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
The first step was making twelve columns. They were made to be filled with the number or value of:
a. NIS
: Students Identification Number b.
X or Y : X refers to students posttest score in the experimental class Y refers to students posttest score in the control class
c. P=
: Probability of students‘ score which was gained from the result of
the score frequency divided by the total number of students. For instance, see table 4.4, NIS X number 5 got score 72 and the
frequency of 72 score was 1. So the value of ‗P‘ was just dividing the
frequency, 1, by the total number of students i.e. 37. The result was 0.0263.
d. p
: Su m probability of students‘ score which was gained from the
result of the previous score of p added by the score of P=
. For instance, see table 4.4, the first
p score was 0.0263 while the second
p score was 0.0526. The first p score was gotten by adding the base score of
p, 0, with the P= first score, 0.0263. The
result was 0.0263. While the second p was gotten by adding the
previous score of p, 0.0263, with the P=
second score, 0.0263. The result was 0.0526 or 0.053.
e. or
: Square degree of students score. For instance, see table 4.4, the value of the first
in the column was gotten from X score, 48, times 48. The result was 2304.
f. ̅
or ̅
: ̅
refered to the average students‘ posttest scores in the
experimental, while ̅
refered to the average students‘ posttest scores
in control class. They we re gotten by dividing the sum of students‘
posttest scores with the number of students. For instance, see table 4.4, the value of
̅ was gotten from 3216 divided by 37. The result
was 86.42.
g. : Variance. The value of variance was gotten from
–
. For instance, see table 4.4, the score of
was 156.132. It was gotten from the result of
–
h. : Standard deviation. The value of standard deviation was gotten by
square rooting the value of . For instance, see table 4.4, the value
of S was 12.495. It was gotten from the result of √ .
i. Z
: Standard score. The value of standard score was gotten from
̅
and the value of ̅ was gotten from
. So, the ̅ value in the table
4.4 was gotten from = 86.42, while the first Z value in the table
4.4 was gotten from = -3.07
j. ɸ
: Probability distribution table of standard normality. The value of ɸ
was gotten from the probability distribution table with significance 5
k. a= p-ɸ : The value of normality observation. It was gotten from p-ɸ.
However, the normality observation that had to be used was the highest one from the list. So, the normality observation that was used
in the table 4.4 was 0.2142 because it was the highest normality observation from the table 4.4.
After that, all data were inputted into the twelve columns and then they were calculated till the following tables were produced.
Table 4.4 Table Data Normality Analysis in the Experimental Class
NIS X
X F p=
p ̅
S Z
ɸ a =
p- ɸ
1 48 1 0.0263 0.026
2304 86.42 156.13
12.4953 -3.1 0.0011
0.02522 2
48 1 0.0263 0.053 2304
86.42 -3.1 0.0011
0.05153 3
68 1 0.0263 0.079 4624
86.42 -1.5 0.0708
0.00815
Table 4.5 Table Data Normality Analysis in the Control Class
NIS Y
Y F p=
p ̅
S Z
ɸ a=
p- ɸ
1 28 1 0.027 0.027
784 68.97 246.58
15.7029 -2.6 0.0045
0.02253 2
36 1 0.027 0.054 1296
68.97 -2.1 0.0179
0.03615 3
40 1 0.027 0.081 1600
68.97 -1.8 0.0322
0.04888 4
40 1 0.027 0.108 1600
68.97 -1.8 0.0322
0.07591 5
44 1 0.027 0.135 1936
68.97 -1.6 0.0559
0.07924 6
52 1 0.027 0.162 2704
68.97 -1.1 0.1401
0.02206 7
56 1 0.027 0.189 3136
68.97 -0.8 0.2033
0.0141 8
56 1 0.027 0.216 3136
68.97 -0.8 0.2033
0.01292 9
60 1 0.027 0.243 3600
68.97 -0.6 0.2843
0.0411 10
64 1 0.027 0.27
4096 68.97
-0.3 0.3745 0.1042
11 68 1 0.027 0.297
4624 68.97
-0.1 0.4761
0.1788 A complete data is available at appendix 5 p. 98
2552 184896
Further, as stated on the tables, the value of normality observation in the experimental class was 0.2142 while the value of normality observation in the
control class was 0.1788. Such values had to be compared with the value of normality table with significance 5 to find whether the two data had a normal
distribution or not. 4
68 1 0.0263 0.105 4624
86.42 -1.5 0.0708
0.03446 5
72 1 0.0263 0.132 5184
86.42 -1.2 0.1251
0.00648 6
76 1 0.0263 0.158 5776
86.42 -0.8 0.2033
0.0454 7
80 1 0.0263 0.184 6400
86.42 -0.5
0.305 0.1208
8 84 1 0.0263 0.211
7056 86.42
-0.2 0.4247
0.2142
A complete data is available at appendix 5 p.98 3216
285152
In this study, the value of normality table that was gotten was 0.218. In other word, the value of normality observation both in the experimental i.e. 0.2142 and
control classes i.e. 0.1788 were lower than the value of normality table i.e. 0.218. In this case, if the value of normality observation was same as or lower than the
value of normality table, it meant that the data had a normal distribution. Conversely, if the value of normality observation was higher than the value of
normality table, it meant that the data did not have a normal distribution. So, in this study, the two data had a normal distribution.
