= variance of control class = total students in experimental class
= total students in control class
After the value of t observation had been gotten, the value of t table with significance
5, , and degree of freedom
+ -2 had to be sought.
The value of t observation and t table were then compared to know whether CALL was effective in teaching past tense or not.
4. Testing the Effect Size of CALLCohen’s d
After the value of t-test was gotten, the effect size of CALL was then measured. In this case,
Cohen’s d formula was used to measure whether the effect size of CALL was strong or weak.The formula was as follow:
14
d = Mean for experimental class —Mean for control class Pooled standard
deviation Where
Pooled standard deviation = Standard devation of experimental class + Standard devation of control class 2
Then, the criteria below acted as a guidance to determine the effect size of CALL:
0-0.20 = weak effect
0.21-0.50 = modest effect
0.51-1.00 = moderate effect
1.00 = strong effect
G. The Statistical Hypothesis of the Study
14
Daniel Muijs, Doing Quantitatve Research in Education, London: Sage Publications, 2004, pp. 136
—137.
From the result of such analysis, the value of and
could be gotten and could be used to determine the truth or false of the hypotheses. If the value of
was equal to or higher than the value of , the null hypothesis
would be rejected and the alternative hypothesis
would be accepted. Conversely, If the value of
was smaller than the value of , the null hypothesis
would be accepted and the alternative hypothesis
would be rejected. ≥
, is rejected and
is accepted ,
is accepted and is rejected
The followings were the null hypothesis and the alternative hypothesis
of this study. 1.
Null hypothesis : computer-assisted language learning CALL is not
effective in teaching past tense to the tenth grade students of SMAN 5 Tangerang Selatan.
2. Experimental hypothesis
: computer-assisted language learning CALL is effective in teaching past tense to the tenth grade students of SMAN 5
Tangerang Selatan.
51
CHAPTER IV FINDINGS OF THE STUDY
A.
The Description of the Data
After students‘ pretest and posttest scores were gotten from both the
experimental X and control classes Y, the students‘ gained scores could also be
founded by reducing the students‘ posttest scores with pretest scores. The result of
those scores was showed as follow.
Table 4.1 The Scores of Students’ Tests in the Experimental X and Control Classes Y
NIS X
Pretest X
Posttest X
Gained Score X
NIS Y
Pretest Y
Posttest Y
Gained Score Y
1 48
84 36
1 48
68 20
2 32
92 60
2 60
76 16
3 32
96 64
3 24
68 44
4 40
96 56
4 28
36 8
5 24
68 44
5 60
72 12
6 44
92 48
6 56
68 12
7 40
96 56
7 60
84 24
8 56
80 24
8 21
28 7
9 24
88 64
9 52
80 28
A complete data is available at appendix 4, page 96-97 40.86 86.92
46.05 48.03 68.97
20.95
From the table above, there were three things that could be described more detailed below. They were the descriptions
of students‘ pretest scores, students‘ posttest scores, and students‘ gained scores as follows.
1. The Description of Students’ Pretest Scores
The table 4.1 above showed that the students‘ average pretest scores in the
experimental class X was 40.86; while the students‘ average pretest score in the
control class Y was 48.03. Such scores expressed that the initial students‘
knowledge about past tense in the control class Y was higher than those in the experimental class X. In this case, difference was about 7.17 points. To prove it
more clearly, table 4.2 was added as follow.
Table 4.2 Table
frequency of students’ pretest in the experimental X and control classes Y
Score X Frequency X
Score Y Frequency Y
16-25 6
21-27 5
26-35 8
28-34 2
36-45 10
35-41 4
46-55 6
42-48 3
56-65 5
49-55 9
66-75 1
56-62 10
76-85 1
63-69 4
Total 37
Total 37
The table 4.2 gave information about the most frequent pretest score that students got in the experimental X and control classes Y. In the experimental
class X, most of students got scores which fell into interval 36-45. The number of the students which got such score was 10 students. While in the control class
Y, most of students got score in the interval 56-62. The total students which got such score were 10 students. Such information proved that most of students in the
control class Y had much more initial past tense knowledge than those in the experimental class X.
2. The Description of Students’ Posttest Scores
N ot only showing the students‘ pretest scores, table 4.1 also showed the
students‘ posttest scores both in the experimental X and control class Y. In the
experimental class X, students got average posttest scores around 86.92; while in the control class, students got average posttest scores around 68.97. Such scores
expressed that the students‘ average final past tense scores increased both in the
experimental X and control class Y. However, in the experimental class X, the st
udents‘ average posttest score was higher than the students‘ average posttest score in the control class Y. The different score was around 17.95. To prove it
more clearly, table 4.3 was added as follow.
Table 4.3 Table frequency of students
’ posttest in the experimental X and control class Y
Score X Frequency X
Score Y Frequency Y
48-55 2
28-37 2
56-63 38-47
3 64-71
2 48-57
3 72-79
2 58-67
2 80-87
7 68-77
16 88-95
11 78-87
9 96-103
13 88-97
2 Total
37 Total
37
The table 4.3 gave information about the most frequent posttest score that students got in the experimental X and control class Y. As stated on the table,
most of students in the experimental class X got score which fell into interval 96-103. The number of students which got such score was 13 students. While in
the control class Y, most of students got score in the interval 68-77. The total students which got such score were 16 students. Such description proved that most
of students in the experimental class X had much more final past tense knowledge than most of students in the control class Y.
3. The Description of Students’ Gained Scores
Further, table 4.1 also showed the students‘ average gained score both in the
experimental X and control classes Y. In the experimental class X, students
got average gained score around 46.05; while in the control class Y, students got average gained score around 20.95. It showed that students in the experimental
class got much more increasing knowledge about past tense which was higher around 25.10 than students in the control class. So, it could be said that students
who received a treatment using CALL could understand past tense much more than the students who did not receive treatment using CALL.
Further, to get information whether the use of CALL in teaching past tense was effective or not, a statistical analysis had to be done as what was explained
below.
B.
The Analysis of the Data
As stated in the chapter 3, the analysis of the data was to be done through four steps. The steps were examining data normality, data homogeneity, t-test, and
the effect size of CALL. In this case, testing normality and homogeneity had to be done first because the result of such analysis determined which statistical
calculation that had to be used in this study. If the data showed that it had a normal distribution and an equivalent variance, the statistical calculation that had
to be used was parameter statistic. Conversely, if the data did not have a normal distribution andor an equivalent variance, the statistical calculation that had to be
used was non-parameter statistic.
1. The Analysis of the Data Normality
Testing normality was used to check whether the data had a normal distribution or not. By employing the normality formula below, calculation of the
data normality was done through certain steps as follows: a=
p-ɸ Note:
a = value of a p = sum value of data probability
ɸ = value of Kolmogorov table
