CHAPTER III RESEARCH METHODOLOGY
E. Technique of Data Collection
The procedure of data collecting used the following steps:
1. Pretest
A pre-test was administered at the first meeting. The pre-test was given to the students before doing the treatment. The researcher asked the student to read text based on the curriculum and syllabus. Besides, the researcher used media to get the students' scores. The researcher given a pre-test to students‟; it was supposed to know their basic knowledge about reading in descriptive text. Test descriptive text that focused on main idea and supporting detail. Multiple choices were the type of test that was used; multiple choice tests consisted of 20 items;
each question consisted of four answer choices (a, b, c, d). 2. Treatment
The treatment was conducted for four meetings. Each meeting lasted for 2 x 45 minutes. For the first meeting, the researcher explained to the students about the general description about Decoding Skills and explains about descriptive text. Next, the researcher gave activities to practice decoding skills in reading and using decoding skills for students‟ automaticity in reading comprehension. The next meeting, the researcher used the same activity as in the second meeting, but with a different topic. And at the last meeting, the researcher given students an opportunity to express their point of view about Decoding Skills.
3. Post-test
After giving the treatment, the researcher used a post-test. The questions were given consisted of twenty numbers of multiple choices.
The same as the pretest, post-test was given to see the effectiveness of using decoding skills for students‟ automaticity in reading comprehension. Post-test was used to measure how deep students' understanding of the text is. The post-test was conducted to find out the student's achievement and their progress.
G. Technique of Data Analysis
The data were analyzed quantitatively. Data analysis technique used data from the test. The researcher used the test twice that is pre-test (before treatment) and post-test (after treatment). The data was compared from the mean of the scores from pre-test and post-test. The results of the test were scored using an analytic scale which converts into 10-100. The data from the test were analyzed using SPSS 21.
a. Normality Test
The research normality test was aimed at finding out whether or not the data from the examined experimental and controller group comes from the normal distribution population. For both sample groups, therefore, the normality test was performed.
b. Homogeneity Test
After the consequence of the normality test stated that the result was normally distributed, a homogeneity test was carried out by the researcher. The aim of the homogeneity test is to assess the resemblance between the two groups. Similar to the normality test, the researcher also uses SPSS implementation to evaluate the homogeneity test.
c. Hypothesis Test
After the two trials (Normality and Homogeneity test) have been carried out, the researcher must proceed to analyze the information through a T-test. The purpose of the t-test was to examine the distinctions between the two study groups. The researcher could determine if the hypothesis is adopted or dismissed by using a t-test.
d. Cohen Effect Size
The last step to produce the test outcome is to assess the effect-size by the writer. This test was performed to understand the impact level of meaning. In this research, the investigator used Cohens‟s d effect size formula. Furthermore, the formula for measuring the effect size could be seen as follows:
Louis Cohen et.al (2007)
Explanation:
D: Effect Size
Mean of Group A: Mean for experimental class Mean of Group B: Mean for controlled class
(Pooled standard deviation: Standard deviation of Group A Standard deviation of Group B
The effect size formulation has been calculated and the result could be used to determine the level of significance. Below were the effect size criteria by Cohens‟:
0-0.20 : Weak effect 0.21- 0.50 : Modest effect 0.51 – 1.00 : Moderate effect
> 1.00 : Strong effect
CHAPTER IV
FINDINGS AND DISCUSSSION A. Findings
1. Data Description
The purpose of this research was to find out a significant effect of using decoding skills for students‟ automaticity in reading comprehension through descriptive in terms of literal comprehension. After providing the data in the experimental and control class about the descriptive text by the students. Research data were drawn from the SMA Negeri 10 Maros by pre-test and post-test scores of tenth- grade students. The description below shows the research outcomes based on pre-test and post-test scores provided to research participants.
a. The Data of Experimental Class
The X MIA 2 was taken as an experimental class by this research.
The class is made up of 26 students. Decoding Skills was used to teach the experimental class. The researcher used pre-test and post-test to retrieve the data. Furthermore, pre-test was performed before the implementation of Decoding Skills. While after the writer implanted Decoding Skills in teaching reading understanding of descriptive text, the post-test was performed. The score for the pre-test and post-test were as follows:
Table 4.1 Score of Pre-test and Post-test of Experimental Class
Students Pre-Test Post-Test Gained Score
1 55 80 25
2 45 75 30
3 70 90 20
4 65 80 15
5 60 85 25
6 45 75 30
7 65 80 15
8 55 75 20
9 45 65 20
10 55 70 15
11 45 80 35
12 75 85 10
13 65 70 5
14 70 85 15
15 55 70 15
16 80 85 5
17 55 85 30
18 65 80 15
19 35 75 40
20 50 70 20
21 60 90 30
22 70 90 20
23 50 90 40
24 60 80 20
25 40 70 30
26 60 80 20
SUM 1495 2060 565
Mean
Score 57.5 79 21,7
Maximum
Score 80 90 40
Minimum
Score 35 65 5
Source: SPSS Versions 21
Based on the description above, it showed that the mean of pre-test was 57,5 and the mean of post-test was 79. Therefore the average of gain score is 21,7. The lowest score of pre-test was 35; the highest score of pre- test was 80. After getting treatment or using Decoding skills, the lowest score of post-test 65, and the highest score of post-test was 95 and the average of post-test were 79.
