The Effectiveness Of Simulation In Speaking Ability Of MAN Model At The 10th Graders Of Palangka Raya - Digital Library IAIN Palangka Raya
CHAPTER IV
RESEARCH FINDING AND DISCUSSION
This chapter discusses : (a) research finding, (b) discussion, (c) data
analysis
A. Research Finding
1. The Result of Pre-Test of Experimental Group
The pre-test was conducted on Saturday 10th may 2014. The test meeting
about 1.30 minute at 12.00-13.30 pm in clas x5. They were 36 student who
followed this test. To make it clear, the writer shows the description of pre-test
score of the data achieaved by the experimental group in table 4.1 below:
Table 4.1
The Result of Pre Test Score of Experimental Group
Student'
code
Rater 1
Rater 2
Final score
E01
69
63
66
E02
71
65
68
E03
67
69
68
E04
71
67
69
E05
69
61
65
E06
69
63
66
E07
67
67
67
E08
73
59
66
E09
69
73
71
E10
69
63
66
E11
73
63
68
E12
71
65
68
40
41
Student'
code
Rater 1
Rater 2
Final score
E13
69
65
67
E14
67
63
65
E15
67
67
67
E16
71
63
67
E17
69
69
69
E18
71
59
65
E19
75
69
72
E20
69
67
68
E21
67
63
65
E22
75
63
69
E23
67
67
67
E24
73
59
66
E25
75
63
69
E26
69
63
66
E27
71
69
70
E28
75
59
67
E29
69
63
66
E30
73
59
66
E31
69
61
65
E32
75
63
69
E33
73
63
68
E34
69
63
66
E35
73
67
70
E36
67
63
65
42
The distribution of students’ pre test scores of experiment group can also
be seen in the following figure.
Figure 4.1 Histogram of Frequency Distribution of Pre Test Scores of
Experiment Group
The figure 4.1 showed the pre test scores of students of experiment group.
It can be seen that there was a student got score 61, and 66. There were two
students got score 63, and 70. There were three students got score 64. There were
five students got score 62, 65 and 69. And there were six students got score 67
and 70.
Table 4.2
The Table Calcuation of Mean, Standar Deviation, And
Standard Error of Mean of Post Test Score In Control
Group Using Spss 21 Program
Statistics
code
Valid
nilai
36
36
0
0
N
Missing
Mean
Std. Error of Mean
Median
67,28
,302
67,00
43
code
Mode
nilai
66
Std. Deviation
1,814
Variance
3,292
Range
7
Minimum
65
Maximum
72
Sum
2422
2. The Result of Pre Test of Control Group
The pre-test was conducted on Saturday 10th may 2014. The test meeting
about 1.30 minute at 12.00-13.30 pm in clas x5. They were 36 student who
followed this test. To make it clear, the writer shows the description of pre-test
score of the data achieaved by the experimental group in table 4.1 below:
Table 4.3
The result of pre-test score of control group
Student'
code
Rater 1
Rater 2
Final score
C01
63
57
60
C02
57
63
60
C03
61
63
62
C04
71
61
66
C05
63
53
58
C06
67
63
65
C07
59
73
66
C08
73
53
63
C09
63
67
65
C10
67
65
66
C11
67
69
68
44
Student'
code
Rater 1
Rater 2
Final score
C12
71
63
67
C13
67
59
63
C14
63
65
64
C15
67
67
67
C16
67
63
65
C17
67
63
65
C18
69
65
67
C19
69
69
69
C20
67
63
65
C21
69
63
66
C22
67
69
68
C23
69
63
66
C24
73
65
69
C25
73
59
66
C26
67
63
65
C27
69
67
68
C28
75
53
64
C29
63
69
66
C30
73
59
66
C31
75
59
67
C32
69
63
66
C33
73
63
68
C34
73
63
68
C35
61
67
64
C36
69
67
68
45
The distribution of students’ pre test scores of control group can also be
seen in the following figure.
Figure 4.4 Histogram of Frequency Distribution of Pre Test Scores of control
Group
The figure 4.4 showed the pre test scores of students of control group. It
can be seen that there was a student got score 58, and 62. There were two students
got score 60, 63, 69,. There were three students got score 64. There were four
students got score 67. There were six student 65 and 68. And there were nine
student got score 66.
