40 Where,
M = mean
∑x = the sum of the item score
N = the number of the students
3.5 Procedures of Collecting Data
In collecting the data, this study used a non-equivalent control group design. Based on this design, the students of both experimental and control groups first
individually did the pre-test without giving them any treatment. The result of this test was
used to find out the achievement of the students‟ writing in recount text. In this part, guided writing technique had not been applied yet. The next process
was giving the students treatment of guided writing technique for the experimental group, however, the control group used the conventional method.
Both experimental and control groups had the post-test. This post-test had aim to
measure the students‟ progress on writing recount text.
3.6 Methods of Analyzing Data
Data analysis of this research was a quantitative in which the data measured in the form of numbers. After collecting the data, I analyzed them statistically. In
this study, there were some steps of analyzing data, such as analyzing scoring technique, analyzing mean scores between experimental group and control
group, and analyzing t-test result and hypotheses.
41
3.6.1 Scoring Technique
After conducting pre-test and post-test, I analyzed the students‟ works and
scored them based on the quality of their writing. Moreover, to score the test, I applied the analysis method. This method depended on marking composition
suggested by Brown and Bailey in Brown 2004:244. see Appendix 2. There are five aspects scored and each is scored 20, the maximum score is
100. To get the score of each student, the scoring considered the five components mentioned above.
Finishing scoring the students, I calculated the mean of the students‟ score.
The formula is as follow.
3.6.2 Mean Score Differences between Experimental Group and Control Group
The following formulas were used to get the means scores of two groups to know whether there was the significant difference between both groups or not.
In which: Mx
: the mean of the experimental group
x
: the sum of all scores of the experimental group My
: the mean of the control group y
: the sum of all scores of the control group
42 N
: the number of the subject sample
3.7 t-Test Statistical Analysis
In order to examine the significance difference between experimental and control group, t-test formula was applied. By examining this difference I found
whether the treatment given to the experimental group was effective or not. The result of the consultation was then used as an attempt to verify the hypothesis.
The first thing that should be done was finding t-value. Then, the t-value was compared with the t-table. The formula of the t-value could be written as follows.
̅̅̅ ̅̅̅
Fraenkel and Wallen, 2008:248 In which,
t = t-value
X
1
= mean of experimental group X
2
= mean of control group SED = standard error of the difference
However, before counting t-test, standard error of difference should be computed. The formula of standard error of difference was as follows.
√
Fraenkel and Wallen, 2008:248
43 In which:
SED = standard error of difference SEM
1
= standard error of the mean for experimental group SEM
2
= standard error of the mean for control group To calculate SED, standard error of the mean from both group should be
calculated first. The formula of standard error of the mean was as follows.
√
Fraenkel and Wallen, 2008:248 After getting the result of t-test, the hypotheses of the study was tested by the
following criteria: 1.
Rejecting null hypothesis Ho and accepting alternative hypothesis Ha if t
value
was higher than t
table
t
value
t
table
. 2.
Accepting null hypothesis Ho and rejecting alternative hypothesis Ha if t
table
was higher than t
value
t
table
t
value
.
44
CHAPTER IV DATA ANALYSIS AND DISCUSSION
In this chapter, all data collected during the research were analyzed and interpreted. This chapter is divided into nine subchapters: General Description,
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