9-12 to find information to evaluate the
grammatical structures, vocabularies and pronunciation of the materials
Nunan 2004: 174, BSNP
2014, Celce-Murcia
2001: 425 13-14
to find information to evaluate the language skills covered in the materials
Celce-Murcia 2001: 425, BSNP
2014 15-20
to find information to evaluate the activities in the materials
Nunan 2004: 174, Celce-Murcia
2001: 425, BSNP 2014, Hutchinson
and Waters 1987: 102-103
21-23 to find information to evaluate the
organisation of the materials Hutchinson
and Waters
1987: 102, Brown 2001:
142, Nunan 2004: 174,
Tomlinson 1998:
7-21, BSNP 2014
24-27 to find information to evaluate the
layout of the designed materials Hutchinson and
Waters 1987: 107, Brown 2001:
142, Tomlinson 1998: 7, Celce-
Murcia 2001: 426
F. Data analysis techniques
There are two types of data in this research. They are qualitative and quantitative data. The qualitative data were obtained from the interview session
with the teacher. Burns 2010 proposes the main tools for analyzing qualitative data. They are categorizing and analysing talk. The deductive coding in
categorizing data as proposed by Burns 2010: 107 was used to match the data with the developed categories. As the result, there were opinions and suggestions
from the vocational high school teacher about what the appropriate materials should be and the target needs. The result of observations were in the form of
supported documents. These documents were used to find out the target needs. Furthermore, there are also quantitative data obtained from the first and the
second questionnaires. The first questionnaire needs analysis was in the form of multiple choice questions while the second questionnaire expert judgements
used the five-point scale of Likert. The points —as provided by Burns 2010—are
extremely well, very well, fairly well, a little and not at all. The first questionnaire was analysed manually in order to get the
percentage of each answer. Then, the second questionnaire distributed to experts was analysed by measuring the mean values. It was calculated by following the
formula proposed by Suharto 2006: 51 below. Mn =
∑f
ᵡ
N To put all the mean values in the category, range was used to classify the mean
values in classes Suharto, 2006. The method to calculate it was the same with the score conversion, i.e. finding the class interval for determining the category.
The class interval was calculated based on the following procedure. First, to find the range of the class, the formula is R = X highest
– X lowest. Next, the result of the calculation was divided by the desired number of the class these case are 5
classes. Based on the calculation, the class interval could be presented in Table 12 below.
Table 12. Quantitative Data Conversion
Scale Interval of the
mean values The other form of
the interval Category
5 4.6
X 4.6 Extremely well
4 3.7
– 4.5 3.7 X ≤ 4.5
Very well 3
2.8 – 3.6
2.8 X ≤ 3.6 Fairly well
2 1.9
– 2.7 1.9 X ≤ 2.7
A little 1
1.8 X 1.8
Not at all
G. Validity