Table 4.5
The Table Calcuation Of Mean, Standar Deviation, And
Standard Error of Mean of Pre Test Score In Control Group
Using Spss 21 Program
Statistics
code
Valid
nilai
36
36
0
0
N
Missing
Mean
Std. Error of Mean
65,44
,421
46
code
nilai
Median
66,00
Mode
66
Std. Deviation
2,524
Variance
6,368
Range
11
Minimum
58
Maximum
69
Sum
2356
3. The Result of Post-Test Experimental Group
The pre-test was conducted on Saturday 31th may 2014. The test meeting
about 1.30 minute at 12.00-13.30 pm in class x5. They were 36 student who
followed this test. To make it clear, the writer shows the description of post-test
score of the data achieved by the experimental group in table 4.1 below:
Table 4.5
The result of post-test score of experimental group
Student'
code
Rater 1
Rater 2
Final score
E01
69
73
71
E02
71
63
67
E03
71
69
70
E04
63
69
66
E05
69
67
68
E06
73
69
71
E07
67
73
70
E08
73
65
69
E09
71
75
73
E10
73
65
69
47
Student'
code
Rater 1
Rater 2
Final score
E11
75
69
72
E12
71
69
70
E13
75
59
67
E14
69
67
68
E15
75
69
72
E16
67
69
68
E17
75
65
70
E18
65
67
66
E19
75
71
73
E20
75
69
72
E21
69
71
70
E22
73
69
71
E23
69
69
69
E24
69
65
67
E25
73
65
69
E26
73
71
72
E27
69
73
71
E28
75
59
67
E29
65
67
66
E30
75
67
71
E31
75
65
72
E32
69
71
70
E33
73
71
72
E34
73
69
71
E35
75
65
70
E36
69
65
67
48
The distribution of students’ post test scores of experimental group can
also be seen in the following figure.
Figure 4.6 Histogram of Frequency Distribution of Post Test Scores of
experimental Group
The figure 4.6 showed the post test scores of students of experiment group.
It can be seen that There were two students got score 73. There were three
students got score 66, and 68,. There were four students got score 69. there were
five students got score 67. There were six student got score 71. And there were
eight student got score 70.
Table 4.7
The Table Calcuation of Mean, Standar Deviation, And
Standard Error of Mean of Post Test Score In experimental
Group Using Spss 21 Program
Statistics
code
Valid
nilai
36
36
0
0
N
Missing
Mean
Std. Error of Mean
Median
Mode
69,64
,348
70,00
70
49
code
nilai
Std. Deviation
2,086
Variance
4,352
Range
7
Minimum
66
Maximum
73
Sum
2505
4. The Result of Post-Test Control Group
The pre-test was conducted on Saturday 26th may 2014. The test meeting
about 1.30 minute at 12.00-13.30 pm in class x2. They were 36 student who
followed this test. To make it clear, the writer shows the description of post-test
score of the data achieved by the control group below:
Table 4.5
The result of post-test score of cotrol group
Student'
code
Rater
1
Rater
2
Final score
C01
69
63
66
C02
71
65
68
C03
67
69
68
C04
71
67
69
C05
69
61
65
C06
69
63
69
C07
67
67
67
C08
73
59
70
C09
69
73
71
C10
69
63
66
C11
73
63
68
50
Student'
code
Rater
1
Rater
2
Final score
C12
71
65
70
C13
69
65
67
C14
67
63
66
C15
67
67
67
C16
71
63
67
C17
69
69
69
C18
71
59
65
C19
75
69
72
C20
69
67
68
C21
67
63
65
C22
75
63
69
C23
67
67
67
C24
73
59
66
C25
75
63
69
C26
69
63
68
C27
71
69
70
C28
75
59
67
C29
69
63
70
C30
73
59
66
C31
69
61
65
C32
75
63
69
C33
73
63
68
C34
69
63
66
C35
73
67
70
C36
67
63
65
51
The distribution of students’ post test scores of control group can also be
seen in the following figure
The figure 4.1 showed the post test scores of students of control group. It
can be seen that there was a student got score 71, and 72. There were four
students got score 65. There were six students got score , 66, 68 and 69. And there
were seven students got score 67.
Table 4.7
The Table Calcuation of Mean, Standar Deviation, and
Standard Error of Mean of Post Test Score In control Group
Using Spss 21 Program
Statistics
code
Valid
nilai
36
36
0
0
N
Missing
Mean
Std. Error of Mean
Median
Mode
67,36
,304
67,00
66
Std. Deviation
1,823
Variance
3,323
Range
Minimum
7
65
52
code
Maximum
nilai
72
Sum
2425
5. The Comparison of Final Scores Between Experiment Group and
Control Group
Based on the data above, it can be seen the comparison in Table
Table 4.8
Control
Experiment
group
Group
66
68
68
69
65
69
67
70
71
66
68
70
67
66
67
67
69
65
72
68
65
69
67
66
69
68
70
67
70
66
71
67
70
66
68
71
70
69
73
69
72
70
67
68
72
68
70
66
73
72
70
71
69
67
70
72
71
67
66
71
53
65
69
68
66
70
65
72
70
72
71
70
67
Table 4.9
The Comparison of Final Scores between Control and Experiment Group in
Statistic
Statistics
code
nilai
nilai
36
36
36
0
0
0
Mean
69,64
67,36
Std. Error of Mean
0,348
0,304
Median
70
67
Mode
70
66
Std. Deviation
2,086
1,823
Variance
4,352
3,323
Range
7
7
Minimum
66
65
Maximum
73
72
2505
2425
Valid
N
Missing
Sum
6. Testing Normality and Homogeneity
a. Testing normality
One of the requirements in experimental design was the test of normality
assumption. Because of that, the writer used SPSS 21 to measure the normality of
the data. Test Normality of Pre Test and Post Test Scores were described in Table
4.11.
