(ug) chapter iv
TRANSCRIPT
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CHAPTER IV
RESEARCH FINDINGS AND DISCUSSION
A. Research Findings and Description
To meet the objective of this research, the researcher analysed the data
collected using descriptive statistic and parametric (inferential) statistic analysis
technique. In order to calculate the data, the researcher used SPSS version 21.0 for
Windows. The results of analysis are described as follows:
1. Participants’ Initial Competence in Reading Comprehension
Based on the analysis results of the pre-test scores of both control and
experimental groups from the participants’ worksheet on reading
comprehension, the mean, minimum, and maximum scores of control and
experimental groups found are described on Table 4.1 and the complete output
of the descriptive statistic technique used is put in Appendix.
Table 4.1
Statistic Description of Pre-Test Score in Control and
Experimental Groups
Pre-Test
Group Mean Minimum Maximum
Control 73.09 60.00 90.00
Experimental 74.24 60.00 87.00
X 73.66 60.00 88.50
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As shown in Table 4.1, the mean of the control group is 73.09
points; while that of the experimental group is 74.24. It indicates that the
respondents’ competence of the experimental group in reading
comprehension is higher than that of the control group. Table 4.1 also
indicates that the minimum and maximum scores of the control group are
60.00 and 90.00 respectively; while those of the experimental group are
60.00 and 87.00 respectively. It shows that both groups have the same
minimum score but the maximum score of control group are higher than
that of the experimental group. The average of the mean, minimum and
maximum scores between the control and the experimental groups are
respectively calculated as: 73.66; 60.00; and 88.50 points. The participants’
initial competences in reading comprehension are figured in Figure 4.1.
Figure 4.1
Pre-Test Score Histogram of Control and Experimental Groups
Scores
Control Group Experimental Group
Scores
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2. Participants’ Achievement in Reading Comprehension
Based on the results of data analysis on the post-test and pre-test scores
of the control and experimental groups, the researcher found some differences
showing achievements. The achievements were resulted from the gains that are
the post-test and pre-test differences of the two groups. The followings are the
descriptions of the participants’ gains.
a. The Participants’ Achievement in Reading Comprehension of Control
Group
Based on the data analysis results, the gains of the control group are
as described in the following table:
Table 4.2
Statistic Description of Post-Test and Pre-Test Scores in
Control Group
Group Test Mean Minimum Maximum
Control Post-Test 76.48 63.00 90.00
Pre-Test 73.09 60.00 90.00
Differences
(Gains)
3.39 3.00 0
From the table above, it is known that there was an increase of
scores in post-test compared to those in the pre-test, except the maximum
score. It could be evidenced through the scores gained of the post-test and
pre-test. In the pre-test, the mean score is 73.09 points, the minimum score
is 60.00 points, and the maximum score is 90.00 points. However, after
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teaching, the post-test increased to 76.48 points for mean score, 63.00
points for minimum score, and no increase for maximum score. It was
reasonable because the data of pre-test scores were the initial scores that
reflected their initial average competences and the conventional technique
factually worked.
Compared, the increase differences of the mean, minimum,
maximum scores of post-test and pre-test are respectively: 3.39 points
(76.48 – 73.09) or %; 3.00 points (63.00 – 60.00) or %; and 0 points (90.00
– 90.00) or 0%. In general, it can be said that there was an increase of
reading comprehension score in the control group. The results of the post-
test and pre-test of control group are displayed in Figure 4.2 below:
Figure 4.2
Post-Test and Pre-Test Score Histogram of Control Group
Scores
Post-Test Pre-Test
Scores
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b. The Participants’ Achievement in Reading Comprehension of
Experimental Group
Based on the research results of the gain scores, the researcher
found that the gain of the experimental group, in general, increased. The
data of the experimental group gains are displayed in the following table.
Table 4.3
Statistic Description of Post-Test and Pre-Test Scores in
Experimental Group
Group Test Mean Minimum Maximum
Experimental Post-Test 80.76 70.00 93.00
Pre-Test 74.24 60.00 87.00
Differences
(Gains)
6.52 10.00 6.00
Based on the table above, it is known that in experimental group,
there were increases of scores in post-test compared to those in the pre-test.
The output of the descriptive statistic technique shows that the mean,
minimum, and maximum scores of the post-test are respectively 80.76;
70.00; and 93.00 points. While those of the pre-test, Table 4.3 exposes that
the mean, minimum, and maximum scores of pre-test are respectively
74.24; 60.00; and 87.00 points.
The differences between the post-test and pre-test scores indicated
that as a whole, there was an increase in the post test in the experimental
group. The differences are respectively as follows: mean = 6.52 points
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(80.76 – 74.24) or %; minimum score = 10.00 points (70.00 – 60.00) or %;
and the maximum score = 6.00 points (93.00 – 87.00) or %. The following
figure displays the post-test and pre-test scores in the experimental group.
