48
Table 4.5 The Average Scores of Pre-Test and Post-Test of
the Experimental and Control Groups
Average Score of Pre-Test
Average Score of Post-Test
The Difference between Pre-Test
and Post-Test Experimental Group
42.21 60.30
18.09 Control Group
41 56.45
15.45 The Difference
between Experimental and Control Groups
1.21 3.85
Based on the result above, it shows that the difference of the pre-test score of the experimental and control groups is 1.21, while the difference average
score of the post-test is 3.85. In addition, the difference between the pre-test and the post-test of experimental group is 18.09. It is higher than the control group
which has average score of 15.45. Besides, I also compared the gain of the pre-test and the post-test result.
It shows that the progress of the experimental group 18.56 has higher gain than control group 15.25. The score is shown on the table as follows:
Table 4.6 The Percentage of the Gain of Pre-Test and Post-Test Experimental Group
Control Group Pre-test
42.44 41.21
Post-test 60.80
56.46 Gain d
18.56 15.25
49
4.8 Difference between Two Means
As mentioned above, especially the information found on the Table 4.5, the mean of the control group was lower than the mean of the experimental group.
Nevertheless, I could not infer that the difference between the two means was significant. Hence, to determine whether the difference between the two means is
statistically significant, I applied t-test formula. Here is the formula: =
: − = ? ∑: + ∑=
: + = − 2 ? 1
: + 1
= Arikunto, 2006:311
Where: t
: t-test Mx
: difference gain of pre and post-test of the experimental group My
: difference gain of pre and post-test of the control group ∑x
2
: the sum of the difference gain of pre and post-test of the experimental group
∑y
2
: the sum of the difference gain of pre and post-test of the control group Nx
: the number of experimental group students Ny
: the number of control group students Before applying the t-test formula, I calculated the difference gain
between the pre-test and the post-test of the experimental and control groups. The calculation is as follows:
50
= ∑
= 184
33 = 5.57
Therefore, the difference gain of the pre-test and the post-test of the experimental group is 5.57.
= ∑
= 151
33 = 4.57
Meanwhile, the difference gain of the pre-test and post-test of the control group is 4.57.
Where: ∑X
: sum of the difference gain of the pre-test and post-test of the experimental group
∑Y : sum of the difference gain of pre-test and post-test of the control group
n
x
: the number of students of experimental group n
y
: the number of students of control group After finding the difference gain of the pre-test and post-test, I
calculated the sum of the difference gain of the pre and post-test of the experimental and control groups. The calculation is as follows:
∑: = ∑ − ∑
51
= 1142 − 184
33 = 116.06
The sum of the difference gain of the pre and post-test of the experimental group was 116.06.
∑= = ∑ − ∑
= 799 − 151
33 = 108.06
Meanwhile, the sum of the difference gain of the pre and post-test of the control group was 108.06.
Where: ∑X
: the sum of the score difference of pre-test and post-test of the experimental group
∑Y : the sum of the score difference of pre-test and post-test of the control
group ∑X
2
: the sum square of the score difference of pre-test and post-test of the experimental group
∑Y
2
: the sum square of the score difference of pre-test and post-test of the control group
After that, I applied the t-test as follows: =
: − 尠= ? ∑: + ∑=
: + = − 2 ? 1
A
+ 1=
52
= 5.57 − 4.57
B116.06 + 108.06 33 + 33 − 2 C B
1 33 +
1 33C
= D. EF
Then, to interpret the t obtained, I have to find the critical value of the t
table
. First, I counted the degree of freedom. It is the number of the subject from both groups that was obtained from the formula:
+ − 2
. There were 66 students from both groups so that the degree of freedom df was 64. To define the
critical value, I used the interpolation.
t
table
for: df 60 = 2.00
df 120 = 1.98
So, t
table
for df 64 =
.GG H .GG .IJ
=
KG KL KG
G
t = 1.999
Based on the computation above, I obtained that t
value
was 2.18 and the t
table
was 1.999 so the t
value
is higher than t
table.
It means that there is significant difference between the mean of the experimental and control groups.
4.9 Data Interpretation