54
Tests of Normality
a
Kolmogorov-Smirnov
Statistic
df
Shapiro-Wilk
Sig.
Statistic
df
Sig.
pretest
,119
72
,013
,953
72
,009
posttest
,125
72
,007
,954
72
,011
a. Lilliefors Significance Correction
Description:
If respondent > 50 used Kolmogorov-Sminornov
If respondent < 50 used Saphiro-Wilk
The criteria of the normality test Pre Test and Post Test is if the value of r
(probability value/critical value) is higher than or equal to the level of significance
alpha defined (r ≥ α = 0.05), it means that, the distribution is normal. Based on the
calculation using SPSS 21 above, the value of r (probably value/critical value)
from Pre test and Post test of the control group and experimental group in
Kolmogorov-Sminornova was higher than level of significance alpha used or r =
0.013> 0.05 (Pre Test) and r = 0.07> 0.05 (Post Test) so that the distributions are
normal. It meant that the students’ scores of in Pre Test and PostTest had a normal
distribution
b. Testing Homogeneity
The definition of Homogeneity of Variance is when all the variables in
statistical data have the same finite or limited variance. When homogeneity of
variance is equal for a statistical model, a simpler computation approach to
analyzing the data can be used due to a low level of uncertainty in the data.
Because of that, the writer used SPSS 21 to measure the homogeneity of the data.
55
Test of Homogeneity of Variance
Levene Statistic
posttest
Based on Mean
Based on Median
Based on Median and with
adjusted df
Based on trimmed mean
df1
df2
Sig.
1,068
1
70
,305
,591
1
70
,445
,591
1
67,852
,445
1,027
1
70
,314
From the table output above can be known that the value of significance
higher than 0.05 so can be concluted that the data have the same variance or
homogene
7. Data Analysis
a. Testing hypothesis
The writer applied SPSS 21 program to calculated ttest in testing hypothesis
of the study. The result of the ttest using SPSS 21 program was described in Table
bellow.
Table 4.13
Standard Deviation and Standard Error of X1 and X2 Group Statistics
Group Statistics
code
N
Mean
Std. Deviation
Std. Error Mean
x1
36
77,53
4,205
,701
x2
36
72,11
5,371
,895
score
56
Table 4.14
The Calculation ttest Using SPSS 21 Independent Samples Test
Independent Samples Test
Levene's
t-test for Equality of Means
Test for
Equality of
Variances
95%
Sig.
F
Sig.
t
df
(2taile
Confidence
Mean
Std. Error
Difference Difference
Interval of the
Difference
Equal variances
assumed
Equal variances
not assumed
score
d)
,717
,400
Lower
Upper
4,765
70
,000
5,417
1,137
3,149
7,684
4,765
66,192
,000
5,417
1,137
3,147
7,686
The table showed the result of ttest calculation using SPSS 21 program.
Since the result of Test test between experimental and control group had
difference scores of variance, it found that the result of tobserved was 4,765.
To examine the truth or false of null hypothesis stating that using
simulation technique does not increase the 10th grade students’ speaking scores,
the result of ttest was interpreted on the result of degree of freedom to get the ttable.
The result of degree of freedom (df) was 70, it found from the total number of
students in both group minus 2.
57
Table 4.15
The Result of tobserved and ttable/ttest
ttable
Variable tobserved
X1-X2
4.765
Df
5%
1%
2.000
2.660
70
The interpretation of the result of ttest using SPSS 21 Program, it was found
the tobserved was greater than the ttable at 1% and 5% the level significance or 2.000
< 4.765 > 2.660. It could be interpreted based on the result of calculation that Ha
stating that “the students taught by simulation technique gain better apeaking
performance” was accepted and Ho stating “the students taught by simulation
technique do not gain better speaking achievement” was rejected. It meant that
teaching speaking by using speaking technique increases the 10th grade students’
speaking scores at MAN Model Palangka Raya
b. Manual testing
The writer chose the level of significance in 5%, it mean that the level of
significance of the refusal null hypothesis in 5%. The writer decided the level of
significance at 5% due to the hypothesis type stated on non-directional (two-tailed
test).It meant that the hypothesis cannot directly the prediction of alternative
hypothesis. To test the hypothesis of the study, the writer used t-test statistical
calculation. First, the writer calculated the standard deviation and the standard
error of X1 and X2. It was found the standard deviation and the standard error of
PostTest of X1 and X2 at the previous data presentation. It was described in Table
4.16.
