In doing the above mentioned calculation, the researcher used statistical software named SPSS Statistical Product and Service Solution to measure the
difference score between X and Y variables. The researcher used some steps as following:
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a. Input the score of pre- test and post- test on different column on new file of SPSS program.
b. Choose analyze c. Choose compare means
d. Choose paired simple t- tests e. Input the X and Y variables into paired variable column
f. Choose option and fill confidence interval g. Choose continue
h. Choose OK By doing those steps, the result of comparing means scores of pre- test and
post- test could be easily and instantly seen.
2. Technique of Qualitative Data Analysis
In analyzing qualitative data, firstly the writer transcribed the audiotape
recorder of qualitative data into text data. Creswell states that the transcription is
the process of converting audiotape recordings or field notes into text data.
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After transcribing the data, the researcher focused on analyzing how pictures affected
respondents’ score and ignored any unimportant information from the respondents. Then, the researcher classified
the respondents’ answer into some classifications, whether the pictures were motivating, interesting, encouraging,
understandable, too complex, or ineffective teaching aid for learners when studying the comparative adjectives. Finally, the researcher interpreted the data by
developing a list of key points or important findings from the classified data.
13
11
Budi Susetyo, Statistika untuk Analisis dan Penelitian, Bandung: Refika Aditama, 2010, p. 277
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John W. Creswell, op.cit., p. 239
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Ellen Taylor-Powell and Marcus Renner, Analyzing Qualitative Data, Program Development and Evaluation of Uni versity of Wisconsin-Extension, 2003, p. 5
G. Statistical Hypotheses
Quantitatively, the hypotheses were used only for the first research question about the effect of using pictures in learning comparative adjectives to learners’
score, which needed the analyzing data statistically. Those research hypotheses
are:
H : The use of pictures does not a
ffect on learners’ score in learning comparative adjectives.
H
1
: The use of pictures a ffects on learners’ score in learning comparative
adjectives. In stastitical notation, those hypotheses are drawn as following:
H : µ
a
= µ
b
H
1
: µ
a
≠ µ
b
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CHAPTER IV RESEARCH FINDINGS AND DISCUSSION
This chapter presents the result of the research. In this case, it describes the result of the research about the effect of the use of pictures in learning comparative
adjectives to learners’ score and perception.
A. Research Findings
1. Data Description
In describing data of this research, the researcher divides this part into two parts. Firstly, there is a description about quantitative data, and secondly, there is a
description about qualitative data. This part is divided into two parts because the researcher needs to analyze both quantitative and qualitative data to answer two
research questions. The quantitative data is needed to answer first research question about the effect of the use of pictures in learning comparative adjectives
to learners’ score. Moreover, the qualitative data is needed to analyze to answer second research question about the effect of the use of pictures in learning
comparative adjectives to learners’ perceptions. Besides, those two data description, there is also elaboration about assumption test of quantitative data.
a. Quantitative Data Description
As described in previous chapter, the researcher held the research at MTs. Al- Islamiyah Ciledug Tangerang. She held the research by taking the learners
’ score of the tests pre-test and post-test and giving the learners the treatment, use
pictures in learning comparative adjectives. The pre- test was given before the treatment and the post- test was given after the treatment.
The test consisted of 30 questions valued 10 score in each question. Additionally, if a learner answered one question correctly, heshe got 10 point. In
calculating the total score of the test, the researcher divided the amount of correct
answer with 3. Hence, the highest score of this test was 100.
In describing the result of test pre- test and post- test, the researcher provides descriptive statistic and box plot chart as follow
ing for detail learners’ pre- test and post- test score see Appendix 5:
Table 4.1 Descriptive Statistic
pretest posttest
N Valid
37 37
Missing Mean
19.09 78.08
Median 20.00
86.00 Mode
20 90
Std. Deviation 6.967
18.024 Variance
48.533 324.854
Minimum 3
30 Maximum
36 100
Sum 706
2889 Percentiles
25 13.00
61.50 50
20.00 86.00
75 23.00
93.00
Figure 4.1 Box Plot Chart of Pre- Test and Post- Test Score
From the table and chart above, it showed that the average score of pre- test was 19.09 and the average of post- test was 78.08. The minimal score in pre- test
was 3; while in post- test was 30. Further, the maximal score in pre- test was 36; while in post- test was 100. The quartile scores Q1, Q2, and Q3 was 13, 20, and
23 for pre- test, and 61.5, 86, and 93 for post- test. Therefore, it also could be seen clearly an improvement between pre- test and post- test on the boxplot chart.
b. Assumption Test
Before the quantitative data on this research were statistically analyzed, the data were assumption tested to determine whether parametric or non-parametric
statistic was used. The parametric statistic had some requirements to fulfill, such as test of data normality, data homogeneity, and data linearity.
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In this part, the researcher shows the result of those tests.
1. Test of Data Normality In the test of data normality, the sample of this research was tested in order to
know whether the sample came from a normally distributed population or not. In testing the normality of data, the researcher used SPSS Statistical Product and
Service Solution to make easier and less time consuming. There were some ways in testing the data normality.
There are three ways in testing the data normality. They are Skewness value, histogram display normal curve, and P-plot normal curve. In this research, the
Skewness value was chosen in testing the data normality by following these steps: a. choose analyze
b. choose descriptive statistic c. choose descriptive
d. choose names of variable and put them on variable column e. choose option
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Budi Susetyo, Statistika untuk Analisis dan Penelitian, Bandung: Refika Aditama, 2010, p. 138
