CHAPTER IV
FINDINGS AND INTERPRETATION

This chapter deals with (a) the findings and (b) the interpretation of this study.

A.	Findings
In findings, the writer presents data description, pre-requisite analysis and hypothesis testing.

1.	Data Description
Data description deals with frequency data and descriptive statistic. In this part, the writer described and analyzed the result of pretest and posttest in the experimental and control group by using SPSS 16.

(a)	Distribution of Frequency Data
It presents the students’ score in control and experimental groups before and after giving the treatment.

(1)	Students’ Pretest Scores in Experimental Group
After analyzing the data of students’ pretest score in experimental group, the writer got the frequency and percentage. There were 1 student (3.3%) got 37, 1 student (3.3%) got 40, 1 student (3.3%) got 43, 2 students (6.7%) got 50, 2 students (6.7%) got 53, 3 students (10%) got 57, 5 students (16.7%) got 60, 2 students (6.7%) got 63, 1 student (3.3%) got 67, 4 students (13.3%) got 70, 1 student (3.3%) got 73, 2 students (6.7%) got 77, 1 student (3.3%) got 80, 2 students (6.7%) got 83, 2 students (6.7%) got 87. The distribution of frequency data in pretest of experimental group is figured out in table 7.
Table 7
Frequency Data of Students’ Pretest Score In Experimental Group

		Frequency	Percent	Valid Percent	Cumulative Percent	
Valid	37	1	3.3	3.3	3.3	
	40	1	3.3	3.3	6.7	
	43	1	3.3	3.3	10.0	
	50	2	6.7	6.7	16.7	
	53	2	6.7	6.7	23.3	
	57	3	10.0	10.0	33.3	
	60	5	16.7	16.7	50.0	
	63	2	6.7	6.7	56.7	
	67	1	3.3	3.3	60.0	
	70	4	13.3	13.3	73.3	
	73	1	3.3	3.3	76.7	
	77	2	6.7	6.7	83.3	
	80	1	3.3	3.3	86.7	
	83	2	6.7	6.7	93.3	
	87	2	6.7	6.7	100.0	
	Total	30	100.0	100.0		

(2)	Students’ Pretest Scores in Control Group
After analyzing the data of students’ pretest scores in control group, the writer got the frequency and percentage. There were 2 students (6.7%) got 37, 1 student (3.3%) got 40, 1 student (3.3%) got 43, 1 student (3.3%) got 47, 3 students (10.0%) got 53, 2 students (6.7%) got 57, 2 students (6.7%) got 60, 3 students (10.0%) got 63, 4 students (13.3%) got 67, 5 students (16.7%) got 70, 2 students (6.7%) got 73, 1 student (3.3%) got 77, 1 student (3.3%) got 80 and 2 students (6.7%) got 87. The distribution of frequency data in pretest of control group is figured out in table 8.
Table 8
Frequency Data of Students’ Pretest Scores In Control Group

		Frequency	Percent	Valid Percent	Cumulative Percent	
Valid	37	2	6.7	6.7	6.7	
	40	1	3.3	3.3	10.0	
	43	1	3.3	3.3	13.3	
	47	1	3.3	3.3	16.7	
	53	3	10.0	10.0	26.7	
	57	2	6.7	6.7	33.3	
	60	2	6.7	6.7	40.0	
	63	3	10.0	10.0	50.0	
	67	4	13.3	13.3	63.3	
	70	5	16.7	16.7	80.0	
	73	2	6.7	6.7	86.7	
	77	1	3.3	3.3	90.0	
	80	1	3.3	3.3	93.3	
	87	2	6.7	6.7	100.0	
	Total	30	100.0	100.0		

(3)	Students’ Posttest Scores in Experimental Group
After analyzing the data of students’ posttest scores in experimental group, the writer got the frequency and percentage. There were 1 students (3.3%) got 63, 2 students (6.7%) got 67, 1 student (3.3%) got 70, 4 students (13.3%) got 73, 4 students (13.3%) got 77, 4 students (13.3%) got 80, 3 students (10.0%) got 83, 3 students (10.0%) got 87, 4 students (13.3%) got 90 and 4 students (13.3%) got 93. The distribution of frequency and percentage data in posttest of experimental group is figured out in table 9.
Table 9
Frequency Data of Students’ Posttest Scores In Experimental Group

		Frequency	Percent	Valid Percent	Cumulative Percent	
Valid	63	1	3.3	3.3	3.3	
	67	2	6.7	6.7	10.0	
	70	1	3.3	3.3	13.3	
	73	4	13.3	13.3	26.7	
	77	4	13.3	13.3	40.0	
	80	4	13.3	13.3	53.3	
	83	3	10.0	10.0	63.3	
	87	3	10.0	10.0	73.3	
	90	4	13.3	13.3	86.7	
	93	4	13.3	13.3	100.0	
	Total	30	100.0	100.0		