58
Table 4.16
Group Statistics
code
N
Mean
Std. Deviation
Std. Error Mean
x1
36
77,53
4,205
,701
x2
36
72,11
5,371
,895
score
TheStandard Deviation and Standard Error of X1 and X2
Description:
X1: Experimental Group
X2: Control Group
The table showed the result of the standard deviation calculation of X1 was
4.205 and the result of the standard error mean calculation was 0.701. The result
of the standard deviation calculation of X2 was 5,371 and the result of the
standard error calculation was 0.895.
The next step, the writer calculated the standard error of the differences mean
between X1 and X2 as follows:
Standard Error of the Difference Mean scores between Variable I and Variable II:
SEM1- SEM2
=
SEM1- SEM2
=
SEM1- SEM2
=
SEM1- SEM2
=
SEM1- SEM2
= 1,136849154461576 = 1,13
59
The calculation above showed the standard error of the differences mean
between X1 and X2 was 0.774. Then, it was inserted theto formula to get the value
of tobserved as follows:
to
=
to
=
to
=
to
= 4,79646017699115 = 4,796
With the criteria:
If ttest (tobserved) > ttable, Ha is accepted and Ho is rejected.
If ttest (tobserved) < ttable, Ha is rejected and Ho is accepted.
Then, the writer interpreted the result of ttest. Previously, the writer
accounted the degree of freedom (df) with the formula:
Df
= (N1 + N2) - 2
= (36 + 36) – 2 = 70
ttable at df 68 at 5% the level of significant = 2,000
The writer chose the level of significance in 5%; it means that the level of
significance of the refusal null hypothesis in 5%. The writer decided the level of
significance at 5% due to the hypothesis typed stated on non-directional (twotailed test). It meant that the hypothesis cannot direct the prediction of alternative
hypothesis.
The calculation above showed the result of ttest calculation as in the Table 4.14.
60
Table 4.17 The Result of ttest
ttable
Variable tobserved
X1-X2
4,765
Df
5%
1%
2,000
2,660
70
Description:
X1
= Experimental Group
X2
= Control Group
tobserved
= The Calculated Value
ttable
= The Distribution of t value
Df
= Degree of Freedom
Based on the result of hypothesis test calculation, it was found that the
value of tobserved was greater than the value of ttable at the level of significance in
5% or 1% that was 2.000 < 4,765 >2.660 It meant Ha was accepted and Ho was
rejected.
It could be interpreted based on the result of calculation that Ha stating
that “the students taught by simulation technique gain better speaking
achievement” was accepted and Ho stating “the students taught by speaking
technique do not gain better speaking achievement” was rejected. It meant that
teaching speaking by using simulation technique increases the 10th grade students’
speaking scores at MAN Model Palangka Raya.
61
B. Data Discussion
In this section are discussed under each objective of the study. The writer
have used the data generated by this experiment study as a backdrop in analysing
the benefits and the knowledge that may be gained from using simulation. Does a
learner’s of speaking is improve his/her speaking ability taught by simulation?
That’s thequestion hunting on the writer’s mind. If the hypothesis is true, then the
writer can say that teaching speaking using simulation is accepted, and thus the
later research can be based on this theoretical foundation.
From the data collected after treatment 6 times, the writer found that
students’ speaking scores are listed in twoseparate lines. SPSS version 21 has
been used to perform Pearson Product-moment correlation, which is conducted to
investigate the valididy and realibility of speaking test. The author of this thesis
made two opposite hypotheses (the null and alternative hypotheses), which
needed to be verified by quantitative analysis. From the analysis in 4.15
concluded that the result of the data analysis showed that the simulation technique
gave significance effect on the students’ speaking scores for the 10th graders of
MAN Model Palangka Raya. The students who were taught using simulation
technique got higher scores than students who were taught without using
simulation technique. It was proved by the mean scores of the students who were
taught using simulation technique was 77.53 and the students who were taught
without using simulation technique was 70.11.
62
This is a little bit different to the one of results from previous study by
Nurviana Hardianty: “Improving Speaking Skill Through The Use Of Simulation
Technique” shows that the use of simulation technique is effective in improving
the students’ speaking skill. It can be seen from the result of the data analysis, in
the pre-test the result was 35.4 while in the post-test the result increased to 57.1.
In this case the writer realize that why the writer’ mean score just raise 7 point, it
because there are several extraneous variable inside process collecting the data
such as: (1) the experience of the writer itself is less, (2) the material is boring (3)
non-interesting class room and noisy. But even so the ability of speaking improve
after treatment is true, support by the theory of fee and joys stated that providing
students with guided practice as they develop language skills for meaningful
communication through whole text.
.
