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Continued
No. Types of information
The purposes of the questions
Reference
5 Students’ interests
To know what topic learners need to learn
Graves, 2000
6 Students’ learning
preferences To know how students expect
to be taught, activities, the role students expect to take in
class Graves,
2000 7
Students’ attitudes To know their attitude in
using target language and writing skill
Graves, 2000
4. Techniques of Data Analysis
Data analysis technique was conducted with two techniques which were qualitative for interview, and quantitative for questionnaires.
a. Techniques of Data Analysis from Interview
There were several models of process analysis. The model used in this research is posted by Miles and Huberman 1994 which were data reduction, data
display and conclusions drawing and verification. 1
Data reduction was the process of selecting, focusing, simplifying, abstracting and transforming data.
2 Data display was an organized, compressed assembly of information
that permits conclusion drawing and action. 3
Conclusion drawing and verification was the process of making a conclusion from the data collected.
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b. Techniques of Data Analysis from Questionnaires
There were three kinds of questionnaires in this research. The first were students’ profile and needs analysis questionnaires and the second were for revising
the product expert judgment, and the last were questionnaires for evaluating the materials. To know the students’ profile, the researcher used the frequencies and
percentage formula. The percentage is calculated by dividing the frequency of a number of the respondents and the result is multiplied by 100. The formula is
shown below: � =
� � �
1 Frequency Percentage Formula
While
P = percentage
F = frequency
N = total of respondents
100 = fixed number
To analyze the materials review and evaluation, the researcher used descriptive statistics to describe the result. The questionnaires were in the form of
scales that include four opinions which were: strongly agree 4, agree 3, disagree 2 and strongly disagree 1. To know the results or to evaluate the materials, the
researcher also used descriptive statistics and the scales were divided into four which were: strongly agree 4, agree 3, disagree 2 and strongly disagree 1. Here is
the formula proposed by Ravid 2011.
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�̅ = ∑ �
�
2 Mean Formula
While �̅
= mean ∑x
= the sum of all scores N
= the number of scores The data were analyzed by using central tendency measurement to summary
score that is used to represent a distribution of scores. According to Ravid 2011 there are three central tendency measurements: mode, median and mean. In this
study, mean was be used to describe data that is the most representative of the data obtained. Mean, which is also called the arithmetic mean, is calculated by dividing
the total sum of the scores by the number of scores. In order to know that the product developed by the researcher was good and
appropriate for students, the scores were analyzed by using the category proposed by Wagiran 2015. The categories were divided into four, which were very good,
good, fair and poor.
Table 4: Interval Category proposed by Wagiran 2015, 337-338 No Interval
Interpretation Category
1 X
Mi + 1,5SD to Mi + 3SD X . �� . Very good
2 X
Mi to Mi + 1,5 SD X
. �� . Good
3 X
Mi – 1,5SD to Mi X
. �� . Fair
4 Mi
– 3SD to Mi – 1,5 SD �� .
Poor
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While X = Total scores per student
M ideal = highest score 4 + lowest score 1 ÷
M ideal = 4 + 1 = 5 ÷ 2 = 2.5
M ideal = 2.5
Sd ideal = highest score 4 – lowest score 1 ÷
Sd ideal = 4 – 1 ÷ = .
Sd ideal = 0.5 c.
Reliability and Validity
Reliability and validity are the two criteria used to judge the quality of all standardized quantitative measures. Reliability referred to the consistency and
dependability of measuring instruments Ravid, 2001. According to Gall, Gall and Borg 2003, test reliability referred to how much measurement error was presented
in the scores affected by the test. Based on the theory, Gall, Gall and Borg 2003 reliability coefficients vary between values of .00 and 1.00. Thus, the test scores
with a reliability of .80 or higher were sufficiently reliable for most research purposes and 1.00 indicated the perfect reliability of the test score. On the other
hand, validity indicated the accuracy of the instruments Lodico et al., 2010. Moreover, validity also referred to the degree to which instrument measured and
appropriateness. The materials validation was done by the expert judgment. Validation was
judged by several aspects of materials developing. From the results, the materials were valid and can be used for the next steps of the research.
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In order to analyze the reliability of instruments and the stage of materials evaluation, the researcher used the interval scoring proposed by Cohen et al.,
2007. The interval scoring is presented as follow:
Table 5: The Reliability Coefficient of Cronbach’s Alpha Cronbach’s Alpha Coefficient
Interpretation
. Very highly reliable
. − . Highly reliable
. − . Reliable
. − . Marginallyminimally reliable
. Unacceptable low reliability
Cohen et al., 2007, 506
The reliability is used to measure the instruments whether they can be used in this research. The table shows level of reliability. According to the table, score
among 0.70-0.80 means the instruments are reliable. The higher reliable is the score among 0.80-0.90. The highest reliable instruments are the score those higher than
0.90.
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CHAPTER IV FINDINGS AND DISCUSSION
In this chapter, needs analysis was shown in the form of percentages. The syllabus and lesson plan were done in order to design instructional materials for
English writing.
A. Needs Analysis Results
Needs analysis was done to obtain the information from the Second Year students of English Department, Champasak University. The data was analyzed into
percentages and interpreted in order to explain the results.
1. Data from Questionnaires
a. Students’ Profile Part A
Table 6: Gender Gender
Male Female
Total
Participants 14
16
30
Percentages 46.66
53.33 100
Of all of the participants, the results showed that 14 participants were male 46,66, and 16 participants were female which referred to 53,33.
Table 7: Age Age
19 20
21 22
More than 22
Total
Participants 3
8 8
1 10
30
Percentages 10 26.66 26.66 3.33
33.33
100