(4)	Students’ Posttest Scores in Control Group
After analyzing the data of students’ posttest scores in control group, the writer got the frequency and percentage. There were 2 students (6.7%) got 60, 2 students (6.7%) got 63, 1 student (3.3%) got 67, 7 students (23.3%) got 70, 5 students (16.7%) got 73, 5 students (16.7%) got 77, 2 students (6.7%) got 80, 1 student (3.3%) got 83, 4 students (13.3%) got 87, 1 student (3.3%) got 90. The distribution of frequency data in posttest of control group is figured out in the following table.
Table 10
Frequency Data of Students’ Posttest Scores In Control Group

		Frequency	Percent	Valid Percent	Cumulative Percent	
Valid	60	2	6.7	6.7	6.7	
	63	2	6.7	6.7	13.3	
	67	1	3.3	3.3	16.7	
	70	7	23.3	23.3	40.0	
	73	5	16.7	16.7	56.7	
	77	5	16.7	16.7	73.3	
	80	2	6.7	6.7	80.0	
	83	1	3.3	3.3	83.3	
	87	4	13.3	13.3	96.7	
	90	1	3.3	3.3	100.0	
	Total	30	100.0	100.0		

(b)	Descriptive statistic
In this part, the writer analyzed the students’ pretest and posttest scores in control and experimental groups to get the minimum, maximum, mean and standard deviation.

(1)	Students’ Pretest Scores in Experimental Group
Based on descriptive statistic analysis of students’ pretest score in experimental group, it was found that the total sample wass 30 with the minimum score was 37.00, maximum score was 87.00, mean score was 63.9000 and the standard deviation was 13.41217. The result of descriptive statistic analysis is described in table 11.
Table 11
Descriptive Statistics of Pretest Scores in Experimental Group
	N	Minimum	Maximum	Mean	Std. Deviation	
pretest_experiment	30	37.00	87.00	63.9000	13.41217	
Valid N (listwise)	30					

(2)	Students’ Pretest Scores in Control Group
Based on descriptive statistic analysis of students’ pretest score in control group, it was found that the total sample was 30 with the minimum score was 37.00, maximum score was 87.00, mean score was 62.7000 and the standard deviation was 13.22263. The result of descriptive statistic analysis is described in following table.

Table 12
Descriptive Statistics of Pretest Scores in Control Group

	N	Minimum	Maximum	Mean	Std. Deviation	
pretest_cntrl	30	37.00	87.00	62.7000	13.22263	
Valid N (listwise)	30					

(3)	Students’ Posttest Scores in Experimental Group
Based on descriptive statistic analysis of students’ posttest score in experimental group, it was found that the total sample was 30 with the minimum score was 63.00, maximum score was 93.00, mean score was 80.9667 and the standard deviation was 8.67212. The result of descriptive statistic analysis is described in table 13.
Table 13
Descriptive Statistics of Posttest Scores in Experimental Group

	N	Minimum	Maximum	Mean	Std. Deviation	
Posttest_Experiment	30	63.00	93.00	80.9667	8.67212	
Valid N (listwise)	30					

(4)	Students’ Posttest Scores in Control Group
Based on descriptive statistic analysis of students’ posttest score in control group, it was found that the total sample was 30 with the minimum score was 60.00, maximum score was 90.00, mean score was 74.4667 and the standard deviation was 8.14410. The result of descriptive statistic analysis is described in table 14.
Table 14
Descriptive Statistics of Posttest Scores in Control Group

	N	Minimum	Maximum	Mean	Std. Deviation	
Posttest_Control	30	60.00	90.00	74.4667	8.14410	
Valid N (listwise)	30					

