4.1.2 Test Scoring
After administrating the test, I got the result of the students’ achievement as shown in appendix 9 and 10.
In order to further know the students’ achievement in detail; I used the following formula to find out the achievement of each component. The formula:
Ssa = ∑OSc X100
Stsc-Ss Where: Ssa = Students’ achievement
∑OSc = Number of obtained scores Stsc = Sub total score
∑Ss = Number of students
4.2 Computation between the Two Means
After getting all the scores, the computation was made. The first way to know the significant difference of the experiment could be seen through the difference of
the two means. The following formula was used to get the means: ∑Xe ∑Xc
Me = Mc = N N
Where, Me = the mean score of the experimental group ∑Xe = the sum of all scores of the experimental group
Mc = the mean score of the control group ∑Xc = the sum of all scores of the control group
N = the number of the subject sample
The score distribution of the experimental and control groups can be seen in Appendix 11 and 12. The computation of the scores of the experimental group and
control group was calculated as follows: ∑Xe
Me = N
2187.50 = = 72.91
30
The mean score of the experimental group was 72.91 ∑Xe
Me = N
2136 = = 7120
30
The mean score of the control group was 71.20 If we compared the two means it was clear that the mean of the experimental
group was higher than that of the control group. The difference between the two means was 1.71. To make the analysis more reliable, I analyzed by using t-test
formula as stated in chapter III. Using t-test formula could see the difference between the two means.
t =
⎟ ⎠
⎞ ⎜
⎝ ⎛
+ ⎟
⎟ ⎠
⎞ ⎜
⎜ ⎝
⎛ −
+ +
−
∑ ∑
N N
N N
y x
M M
Y X
Y X
1 1
2
2 2
Arikunto, 1998:306 Where, t
: t-test M
x
: the mean difference of the experimental group,
M
y
: the mean difference of the control group, Nx
: the number of the students of the experimental group, Ny
: the number of the students of the control group, ∑x
2
: sum of quadrate deviation of the experimental group, ∑y
2
: sum of quadrate deviation of the control group. Before applying the t-test formula, we should find out
∑x
2
and ∑y
2
first. The step to get
∑x
2
and ∑y
2
was: ∑X
2
∑X
2
∑x2 = ∑X - ∑x2 = ∑X - N N
122
2
122
2
= 756 - = 1559 - 30 30
= 756 – 496.13 = 1559 – 496.13 = 259.87 = 1062.87
t =
[ ]
⎟ ⎠
⎞ ⎜
⎝ ⎛
+ ⎟
⎠ ⎞
⎜ ⎝
⎛ −
+ +
− 30
1 30
1 2
30 30
87 .
1062 87
. 259
06 ,
4 7
. 6
t = ⎟
⎠ ⎞
⎜ ⎝
⎛ ⎟
⎠ ⎞
⎜ ⎝
⎛ 30
2 58
87 .
1322 64
. 2
= 15
. 2
23 .
1 64
. 2
=
Nx + Ny – 2 = 30 + 60 – 2 = 58 = 1,71 T-calculation is higher than t-table.
After getting t-value, I consulted the critical value of the t-table to check whether the difference was significant or not. Before the experiment had been
conducted, the level significant to be used in the experiment had divided first. I used the 5 .05 alpha level significance as usually used in psychological and
educational research. The number of subjects in this experiment for experimental and control group
were 60 with the degree of freedom df 58, that was N1+N2-2. At the 5 .05 alpha level of significance, the obtained critical value is 2.15. It is higher than the
critical value on the table 2.151.71 so the difference is statistically significant. Based on the computation there was significant difference between teaching writing
using small group discussion and teaching writing without small group discussion. It can be seen by the result of the test where the students taught writing using small
group discussion got higher grades than the students taught writing without small group discussion.
4.3 Grade Achievement
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