2. The Analysis of the Data Homogeneity
Further, the homogeneity of the data had to be examined also. It was used to check whether the data had equivalent variance or not. To test the homogeneity of
the data, the homogeneity formula that was used was like what was written in the chapter 3. The followings were the formula and its calculation:
F=
F=
F=1.58 Note:
= High variance. See table 4.5, the value of high variance was taken from the value of
in the control class Y = Small variance. See table 4.4, the value of high variance was taken from the
value of in the experimental class X
From the above calculation, the ‗f‘ value or what was called as the value of
homogeneity observation was gotten i.e. 1.58. Such value had to be compared to the value of homogeneity table to determine whether the data had an equivalent
variance or not. In this case, the value of homogeneity table that was found was 1.74. In other word, the value of homogeneity observation i.e. 1.58 was lower than
the value of homogeneity table i.e. 1.74. If the value of homogeneity observation was same as or lower than the value of homogeneity table, it meant that the data
had an equivalent variance. Conversely, if the value of homogeneity observation was higher than the value of homogeneity table, it meant that the data did not have
an equivalent variance. So, it could be concluded that the data of this study was homogeny or had an equivalent variance.
3. The Analysis of t-test
T-test was used to examine the truth or false of the study hypothesis. Since the data of this study had a normal distribution and an equivalent variance, the
statistical calculation of t-test that had to be used was parameter statistic. By employing such formula, the following t-test calculations were done:
=
̅ ̅
√
=
√
= 5.29
Note: ̅
= The average students‘ posttest scores in the experimental. See table 4.4
̅ =
The average students‘ posttest scores in control class. See table 4.5 = The variance score in the experimental class. See table 4.4
= The variance score in the control class. See table 4.5 ,
= The number of students in the experimental or control class. The number of students from each class was 37
From the above calculation, the value of t observation was gotten i.e. 5.29. Such value had to be compared with the value of t table with significance
5, =
= , and degree of freedom
+ – 2 = 37 + 37 – 2 = 72.
Fortunately, the value of t table was 1.666. In other word, the value of t observation was higher than the value of t table. In this case, if the value of t
observation was same as or higher than the value of t table, it meant that this study rejected hypothesis observation and accepted the hypothesis alternative. Or, it
could be said that this study proved that the use of CALL in teaching past tense was effective for the tenth grade students of SMAN 5 Tangerang Selatan.
4. The Analysis of the Effect Size of CALL
After the use of CALL was perceived to be effective in teaching past tense, the effect size of CALL itself was then examined. To check whether the effect
size of CALL was weak, moderate, or strong, the following formula and calculation were employed.
D=
̅ ̅
D= = 1.24
Note: ̅
= The average students‘ posttest scores in the experimental. See table 4.4
̅ = The average students‘ posttest scores in control class. See table 4.5
= The variance score in the experimental class. See table 4.4 = The variance score in the control class. See table 4.5
From the above calculation, the value of the effect size of CALL was found i.e. 1.24. It meant that the effect size of CALL was strong since its value was
higher than 1.
C.
The Hypothesis Test
As calculated above, the value of t observation was 5.29 while the value of t table was 1.666. So, the value of t observation was higher than the value of t table.
Based on the study hypothesis rule, 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. 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. Alternative hypothesis
: computer-assisted language learning CALL is effective in teaching past tense to the tenth grade students of SMAN 5
Tangerang Selatan. So, it could be inferred that this study agreed that computer-assisted language
learning CALL was effective in teaching past tense to the tenth grade students of SMAN 5 Tangerang Selatan.
