0.273. It means that every item which has coefficient- correlation ≥
0.273 is significant or valid. Yet, every item that has coefficient- correlation ≤ 0.273 is not significant or not valid. After the writer
analysed the calculation of the test, there were 33 items valid to be used as the pre-test of the research. In order to make easier to
calculate the data, the writer used 20 of valid items as pre-test of this research.
For the post-test items, the writer used 13 valid items left because they has been analysed by ANATES software and they are
significant of valid. However, to make easier to calculate the data, the writer still need 7 others valid items. Thus, the writer reused
seven items of pre-test. So, the final item used in post-test of the research consisted of 20 number of questions.
F. Technique of Data Collection
Collecting data is an important thing, in this research the technique of data collection which is used by the writer.
1. Pre-test The pre-test was given in the beginning of attending class pre-test
was given before doing the experiment in order to know stud ents’
knowledge and achievement of the concrete nouns material. The instrument consist of 20 multiple choice items test and each items
was scored 5 point so total score of this test was 100. 2. Post-test
The post-test was given in the end of the treatment, in order to know the students’ ability and students’ achievement in mastering
the material about concrete nouns. The instrument consist of 20 multiple choice items test and each items was scored 5 point so the
total score of this test was 100.
G. Technique of Data Analysis
The data analysis technique is an activity to process and analyse the data that have been gathered. While, in analysing the data, the writer
used t-test. However, before the t-test was employed, the writer tested the data whether they were distributed normally and homogeneous.
1. The Data Normality Test The test of data normality is used to know whether the data that
have been gathered from the sample came from the normal distributed population. To test the data normality, the writer used the SPSS
version 22.0 for window. Shapiro-Wilk formula with the steps as follow:
a Formulate the hypothesis for the normality test of the data as follow:
H : The data is normally distributed.
H
1
: The data is not normally distributed. b Test the normality of the data is analysed using SPSS.
c The criteria of the decision making is: If the degree of significance is
≤ 0.05, H is accepted
If the degree of significance is 0.05, H is rejected
And the steps to do normality test of the data as below: a From the menu at the top of the screen click on Analyze
then Descriptive then Explore. b Move all of the data into the Dependent list.
c Under display ensure that there is only a ticks next to Plots.
d Click on the Plots tab to open the plots dialogue box. e Under Boxplot click None, then remove any ticks under
Descriptive Place. Place a tick on normality plot with test. f Click Continue, the OK
2. Homogeneity Test of the Data The homogeneity test of the data is used to test whether the data
come from the homogeneous or heterogeneous population. This test was conducted after normality test of the data.
To analyse the homogeneity of the data, the criteria of the test are as follow:
α = 0.05 is accepted if
F
is rejected if
The formula used can be seen as follows:
F = or F=
The writer used SPSS version 22.0 for Windows to calculate homogeneity test. The steps to do homogeneity test as below:
a From the menu at the top of the screen click on Analyze the Compare Means then One-Way ANOVA.
b Move the data from experimental class into Dependent list and the data from controlled class into Factor.
c Under Contrast and Post-Hoc ensure that there is a tick to Options.
d Click on the Options tab to open the options dialogue box.