1 Nurviana Hardianty, Improving Speaking Skill Through The Use Of Simulation
Technique, e-Journal of English Language Teaching Society (ELTS) Vol. 1 No. 2 2013 – ISSN
2331-1841. P . 9
RESEARCH FINDING AND DISCUSSION
This chapter discusses : (a) research finding, (b) discussion, (c) data
analysis
A. Research Finding
1. The Result of Pre-Test of Experimental Group
The pre-test was conducted on Saturday 10th may 2014. The test meeting
about 1.30 minute at 12.00-13.30 pm in clas x5. They were 36 student who
followed this test. To make it clear, the writer shows the description of pre-test
score of the data achieaved by the experimental group in table 4.1 below:
Table 4.1
The Result of Pre Test Score of Experimental Group
Student'
code
Rater 1
Rater 2
Final score
E01
69
63
66
E02
71
65
68
E03
67
69
68
E04
71
67
69
E05
69
61
65
E06
69
63
66
E07
67
67
67
E08
73
59
66
E09
69
73
71
E10
69
63
66
E11
73
63
68
E12
71
65
68
40
41
Student'
code
Rater 1
Rater 2
Final score
E13
69
65
67
E14
67
63
65
E15
67
67
67
E16
71
63
67
E17
69
69
69
E18
71
59
65
E19
75
69
72
E20
69
67
68
E21
67
63
65
E22
75
63
69
E23
67
67
67
E24
73
59
66
E25
75
63
69
E26
69
63
66
E27
71
69
70
E28
75
59
67
E29
69
63
66
E30
73
59
66
E31
69
61
65
E32
75
63
69
E33
73
63
68
E34
69
63
66
E35
73
67
70
E36
67
63
65
42
The distribution of students’ pre test scores of experiment group can also
be seen in the following figure.
Figure 4.1 Histogram of Frequency Distribution of Pre Test Scores of
Experiment Group
The figure 4.1 showed the pre test scores of students of experiment group.
It can be seen that there was a student got score 61, and 66. There were two
students got score 63, and 70. There were three students got score 64. There were
five students got score 62, 65 and 69. And there were six students got score 67
and 70.
Table 4.2
The Table Calcuation of Mean, Standar Deviation, And
Standard Error of Mean of Post Test Score In Control
Group Using Spss 21 Program
Statistics
code
Valid
nilai
36
36
0
0
N
Missing
Mean
Std. Error of Mean
Median
67,28
,302
67,00
43
code
Mode
nilai
66
Std. Deviation
1,814
Variance
3,292
Range
7
Minimum
65
Maximum
72
Sum
2422
2. The Result of Pre Test of Control Group
The pre-test was conducted on Saturday 10th may 2014. The test meeting
about 1.30 minute at 12.00-13.30 pm in clas x5. They were 36 student who
followed this test. To make it clear, the writer shows the description of pre-test
score of the data achieaved by the experimental group in table 4.1 below:
Table 4.3
The result of pre-test score of control group
Student'
code
Rater 1
Rater 2
Final score
C01
63
57
60
C02
57
63
60
C03
61
63
62
C04
71
61
66
C05
63
53
58
C06
67
63
65
C07
59
73
66
C08
73
53
63
C09
63
67
65
C10
67
65
66
C11
67
69
68
44
Student'
code
Rater 1
Rater 2
Final score
C12
71
63
67
C13
67
59
63
C14
63
65
64
C15
67
67
67
C16
67
63
65
C17
67
63
65
C18
69
65
67
C19
69
69
69
C20
67
63
65
C21
69
63
66
C22
67
69
68
C23
69
63
66
C24
73
65
69
C25
73
59
66
C26
67
63
65
C27
69
67
68
C28
75
53
64
C29
63
69
66
C30
73
59
66
C31
75
59
67
C32
69
63
66
C33
73
63
68
C34
73
63
68
C35
61
67
64
C36
69
67
68
45
The distribution of students’ pre test scores of control group can also be
seen in the following figure.
Figure 4.4 Histogram of Frequency Distribution of Pre Test Scores of control
Group
The figure 4.4 showed the pre test scores of students of control group. It
can be seen that there was a student got score 58, and 62. There were two students
got score 60, 63, 69,. There were three students got score 64. There were four
students got score 67. There were six student 65 and 68. And there were nine
student got score 66.