(c)	Students’ Pretest and Posttest Scores Analysis 
In this part, the writer analyzed the students’ pretest and posttest scores to compare the scores in control and experimental groups and the scores’ improvement of both groups in pretest and posttest.
The data of pretest scores showed that control and experimental groups have the same minimum and maximum score. The minimum score was 37 and the maximum score was 87. There were two students (6.7%) in control groups that got score 37 whereas only one student (3.3%) in experimental group. Therefore, there were two students (6.7%) in each groups that got score 87. From 30 students, the percentage of students in control group who got the score upper 60 was 60% while the percentage of students in experimental group who got the score below 60 was 50%. It means that the percentage of students’ scores in experimental group were higher than in control group. It was also found that the students’ mean score in control group was 62.70 and experimental group was 63.90. It could be interpreted that the students’ mean score of experimental group is higher than control group.
After analyzing the posttest scores, the writer analyzed the data of posttest scores. The data of posttest scores showed that the minimum score in control group was 60 and the maximum score was 90 while the minimum score in experimental group was 63 and the maximum score was 93. There were two students (6.7%) in control groups that got minimum score and only one student (3.3%) that got maximum score. Therefore, there was only one student (3.3%) in experimental groups that got minimum score and two students (6.7%) got maximum score. From 30 students, the percentage of students in control group who got the score upper 80 was 19.9% whereas the percentage of students in experimental group who got the score upper 80 was 46.8%. It means that the percentage of students’ scores in experimental group were higher than in control group. The analyzing of students’ posttest scores also showed the students’ mean score of in control group was 74.47 and experimental group was 80.97. It could be interpreted that the students’ mean score of experimental group is higher than control group.
The result of students’ pretest and posttest above shows that control group had improvement since the students’ mean score in posttest is higher than in pretest with 19.2%. Furthermore, the result of students’ pretest and posttest in experimental group also had improvement since the students’ mean score in posttest is higher than in pretest with 26.6%. It could be interpreted that the students in experimental group improve more than students control group.

2.	Prerequisite Analysis
In this part, the writer analyzed the normality and homogeneity of students’ pretest and posttest scores in control and experimental groups.
(a)	Normality Test
Normality test was used to find out whether the distribution of pretest and posttest scores was normal or not. One Sample Kolmogorov-Smirnov formula in SPSS 16.0 was applied to analyze the normality distribution. The data was obtained from the students’ pretest and posttest scores in control and experimental group. According to Basrowi (2007: 85), the scores are considering normal if the significance of normality test (p-output) is higher than 0.025.

(1)	Students’ Pretest Scores in Control and Experimental Group
The result showed that the significance value of the students’ pretest in control group was 0.714, while the experimental group was 0.827. Since the significance values of control and experimental group were higher than 0.025, the distribution of scores in control and experimental pretest were simply assumed normal. The output table of normality test is presented as follows:
Table 15
The Result of Normality Test of Students’ Pretest in Control and Experimental Group
	N	Kolmogorov-Smirnov	Sig.	Result	
Pretest_Control	30	0.698	0.714	Normal	
Pretest_ Experimental	30	0.627	0.827	Normal	

(2)	Students’ Posttest Scores in Control and Experimental Group
The result showed that the significance value of the students’ posttest in control group was 0.616, while the experimental group was 0.751. Since the significance values of control and experimental group were higher than 0.025, the distribution of scores in control and experimental pretest were simply assumed normal. The output table of normality test is presented as follow:
Table 16
The Result of Normality Test of Students’ Posttest in Control and Experimental Group

	N	Kolmogorov-Smirnov	Sig.	Result	
Posttest_Control	30	0.757	0.616	Normal	
Posttest_ Experimental	30	0.676	0.751	Normal	

(b)	Homogeneity Test
To compute homogeneity test, Levene statistics in SPSS 16 was applied. The result of computation would indicate whether the pretest and posttest variance of the experimental and control groups was homogenous. The test is considered homogenous whenever the significance value (p-output) is higher than 0.05 (Basrowi, 2007: 106)
.
(1)	Students’ Pretest Scores in Control and Experimental Group
Based on the homogeneity test of the students’ pretest in control and experimental groups, it was found that the p-output was 0.728. From the result, it could be stated that the obtained score from students’ pretest in control and experimental groups were homogenous, because it is higher than 0.05. The result shows in the following table.

Table 17
The Result of Homogeneity Test of Students’ Pretest in Control and Experimental Group

	N	Levene Statistic	Sig.	Result	
Pretest_Control	30	0.069	0.728	Homogenous	
Pretest_ Experimental	30				

(2)	Students’ Posttest Scores in Control and Experimental Group
Based on the homogeneity test of the students’ posttest in control and experimental groups, it was found that the p-output was 0.561. From the result, it could be stated that the obtained score from students’ pretest in control and experimental groups were homogenous, because it is higher than 0.05. The result shows in the following table.
Table 18
The Result of Homogeneity Test of Students’ Posttest in Control and Experimental Group

	N	Levene Statistic	Sig.	Result	
Pretest_Control	30	0.341	0.561	Homogenous	
Pretest_ Experimental	30				