D.
The Analysis of Interview Data
As stated in the chapter three, there were 12 students in the experimental class from the lower, middle, and upper pretest scores who were interviewed
about their opinion equipped with their reasons for answering two questions which were directed to bear a conclusion whether CALL was effective in teaching
past tense or not. The result of the interview see appendix 6 p. 102-103 showed that most of
the interviewees stated that learning past tense using CALL was interesting, good, and cool for them. It was interesting because the application was designed with
many interesting features such as music, picture, animation, and colorful template which could
increase students‘ motivation and curiosity to learn. It was good because the application provided students with not only text but also video and
sound which could help students understand the material easily and memorize it longer. It was cool since they had a chance to practice and played a game about
past tense which could automatically show students‘ score and show the students
whether their answers were correct or not so that the students could get immediate feedback after practicing and playing a game about past tense. So, it could be
concluded that the use of CALL in teaching past tense was effective for them.
E.
The Interpretation of the Data
From the result of data analyses above, it could be interpreted that the data of this study had a normal distribution, had an equivalent variance, accepted the
alternative hypothesis of this study, and showed the strong effect of CALL as well.
The data of this study had a normal distribution. It was proved by the value of normality observation in the experimental class, 0.2142, and the control class,
0.1788, which were lower than the value of normality table, 0.218. In this case, if the value of normality observation was same as or lower than the value of
normality table, it could be said that the data had a normal distribution. So, in this study, the two data had a normal distribution.
The data of this study also had an equivalent variance. It was proved by the value of homogeneity observation, 1.58, which was lower than the value of
homogeneity table, 1.74. In this case, if the value of homogeneity observation was same as or lower than the value of homogeneity table, it could be said that the data
had an equivalent variance. So, in this study, the two data had an equivalent variance.
In addition, the data of this study accepted the alternative hypothesis of this study which stated that using CALL in teaching past tense was effective. It was
proved by the value of t observation, 5.29, which was higher than the value of t table, 1.666. In this case, if the value of t observation was same as or higher than
the value of t table, it could be said that this study accepted the alternative hypothesis. So, this study proved that the use of CALL in teaching past tense was
effective for the tenth grade students of SMAN 5 Tangerang Selatan. Further, the data of this study showed that the effectiveness of CALL was
strong. It was proved by the value of the effect size of CALL, 1.24, which was higher than 1. In this case, if the effect size of CALL was same as or higher than
1, it could be said that the effect size of CALL was strong. So, this study showed that the effectiveness of CALL in teaching past tense to the tenth grade students of
SMAN 5 Tangerang Selatan was strong.
63
CHAPTER V CONCLUSION AND SUGGESTION
A. The Conclusion of the Study
From the result of data analysis in the chapter IV, it could be concluded that the use of CALL in teaching past tense to the tenth grade students of SMAN 5
Tangerang Selatan was effective. And, the effectiveness of CALL itself was strong. It was proved by the result of
students‘ gained score in the experimental class which wa
s higher than students‘ gained score in the control class i.e. 46.0520.95. In addition, the result of t-test also showed that the value of t
observation was higher than the value of t table i.e. 5.29 1.666. And, the value of the effect size of CALL i.e. 1.24 was higher than 1. This was in line with the
interview result which showed that all of the interviewees felt satisfied with the use of CALL in learning past tense.
B. The Suggestions of the Study
To enhance the effectiveness of CALL in teaching past tense, below are some suggestions that can be used for further researcher:
1. Teacher should make an application that provides students with a game about
past tense as a media for students to practice past tense. By providing such game in the application, teacher can increase students‘ motivation to practice
past tense. 2.
Teacher should make an application that can automatically show students‘ scores or show whether their answers are correct or not. By giving immediate
feedback to students, teacher can increase students‘ curiosity to solve past
tense questions. 3.
Teacher should include not only text, but also video and sound as a media for presenting the material. By using many features to present the material,
teacher can av oid students‘ boredom in learning past tense and also increase
their understanding about the material. 4.
Further, as suggested by the students, the application that the teacher makes should be designed simpler. In this case, there should not be many menus in
the application that can make students confused. The suggestions above we
re resulted from the writer‘s experience in conducting this study as well as from an interview with some students in the
experimental class.
65
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