Table 4.5
The Table Calcuation Of Mean, Standar Deviation, And
Standard Error of Mean of Pre Test Score In Control Group
Using Spss 21 Program
Statistics
code
Valid
nilai
36
36
0
0
N
Missing
Mean
Std. Error of Mean
65,44
,421
46
code
nilai
Median
66,00
Mode
66
Std. Deviation
2,524
Variance
6,368
Range
11
Minimum
58
Maximum
69
Sum
2356
3. The Result of Post-Test Experimental Group
The pre-test was conducted on Saturday 31th may 2014. The test meeting
about 1.30 minute at 12.00-13.30 pm in class x5. They were 36 student who
followed this test. To make it clear, the writer shows the description of post-test
score of the data achieved by the experimental group in table 4.1 below:
Table 4.5
The result of post-test score of experimental group
Student'
code
Rater 1
Rater 2
Final score
E01
69
73
71
E02
71
63
67
E03
71
69
70
E04
63
69
66
E05
69
67
68
E06
73
69
71
E07
67
73
70
E08
73
65
69
E09
71
75
73
E10
73
65
69
47
Student'
code
Rater 1
Rater 2
Final score
E11
75
69
72
E12
71
69
70
E13
75
59
67
E14
69
67
68
E15
75
69
72
E16
67
69
68
E17
75
65
70
E18
65
67
66
E19
75
71
73
E20
75
69
72
E21
69
71
70
E22
73
69
71
E23
69
69
69
E24
69
65
67
E25
73
65
69
E26
73
71
72
E27
69
73
71
E28
75
59
67
E29
65
67
66
E30
75
67
71
E31
75
65
72
E32
69
71
70
E33
73
71
72
E34
73
69
71
E35
75
65
70
E36
69
65
67
48
The distribution of students’ post test scores of experimental group can
also be seen in the following figure.
Figure 4.6 Histogram of Frequency Distribution of Post Test Scores of
experimental Group
The figure 4.6 showed the post test scores of students of experiment group.
It can be seen that There were two students got score 73. There were three
students got score 66, and 68,. There were four students got score 69. there were
five students got score 67. There were six student got score 71. And there were
eight student got score 70.
Table 4.7
The Table Calcuation of Mean, Standar Deviation, And
Standard Error of Mean of Post Test Score In experimental
Group Using Spss 21 Program
Statistics
code
Valid
nilai
36
36
0
0
N
Missing
Mean
Std. Error of Mean
Median
Mode
69,64
,348
70,00
70
49
code
nilai
Std. Deviation
2,086
Variance
4,352
Range
7
Minimum
66
Maximum
73
Sum
2505
4. The Result of Post-Test Control Group
The pre-test was conducted on Saturday 26th may 2014. The test meeting
about 1.30 minute at 12.00-13.30 pm in class x2. They were 36 student who
followed this test. To make it clear, the writer shows the description of post-test
score of the data achieved by the control group below:
Table 4.5
The result of post-test score of cotrol group
Student'
code
Rater
1
Rater
2
Final score
C01
69
63
66
C02
71
65
68
C03
67
69
68
C04
71
67
69
C05
69
61
65
C06
69
63
69
C07
67
67
67
C08
73
59
70
C09
69
73
71
C10
69
63
66
C11
73
63
68
50
Student'
code
Rater
1
Rater
2
Final score
C12
71
65
70
C13
69
65
67
C14
67
63
66
C15
67
67
67
C16
71
63
67
C17
69
69
69
C18
71
59
65
C19
75
69
72
C20
69
67
68
C21
67
63
65
C22
75
63
69
C23
67
67
67
C24
73
59
66
C25
75
63
69
C26
69
63
68
C27
71
69
70
C28
75
59
67
C29
69
63
70
C30
73
59
66
C31
69
61
65
C32
75
63
69
C33
73
63
68
C34
69
63
66
C35
73
67
70
C36
67
63
65
51
The distribution of students’ post test scores of control group can also be
seen in the following figure
The figure 4.1 showed the post test scores of students of control group. It
can be seen that there was a student got score 71, and 72. There were four
students got score 65. There were six students got score , 66, 68 and 69. And there
were seven students got score 67.
Table 4.7
The Table Calcuation of Mean, Standar Deviation, and
Standard Error of Mean of Post Test Score In control Group
Using Spss 21 Program
Statistics
code
Valid
nilai
36
36
0
0
N
Missing
Mean
Std. Error of Mean
Median
Mode
67,36
,304
67,00
66
Std. Deviation
1,823
Variance
3,323
Range
Minimum
7
65
52
code
Maximum
nilai
72
Sum
2425
5. The Comparison of Final Scores Between Experiment Group and
Control Group
Based on the data above, it can be seen the comparison in Table
Table 4.8
Control
Experiment
group
Group
66
68
68
69
65
69
67
70
71
66
68
70
67
66
67
67
69
65
72
68
65
69
67
66
69
68
70
67
70
66
71
67
70
66
68
71
70
69
73
69
72
70
67
68
72
68
70
66
73
72
70
71
69
67
70
72
71
67
66
71
53
65
69
68
66
70
65
72
70
72
71
70
67
Table 4.9
The Comparison of Final Scores between Control and Experiment Group in
Statistic
Statistics
code
nilai
nilai
36
36
36
0
0
0
Mean
69,64
67,36
Std. Error of Mean
0,348
0,304
Median
70
67
Mode
70
66
Std. Deviation
2,086
1,823
Variance
4,352
3,323
Range
7
7
Minimum
66
65
Maximum
73
72
2505
2425
Valid
N
Missing
Sum
6. Testing Normality and Homogeneity
a. Testing normality
One of the requirements in experimental design was the test of normality
assumption. Because of that, the writer used SPSS 21 to measure the normality of
the data. Test Normality of Pre Test and Post Test Scores were described in Table
4.11.
