 1 215. loud 1 216. manner 1 217. meal 1 218. media 1
176. care 2 177. city 2 178. collect 2 179. consider 2 180. day 2 181. down 2 182. during 2 183. enjoy 2 184. even 2 185. few 2 186. fortune 2 187. grand 2 188. hard 2 189. home 2 190. huge 2 191. just 2 192. justify 2 193. kind 2 194. life 2 195. little 2 196. make 2 197. meaning 2 198. never 2 199. next 2 200. partner 2 201. piece 2 202. play 2 203. point 2 204. publish 2 205. recent 2 206. remember 2 207. state 2 208. stay 2 209. stop 2 210. structure 2 211. student 2 212. support 2 213. talk 2 214. then 2 215. topic 2 216. total 2 217. two 2
218. understand 2 219. usual 2 220. afraid 1 221. against 1
174. company 1 175. competition 1 176. compliment 1 177. conclusion 1 178. continue 1 179. coral 1 180. count 1 181. cousin 1 182. crown 1 183. cup 1 184. cute 1 185. darling 1 186. death 1 187. depend 1 188. dialogue 1 189. diary 1 190. dinner 1 191. display 1 192. disturb 1 193. drama 1 194. draw 1 195. dream 1 196. eager 1 197. early 1 198. ecstatic 1 199. emails 1 200. empower 1 201. erase 1 202. ethics 1 203. excite 1 204. exhilarate 1 205. face 1 206. fall 1 207. final 1 208. fire 1 209. flood 1 210. flow 1 211. flower 1 212. foot 1 213. forgive 1 214. formative 1 215. frame 1 216. freeze 1 217. fresh 1 218. fulfil 1 219. gentleman 1
174. length 1 175. les 1 176. lest 1 177. letter 70 178. limit 2 179. local 1 180. lone 1 181. lose 1 182. mail 2 183. mailbox 2 184. man 1 185. maria 1 186. meet 1 187. message 1 188. meteorology 1 189. miserable 1 190. month 1 191. morning 1 192. mountain 1 193. move 1 194. narrow 2 195. neighbour 1 196. nice 1 197. night 3 198. north 1 199. novel 1 200. odd 1 201. off 1 202. office 6 203. often 1 204. oh 1 205. okay 1 206. once 1 207. only 2 208. open 5 209. organize 1 210. otherwise 1 211. own 1 212. pad 2 213. paper 3 214. party 1 215. pass 2 216. pearl 2 217. pellet 1 218. pen 2 219. penny 1
(3)
74 219. medical 1
220. member 1 221. mental 1 222. minor 1 223. mistreat 1 224. monster 1 225. moral 1 226. music 1 227. nation 1 228. necessary 1 229. neither 1 230. nnumbert 1 231. normal 1 232. notebook 1 233. number 1 234. object 1 235. objective 1 236. occur 1 237. offence 1 238. online 1 239. overlook 1 240. overrated 1 241. overweight 1 242. pleasure 1 243. plight 1 244. plot 1 245. polite 1 246. pollute 1 247. poor 1 248. poverty 1 249. powerpoint 1 250. prefer 1 251. pressure 1 252. privacy 1 253. proliferate 1 254. psychology 1 255. push 1 256. quality 1 257. queue 1 258. raise 1 259. rather 1 260. real 1
261. recommend 1 262. relentless 1 263. remote 1 264. resist 1
222. agree 1 223. almost 1 224. also 1 225. amaze 1 226. apply 1 227. approach 1 228. avoid 1 229. awesome 1 230. ban 1 231. blank 1 232. book 1 233. change 1 234. child 1 235. class 1 236. concern 1 237. content 1 238. convince 1 239. course 1 240. cover 1 241. definite 1 242. difference 1 243. direct 1 244. doubt 1 245. due 1 246. each 1 247. easy 1 248. eat 1 249. employ 1 250. english 1 251. enough 1 252. estimate 1 253. expect 1 254. experience 1 255. eye 1
256. famous 1 257. far 1 258. fill 1 259. fine 1 260. fish 1 261. follow 1 262. form 1 263. free 1 264. future 1 265. gather 1 266. genre 1 267. grade 1
220. glad 1 221. goodbye 1 222. grammar 1 223. grammatical 1 224. gratitude 1 225. grudge 1 226. heart 1 227. holiday 1 228. hostel 1 229. hour 1 230. however 1 231. ice 1 232. id 1 233. ill 1 234. illustrate 1 235. include 1 236. income 1 237. indicate 1 238. individual 1 239. inside 1 240. insist 1 241. inspire 1 242. intent 1 243. invent 1 244. job 1
245. knowledge 1 246. lady 1 247. latter 1 248. leave 1 249. length 1 250. les 1 251. lest 1 252. local 1 253. lone 1 254. lose 1 255. man 1 256. maria 1 257. meet 1 258. message 1 259. meteorology 1 260. miserable 1 261. month 1 262. morning 1 263. mountain 1 264. move 1 265. neighbour 1
220. perfect 1 221. perhaps 1 222. period 1 223. personality 1 224. peso 2 225. phrase 2 226. picture 1 227. pinnacle 3 228. popular 1 229. postman 5 230. postmaster 9 231. postscript 3 232. practical 1 233. pray 2 234. precious 1 235. predict 5 236. prepare 2 237. pretext 3 238. previous 1 239. pride 1 240. pronoun 2 241. proper 3 242. purpose 3 243. quick 2 244. quiz 1 245. rain 9 246. rainfall 4 247. rancho 2 248. rapid 3 249. ready 1 250. red 1 251. reef 1 252. refer 1 253. reflect 3 254. remind 2 255. repeat 1 256. replace 1 257. reply 6 258. resolve 1 259. resow 1 260. rest 1 261. restrict 1 262. reunion 1 263. reveal 1 264. ripe 1 265. round 1