Figure 4.3
Post-Test and Pre-Test Score Histogram of Experimental Group
Compared to the increase differences of control group, the scores
of experimental group were highly greater. It can be proved by the
calculation as follows: mean = 3.13 points (6.52 – 3.39); minimum = 7.00
points (10.00 – 3.00); and maximum = 6.00 points (6.00 – 0.00). The
achievement differences between the control and experimental groups are
presented in Figure 4.4.
Post-Test
Scores
Pre-Test
Scores
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Figure 4.4
The Gains in Control and Experimental Groups
3. Test Analyzes
Test analyzes were conducted before hypotheses test did. Any
hypotheses must be tested in order to decide whether the hypotheses of
research proposed, especially the expected result of research, is accepted or
rejected. The requirement of hypotheses test is the data must be distributed
normally and both variables have the same variance (homogeneous).
Normality and homogeneity tests are necessarily carried out in order to make
a decision to use appropriate analysis technique, parametric (inferential) or
non-parametric one.
a. Normality Test
The normality test was conducted to determine whether the
obtained data was distributed normally or not. The hypotheses of normality
test are formulated as follows:
0
2
4
6
8
10
12
Mean Minimum Maximum Control
Experimental
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H0: The sample data are taken from normally-distributed
population;
Ha: The sample data are not taken form normally-distributed
population.
Test of normality in this research using Kolmogorov Smirnov test
which significance level at (α) of 0.05. A criterion for normal distribution
(H0 is accepted) is if the significant score (Sig.) is higher than the
significance level (α) of 0.05.
Significance score (Sig.) > Significance level (α) 0.05
The finding of the normality test is shown in the table below:
Table 4.4
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
Control .136 33 .130 .967 33 .399
Experimental .131 34 .148 .947 34 .098
Table 4.4 indicates that the Sig. value (0.130) > Sig. α (0.05) for
control group. It implies that H0 was accepted and Ha was rejected. In other
words, that the data from the control group derived from population which
distributed normally. For experimental group, the Sig. value (0.148) > Sig.
α (0.05). It also implies that H0 was accepted and Ha was rejected. It means
the sample data were normally distributed in the experimental group.
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As we know that if the data are normally distributed, the data points
in Q-Q plot will be close to the diagonal line. According to figure below,
the points of control and experimental groups were close to the diagonal
line. It means that the data from both of groups are taken from normally-
distributed population.
Figure 4.5
Q-Q Plots of Scores of Control and Experimental Groups
b. Homogeneity Test
The homogeneity test was conducted to determine whether the two
samples have the same variance (homogeneous) or not. The hypotheses of
data homogeneity are formulated as follows:
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H0: Sample data are taken from homogeneous population variances;
Ha: Sample data are taken from non-homogeneous population
variances.
Test of homogeneity using the variance equality test with both
samples criteria has the same/homogeneous variance (H0 is accepted), if
the significant score of Based on Mean is higher than the significant level
(α) of 0.05.
Significant score (Sig.) of Based on Mean > Significant level (α) 0.05
The finding of homogeneity test of pre-test and post-test in the
control class is shown in Table 4.5 below:
Table 4.5
Test of Homogeneity of Variances
Levene
Statistic
df1 df2 Sig.
Scores Based on Mean .493 3 18 .692
Based on Median .585 3 18 .632
Based on Median and
with adjusted df
.585 3 14.674 .634
Based on trimmed
mean
.556 3 18 .651
Based on the table above, it is known that the significant score of
Based on Mean is 0.692. The Sig. value (0.692) is higher than the Sig. α
(0.05); it means two samples have the same variance (homogeneous).
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4. Hypotheses Test
After the test for analysis requirements through the data normality and
homogeneity has met the criteria of each hypotheses, the research hypotheses
were tested using parametric or inferential technique. In order to test the
hypotheses of this research, the researcher used Independent Sample t-test to
see the compare means. The hypotheses of this research were formulated as
follows:
H0 = There is insignificant effect of using TGT to the eleventh graders’
reading comprehension.
Ha = There is significant effect of using TGT to the eleventh graders’
reading comprehension.
The criteria of decision of the hypotheses test should obey the following:
- If Sig (2-tailed) value < Sig. α; H0 is rejected or Ha is accepted;
- If Sig. (2-tailed) value > Sig. α, H0 is accepted or Ha is rejected;
Where Sig. α = 0.05.
The results of the t-test are as displayed on Table 4.6 below:
Since Table 4.6 shows that if the Sig. value (2-tailed) is less than the
standard significant, the hypothesis null (H0) is rejected and alternative
hypothesis (Ha) is accepted. It means the average in both of groups are
different. Based on the criteria of the research hypotheses, the Sig. (2-tailed)
0.000 < Sig. α 0.05, H0 is rejected or Ha iss accepted. Therefore, it can be
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concluded that TGT technique significantly affected the eleventh graders’
reading comprehension at SMAN 55 Jakarta.
B. Discussion