11 The selection of the textbook was based on the following criteria. First, the book is for
university students who are expected to comprehend academic words. These words are rarely used in daily life so that it is essential to be learnt by the learners who study English for
Academic Purposes. Second, the book is used in Management and Global Business Strategy Course at Management Program, which has a concentration program called an International
Business in regular class. The communication between students-students and students-teacher uses
Indonesia
most of the time. However, the students’ textbook is written in English also the students are required to work using English for the final project, and presentation.
However, it may affect the students’ performance in delivering the material discussion also
understanding some specific terms used in economic and business area, especially in management, since they use
Indonesia
as the language of instruction.
C. Research Instrument
The instrument of the research was the Vocabulary Profiler that could be accessed at
www.lextutor.ca
. This program can be used to profile the vocabulary into four words, which are K-1, K-2, AWL, and
Off-Lists Word
. Besides, it also shows each percentage of word categories, which can give us a clear picture about the texts being analyzed. In addition, it
also can categorize the words based on its appeared frequency, such as
competitive
shows 24 times in the input text so that it comes under first rank.
D. Data Collection Procedures
Forty-one pages were selected as the sample of the data. All the sample texts in the textbook were copied in
Microsoft Office Words
file by using different name, such as All Chapter and Chapter I up to VI. However, there are some unnecessary words were deleted
before analyzing the texts. First, the tool could not identify punctuation and numbers so that it
12 should be erased. Second, although the tool could analyze proper name e.g. a name of
person, brand, city, company, place, etc, it would not be necessary for students learn these words since it is easy to understand them without consulting the dictionary.
E. Data Analysis Procedures
After collecting data, the texts needed to be copied in the vocabulary profiler. Next was analyzing the data from the vocabulary profiler website. The first step opened
lextutor.ca
website and file named All Chapter. Then, clicked
Vocabprofile
. After that, clicked
VP- Compleat
and
Compleat Web VP
window showed up. Next, selected
classic GWSAWL
option so that the program could analyze the input text into K-1, K-2, AWL, and
Off-Lists Word
OLW. Then, copied the text and clicked
submit window
. Next, saved the result table under name All Chapter Percentage.
In order to find out the negative vocabulary profile of each words category, moved the cursor down of the web page. Then, clicked
VP-negative-classic-1
and Negative VP for K-1 window would appear. After that, clicked
K-1 hea d-words not found
to find out some words that were not included in the input text. Next, copied the result to
Microsoft Office Words
under file name Negative VP K-1. Then, closed the window. After that, the same steps were applied to find out the missing words of K-2 and AWL.
The tool cannot analyze Negative Vocabulary Profile of OWL words yet since it contains some common words that can be remembered easily by the students, such as proper
name e.g. person, place, etc, brand, number, etc. However, the tool can analyze its frequency word in the textbook, which may useful for the teacher to select the some
economic and business words based on the students’ need. The program put the words into rank from the most to the less frequently appear in the input text. First, opened
lextutor.ca
13 website in new tab at the same search engine and clicked
frequency
. Next, selected English in
the
Frequency Home Page Menu
. After that, copied the
OWL
words from previous tab to the
Web Frequency Indexer
window and clicked submit window. Then, copied the result in
Microsoft Office Words
under file name block frequency VP OWL. Token recycling index of the textbook could be analyzed by the tool to find out the
shared and unshared unique words in the input text. First step went to
lextutor.ca
home page. Then, clicked
Text Lex Compare
and copied Chapter I and V into different column provided in the program. Gave name on each column, which were Chapter I and Chapter V.
Selected families in format menu and clicked submit window. The program would automatically analyze these two chapters by comparing the words appeared in the first and
second text. Then, copied the result to
Microsoft Office Words
under name Token Recycling Index Ch.1 and Ch.V. The same steps were applied to find out the token recycling index of
Chapter I and VI.
FINDING AND DISCUSSION
This section presents the answer of the three research questions in three parts. First, the overall vocabulary profile found in the textbook will be discussed in the first part. Second,
the negative words of K-1, K-2, K-3, and OWL are discussed in the second part. It presents the missing words in the input text also block frequency of OWL. Third, comparisons of the
six Chapters as a foundation to analyze the token recycling index between two Chapters are presented in the last part. Besides, it also discusses shared and unique words in both texts.
A. Overall Vocabulary Profile