54
Tests of Normality
a
Kolmogorov-Smirnov
Statistic
df
Shapiro-Wilk
Sig.
Statistic
df
Sig.
pretest
,119
72
,013
,953
72
,009
posttest
,125
72
,007
,954
72
,011
a. Lilliefors Significance Correction
Description:
If respondent > 50 used Kolmogorov-Sminornov
If respondent < 50 used Saphiro-Wilk
The criteria of the normality test Pre Test and Post Test is if the value of r
(probability value/critical value) is higher than or equal to the level of significance
alpha defined (r ≥ α = 0.05), it means that, the distribution is normal. Based on the
calculation using SPSS 21 above, the value of r (probably value/critical value)
from Pre test and Post test of the control group and experimental group in
Kolmogorov-Sminornova was higher than level of significance alpha used or r =
0.013> 0.05 (Pre Test) and r = 0.07> 0.05 (Post Test) so that the distributions are
normal. It meant that the students’ scores of in Pre Test and PostTest had a normal
distribution
b. Testing Homogeneity
The definition of Homogeneity of Variance is when all the variables in
statistical data have the same finite or limited variance. When homogeneity of
variance is equal for a statistical model, a simpler computation approach to
analyzing the data can be used due to a low level of uncertainty in the data.
Because of that, the writer used SPSS 21 to measure the homogeneity of the data.
55
Test of Homogeneity of Variance
Levene Statistic
posttest
Based on Mean
Based on Median
Based on Median and with
adjusted df
Based on trimmed mean
df1
df2
Sig.
1,068
1
70
,305
,591
1
70
,445
,591
1
67,852
,445
1,027
1
70
,314
From the table output above can be known that the value of significance
higher than 0.05 so can be concluted that the data have the same variance or
homogene
7. Data Analysis
a. Testing hypothesis
The writer applied SPSS 21 program to calculated ttest in testing hypothesis
of the study. The result of the ttest using SPSS 21 program was described in Table
bellow.
Table 4.13
Standard Deviation and Standard Error of X1 and X2 Group Statistics
Group Statistics
code
N
Mean
Std. Deviation
Std. Error Mean
x1
36
77,53
4,205
,701
x2
36
72,11
5,371
,895
score
56
Table 4.14
The Calculation ttest Using SPSS 21 Independent Samples Test
Independent Samples Test
Levene's
t-test for Equality of Means
Test for
Equality of
Variances
95%
Sig.
F
Sig.
t
df
(2taile
Confidence
Mean
Std. Error
Difference Difference
Interval of the
Difference
Equal variances
assumed
Equal variances
not assumed
score
d)
,717
,400
Lower
Upper
4,765
70
,000
5,417
1,137
3,149
7,684
4,765
66,192
,000
5,417
1,137
3,147
7,686
The table showed the result of ttest calculation using SPSS 21 program.
Since the result of Test test between experimental and control group had
difference scores of variance, it found that the result of tobserved was 4,765.
To examine the truth or false of null hypothesis stating that using
simulation technique does not increase the 10th grade students’ speaking scores,
the result of ttest was interpreted on the result of degree of freedom to get the ttable.
The result of degree of freedom (df) was 70, it found from the total number of
students in both group minus 2.
57
Table 4.15
The Result of tobserved and ttable/ttest
ttable
Variable tobserved
X1-X2
4.765
Df
5%
1%
2.000
2.660
70
The interpretation of the result of ttest using SPSS 21 Program, it was found
the tobserved was greater than the ttable at 1% and 5% the level significance or 2.000
< 4.765 > 2.660. It could be interpreted based on the result of calculation that Ha
stating that “the students taught by simulation technique gain better apeaking
performance” was accepted and Ho stating “the students taught by simulation
technique do not gain better speaking achievement” was rejected. It meant that
teaching speaking by using speaking technique increases the 10th grade students’
speaking scores at MAN Model Palangka Raya
b. Manual testing
The writer chose the level of significance in 5%, it mean that the level of
significance of the refusal null hypothesis in 5%. The writer decided the level of
significance at 5% due to the hypothesis type stated on non-directional (two-tailed
test).It meant that the hypothesis cannot directly the prediction of alternative
hypothesis. To test the hypothesis of the study, the writer used t-test statistical
calculation. First, the writer calculated the standard deviation and the standard
error of X1 and X2. It was found the standard deviation and the standard error of
PostTest of X1 and X2 at the previous data presentation. It was described in Table
4.16.