(4)
75 265. resource 1
266. responsible 1 267. result 1 268. rid 1 269. rule 1 270. rush 1 271. sample 1 272. senior 1 273. separate 1 274. service 1 275. seven 1 276. shape 1 277. shoe 1 278. silence 1 279. silly 1 280. similar 1 281. simple 1 282. sister 1 283. skill 1 284. skin 1 285. sleep 1 286. solution 1 287. sore 1 288. speak 1 289. stand 1 290. states 1 291. statistic 1 292. subjective 1 293. suffer 1 294. surface 1 295. survey 1 296. sustenance 1 297. taste 1 298. ten 1 299. tend 1 300. therefore 1 301. three 1 302. toward 1 303. towith 1 304. tragic 1 305. transactional 1
306. traumatic 1 307. treat 1 308. true 1 309. trust 1
268. graphic 1 269. guess 1 270. high 1 271. highlight 1 272. instead 1 273. journal 1 274. less 1 275. low 1 276. magic 1 277. main 1 278. match 1 279. matter 1 280. may 1 281. maybe 1 282. mean 1 283. must 1 284. nature 1 285. note 1 286. offer 1 287. opinion 1 288. option 1 289. overcome 1 290. pain 1 291. plan 1 292. possible 1 293. power 1 294. practise 1 295. prereading 1 296. present 1 297. pronunciation 1
298. provide 1 299. public 1 300. quite 1 301. receive 1 302. reenact 1 303. rock 1 304. role 1 305. sad 1 306. serious 1 307. several 1 308. smoke 1 309. space 1 310. study 1 311. summer 1 312. technology 1
266. nice 1 267. north 1 268. novel 1 269. odd 1 270. off 1 271. often 1 272. oh 1 273. okay 1 274. once 1 275. organize 1 276. otherwise 1 277. own 1 278. party 1 279. pellet 1 280. penny 1 281. perfect 1 282. perhaps 1 283. period 1 284. personality 1 285. picture 1 286. popular 1 287. practical 1 288. precious 1 289. previous 1 290. pride 1 291. quiz 1 292. ready 1 293. red 1 294. reef 1 295. refer 1 296. repeat 1 297. replace 1 298. resolve 1 299. resow 1 300. rest 1 301. restrict 1 302. reunion 1 303. reveal 1 304. ripe 1 305. round 1 306. safe 1 307. salary 1 308. scan 1 309. seed 1 310. settle 1 311. shine 1
266. sack 2 267. safe 1 268. salary 1 269. salutations 2 270. salute 2 271. scan 1 272. scene 3 273. second 2 274. seed 1 275. sell 2 276. send 7 277. settle 1 278. shine 1 279. shop 2 280. short 6 281. sibling 1 282. sight 1 283. sign 2 284. signature 3 285. sincere 4 286. sit 2 287. situate 5 288. skit 2 289. sky 2 290. slang 1 291. slight 1 292. smell 2 293. snorkeling 1 294. sole 1 295. son 2 296. soon 9 297. source 1 298. south 1 299. souvenir 1 300. speed 1 301. staff 1 302. stamp 7 303. start 8 304. still 1 305. storm 2 306. stream 1 307. strength 1 308. style 2
309. subordinate 1 310. succeed 1 311. such 4
(5)
76 310. under 1
311. vendor 1 312. venue 1 313. victim 1 314. viewpoint 1 315. visible 1 316. whether 1 317. wildlife 1 318. without 1 319. witness 1 320. yet 1 321. yogurt 1
313. text 1 314. than 1 315. though 1 316. tick 1 317. too 1 318. warm 1 319. where 1 320. why 1 321. woman 1
312. sibling 1 313. sight 1 314. slang 1 315. slight 1 316. snorkeling 1 317. sole 1 318. source 1 319. south 1 320. souvenir 1 321. speed 1 322. staff 1 323. still 1 324. stream 1 325. strength 1 326. subordinate 1 327. succeed 1 328. sudden 1 329. surprise 1 330. suspicion 1 331. sweetheart 1 332. sympathise 1 333. test 1
334. throw 1 335. trick 1 336. trip 1 337. turn 1 338. uncle 1 339. unflinching 1 340. until 1 341. urgent 1 342. vary 1 343. vast 1 344. visit 1 345. voice 1 346. weather 1 347. wednesday 1 348. welcome 1 349. wet 1 350. white 1 351. wind 1 352. wrench 1 353. xoxo 1 354. yesterday 1
312. sudden 1 313. suggest 2 314. surprise 1 315. suspicion 1 316. sweet 3 317. sweetheart 1 318. sympathise 1 319. tape 2
320. test 1 321. thank 9 322. thief 2 323. through 5 324. throw 1 325. top 4 326. trick 1 327. trip 1 328. turn 1 329. type 2 330. uncle 1 331. unflinching 1 332. until 1 333. urgent 1 334. valley 2 335. vary 1 336. vast 1 337. visit 1 338. voice 1 339. wait 2 340. weather 1 341. wednesday 1 342. welcome 1 343. wet 1 344. white 1 345. whole 3 346. wife 3 347. wind 1 348. wish 5 349. wonder 3 350. world 2 351. worry 2 352. wrench 1 353. xoxo 1 354. yesterday 1
(6)