3.	Hypothesis Testing
In this study, independent t-test was conducted to find out whether there was a significant difference on students’ listening comprehension achievement between the experimental and control class scores on posttest at SD Negeri 195 Palembang. 
There are two hypotheses in this study, null hypothesis (Hₒ) in which there is no statistically significant difference between the pretest and posttest means of the experimental and control groups, and alternative hypothesis (Hₐ) in which there is statistically significant difference between the pretest and posttest means of the experimental and control groups. 
If the t-obtained was lower than t-critical value at the 0.05 significance level and the p-output higher than 0.05, the null hypothesis (Hₒ) is accepted and the alternative hypothesis (Hₐ) is rejected. But, if the t-obtained was higher than t-critical value at the 0.05 significance level and the p-output less than 0.05, the null hypothesis (Hₒ) is rejected and the alternative hypothesis (Hₐ) is accepted (Fraenkel, et al, 2012: 228-233). 
The result of computation of normality and homogeneity indicated that the data on pretest of experimental and control group were normal and homogenous. Therefore, the independent t-test could be used to find out whether there is a significant difference between the experimental and control group scores on pretest. The following table shows the output of the independent t-test on students pretest :
Table 19
Analysis Result of Significant Difference on Students’ Listening Comprehension Achievement before being taught by Listening Grid

Independent Sample t-Test	Ho	
T	Df	Sig. (2-tailed)		
0.349	58	0.728	Accepted	

The result shows that there was no significant difference between the experimental and control group scores on pretest because the value of t-obtained was lower than t-critical value and the p-output higher than 0.05. Therefore, the null hypothesis was accepted which there was no significant difference between students’ who are taught by using listening grid and students who are not. 
The result of computation of normality and homogeneity also indicated that the data on posttest of experimental and control group were normal and homogenous. Therefore, the independent t-test could be used to find out whether there was a significant difference between the experimental and control group scores on posttest. The following table shows the output of the independent t-test on students posttest :
Table 20
Analysis Result of Significant Difference on Students’ Listening Comprehension Achievement after being taught by Listening Grid

Independent Sample t-Test	Ha	
T	Df	Sig. (2-tailed)		
2.993	58	0.004	accepted	

The calculation of independent t-test on posttest shows that the t-obtained was 2.993, the t-critical value at the 0.05 significance level and df 58 was 2.0017 and the p-output was 0.004. Since the value of t-obtained was higher than t-critical value and the p-output lower than 0.05, the null hypothesis was rejected and the alternative hypothesis was accepted. It means that there was a significant difference between students’ who are taught by using listening grid and students who are not. 
B.	Interpretations
The result analysis of measuring significant difference from students’ posttest score in experimental and control group showed that the value of t-obtained was 2.993 and the p-output was 0.004. It could be interpreted that there was significant difference from students’ posttest score taught using listening grid than the group of students were not taught by using listening grid since the value of t-obtained was higher than t-critical value and the p-output was lower than 0.05. Therefore, the null hypothesis (Hₒ) was rejected and alternative hypothesis (Hₐ) was accepted. It indicates that listening grid has significant difference in teaching listening comprehension to the fifth grade students of SD Negeri 195 Palembang. It is in line with Halliwel (2000: 47) that suggests that listening grid can help young learners to understand what they listen by using pictures. In addition, in learning listening comprehension by using listening grid makes the students understand the meaning from the context, visuals, and gestures as in real life even though they may not understand every word. The students will enjoy having to search all over the grid for what the teacher has just said. It is possible for all students in a class to work with the same grid with pictures quite happily. So, Listening Grid will help students to improve their listening comprehension achievement Halliwel (2000: 41).
Since the writer did the teaching process in control group, the writer can compare the progress of each group. Both groups got different treatment in teaching listening. The listening grid which was used for the experimental group is one of teaching listening activity which can be used to help the students to be success in listening. In using listening grid the students will get more vocabularies in English from the pictures in the grid. So, when they are ready to listen they have already known amount of vocabularies. It is related to the Cameron (2005: 109) that states noticing activity like listening grid can support meaning as well as form of the words. Listening grid is also suggested by Irfan Bulut (2011: 74) as kind of listen and notice activity. In addition, Halliwel (2000: 47) also states that listening grid can be used to provide a whole lesson of different activities around the same topic, so the lesson will not be boring for the students since there will be so many activities done with listening grid. Whereas, the strategy which was given to the control group was the strategy that is commonly used by their teacher. The teacher usually uses grammar-translation strategy, so the writer applied those strategies to control group. Because the teacher explains the material without any media, like picture card, the teaching and learning process run boring and a bit noise. The students did not really participate in teaching and learning process and when a student come to the front class to say some vocabularies after memorize them, their friends were also busy to memorize those vocabularies in the seat where it can affect the listening comprehension achievement in control group.