their research especially in a school. This type was also chosen because narrative text questions are usually formed in multiple choices. Both experimental class and
controlled class were given the pretest and the posttest. The pretest was given to see the students’ capability in their reading skill before using DR-TA strategy.
The posttest was given to measure which class had better scores.
F. Data Analysis Technique
After the data of the pretest and the posttest scores were collected, the data then were analyzed by using statistic calculation of t-test formula in manual
calculation and software calculation using SPSS Statistic Product and Statistic Solution version 22. The t-test was used to test the hypothesis. Before calculating
t-test, normality and homogeneity tests were done first.
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1. Normality test
Normality test is performed to show whether the data from the sample is normal or not, the data are both pretest and posttest result taken from experimental
and controlled class. If the normality of the data is more than the level of significance
α 0.05, scores are normally distributed. The normality test is performed by using Kolmogrov-Smirnov and Shapiro-Wilk gained as follows:
Analyze → Descriptive Statistics → Explore. Insert PretestPosttest in Dependent List and Class in Factor List. Click Plots and Checklist Normality plots with tests
→ Continue → OK. This is the example of the data using SPSS:
Tests of Normality
Class Kolmogorov-Smirnov
a
Shapiro-Wilk Statistic
df Sig.
Statistic Df
Sig. Pretest
Experimental .110
38 .200
.969 38
.363 Controlled
.133 38
.089 .975
38 .537
. This is a lower bound of the true significance. a. Lilliefors Significance Correction
6
Budi Susetyo, Statistika untuk Analisis Data Penelitian, Bandung: PT. Refika Aditama, 2010, pp. 137
– 138.
2. Homogeneity test
Homogeneity test is performed to test whether the data from the two groups, experimental and controlled class, have the same variant in order that the
hypothesis can be tested by t-test or not. Homogeneity test is calculated by using Levine and gained as follows: Analyze
→ Compare means → One Way Anova → Put PretestPosttest in Dependent list and
Class in Factor List → Click option and Checklist Homogeneity of variance test
→ Continue → OK. Here is the example of homogeneity test result of the data:
Test of Homogeneity of Variances
Pretest Levene Statistic
df1 df2
Sig. .140
1 38
.711
3. Hypothesis test
After getting the data from pre-test and post-test taken from experimental and controlled class, it needs to find out the differences score
in the students’ reading comprehension by using Directed Reading
– Thinking Activity. Here, the two classes are compared to the independent variable, the experimental class is X
variable and the controlled class is Y variable. Statistical calculation of the t-test with significant degree 5 0.05 and 1 0.01 is used. The formula of t-test
is expressed as follows:
7
�
�
= −
�
� −�
In which: M
x
= Mean of variable X M
y
= Mean of variable Y SE = Standard error
7
Anas Sudijono, Pengantar Statistik Pendidikan, Jakarta: PT. Raja Grafindo Persada, 2008, p. 324.
Prior the calculation of the t-test; there are several steps as follows: 1. Determining Mean of Variable X with formula:
= ∑
2. Determining Mean of Variable Y with formula: =
∑
3. Determining Standard of Deviation Score of Variable X with formula: �
= √ ∑
2
4. Determining Standard of Deviation Score of Variable Y with formula: �
= √ ∑ ²
5. Determining Standard Error of Mean of Variable X with formula: � � =
� √ −
6. Determining Standard Error of Mean of Variable Y with formula: � � =
� √
−
7. Determining Standard Error of Difference of Mean of Variable X and Y with formula:
�
� −�
= √� � ² + � � ²