58
Table 4.16
Group Statistics
code
N
Mean
Std. Deviation
Std. Error Mean
x1
36
77,53
4,205
,701
x2
36
72,11
5,371
,895
score
TheStandard Deviation and Standard Error of X1 and X2
Description:
X1: Experimental Group
X2: Control Group
The table showed the result of the standard deviation calculation of X1 was
4.205 and the result of the standard error mean calculation was 0.701. The result
of the standard deviation calculation of X2 was 5,371 and the result of the
standard error calculation was 0.895.
The next step, the writer calculated the standard error of the differences mean
between X1 and X2 as follows:
Standard Error of the Difference Mean scores between Variable I and Variable II:
SEM1- SEM2
=
SEM1- SEM2
=
SEM1- SEM2
=
SEM1- SEM2
=
SEM1- SEM2
= 1,136849154461576 = 1,13
59
The calculation above showed the standard error of the differences mean
between X1 and X2 was 0.774. Then, it was inserted theto formula to get the value
of tobserved as follows:
to
=
to
=
to
=
to
= 4,79646017699115 = 4,796
With the criteria:
If ttest (tobserved) > ttable, Ha is accepted and Ho is rejected.
If ttest (tobserved) < ttable, Ha is rejected and Ho is accepted.
Then, the writer interpreted the result of ttest. Previously, the writer
accounted the degree of freedom (df) with the formula:
Df
= (N1 + N2) - 2
= (36 + 36) – 2 = 70
ttable at df 68 at 5% the level of significant = 2,000
The writer chose the level of significance in 5%; it means that the level of
significance of the refusal null hypothesis in 5%. The writer decided the level of
significance at 5% due to the hypothesis typed stated on non-directional (twotailed test). It meant that the hypothesis cannot direct the prediction of alternative
hypothesis.
The calculation above showed the result of ttest calculation as in the Table 4.14.
60
Table 4.17 The Result of ttest
ttable
Variable tobserved
X1-X2
4,765
Df
5%
1%
2,000
2,660
70
Description:
X1
= Experimental Group
X2
= Control Group
tobserved
= The Calculated Value
ttable
= The Distribution of t value
Df
= Degree of Freedom
Based on the result of hypothesis test calculation, it was found that the
value of tobserved was greater than the value of ttable at the level of significance in
5% or 1% that was 2.000 < 4,765 >2.660 It meant Ha was accepted and Ho was
rejected.
It could be interpreted based on the result of calculation that Ha stating
that “the students taught by simulation technique gain better speaking
achievement” was accepted and Ho stating “the students taught by speaking
technique do not gain better speaking achievement” was rejected. It meant that
teaching speaking by using simulation technique increases the 10th grade students’
speaking scores at MAN Model Palangka Raya.
61
B. Data Discussion
In this section are discussed under each objective of the study. The writer
have used the data generated by this experiment study as a backdrop in analysing
the benefits and the knowledge that may be gained from using simulation. Does a
learner’s of speaking is improve his/her speaking ability taught by simulation?
That’s thequestion hunting on the writer’s mind. If the hypothesis is true, then the
writer can say that teaching speaking using simulation is accepted, and thus the
later research can be based on this theoretical foundation.
From the data collected after treatment 6 times, the writer found that
students’ speaking scores are listed in twoseparate lines. SPSS version 21 has
been used to perform Pearson Product-moment correlation, which is conducted to
investigate the valididy and realibility of speaking test. The author of this thesis
made two opposite hypotheses (the null and alternative hypotheses), which
needed to be verified by quantitative analysis. From the analysis in 4.15
concluded that the result of the data analysis showed that the simulation technique
gave significance effect on the students’ speaking scores for the 10th graders of
MAN Model Palangka Raya. The students who were taught using simulation
technique got higher scores than students who were taught without using
simulation technique. It was proved by the mean scores of the students who were
taught using simulation technique was 77.53 and the students who were taught
without using simulation technique was 70.11.
62
This is a little bit different to the one of results from previous study by
Nurviana Hardianty: “Improving Speaking Skill Through The Use Of Simulation
Technique” shows that the use of simulation technique is effective in improving
the students’ speaking skill. It can be seen from the result of the data analysis, in
the pre-test the result was 35.4 while in the post-test the result increased to 57.1.
In this case the writer realize that why the writer’ mean score just raise 7 point, it
because there are several extraneous variable inside process collecting the data
such as: (1) the experience of the writer itself is less, (2) the material is boring (3)
non-interesting class room and noisy. But even so the ability of speaking improve
after treatment is true, support by the theory of fee and joys stated that providing
students with guided practice as they develop language skills for meaningful
communication through whole text.
.
1 Nurviana Hardianty, Improving Speaking Skill Through The Use Of Simulation
Technique, e-Journal of English Language Teaching Society (ELTS) Vol. 1 No. 2 2013 – ISSN
2331-1841. P . 9