From the description above, it can be concluded that the students in the experimental class got the improvement of using decoding skills for student‟s automaticity in reading comprehension of descriptive text.
Therefore, the score of the students in post-test is better than in the pre- test. It proves that most of the students can increase their reading comprehension after they are taught by using decoding skill in class.
b. The Data of Controlled Class
The control class was students of X MIA 1. The class was made up 26 students. The control class was not using Decoding Skills. Similar to the experimental class, pre-test and post-test score data of the control class were acquired.
Table 4.2 Score of pre-test and post-test of Controlled Class
Students Pre-Test Post-Test Gained Score
1 60 70 10
2 40 50 10
3 60 65 5
4 80 85 5
5 75 75 0
6 65 75 10
7 65 70 5
8 65 65 0
9 75 80 5
10 60 65 5
11 35 50 15
12 65 60 5
13 60 50 -10
14 45 40 -5
15 70 60 -10
16 50 65 5
17 45 60 15
18 75 65 -10
19 80 80 0
20 55 65 10
21 45 60 15
22 65 75 10
23 50 55 5
24 55 70 15
25 65 75 10
26 70 65 -5
SUM 1575 1693 120
Mean
Score 61 65 4,61
Maximum
Score 80 85 15
Minimum
Score 35 40 0
Source: SPSS Versions 21
Based on the description above of data in control class above, it showed that the mean of pre-test was 61 and the mean of post-test was 65.
Therefore the average of gain score was 4,61. The lowest score of pre-test was 35, the highest score of pre-test was 80. Furthermore, the lowest score of post-test was 40, the highest post-test was 85.
Figure 4.1 The Difference between Students’ Score of Experimental Class and Control Class
Based on the data in Figure 4.1, students in the experimental class achieved greater ratings in understanding descriptive text. It happened after the experimental class was taught using Decoding Skills and control class students were instructed using conventional learning methods. In conclusion, Decoding Skills was effective in reading the understanding of descriptive text for students.
0 10 20 30 40 50 60 70 80 90
Pre-test Post-test
Experimental Class Control Class
2. Analysis of the Data a. Normality Test
The test of normality intends to evaluate whether or not the data was normally distributed. The researcher was testing Kolmogorov – Smirnov and Shapiro-Wilk to evaluate the data‟s normality. The amount of meaning in the studies is 0,05. The results of the analysis will be shown as below:
Table 4.3 Normality Test of Pre-Test and Post-Test of Experimental Class and Controlled Class
Significance (Sig.) in both classes‟ Kolmogorov-Smirnov columns, as shown in Table 4.3, is 0,05. The experimental class was 0,200 and the regulated class was 0,199. According to the consequence, it can be concluded that pre-test experimental class and control class data were normally distributed.
Tests of Normality
Kelas Kolmogorov-Smirnova Shapiro-Wilk
Statistic Df Sig. Statistic Df Sig.
Hasil Belajar Siswa
Pre-Test
Eksperimen .104 26 .200* .978 26 .838
Post-Test
Ekperimen .157 26 .097 .929 26 .075
Pre-Test
Control .141 26 .199 .959 26 .379
Post-Test
Control .149 26 .140 .960 26 .383
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
It can be seen in the Kolmogorov-Smirnov rows of the two classes from Table 4,3, Significance (Sign.) is 0.05. The experimental class was 0,097 and controlled class was 0,140. The writer found on the basis of the consequence that the importance of the data in the experimental class and the controlled class is above 0,05. This implies that study information is normally distributed and using Decoding Skills was effective for increase reading comprehension in learning descriptive text understanding.
b. Homogeneity Test
The aim of the homogeneity test is to determine whether or not the information from the class of experimental and controller is homogeneous (equivalent). The research used Levene Statistics in this study to scale the experimental class and controller class homogeneity test. The test outcome can be seen as below:
Table 4.4 Homogeneity Test of Pre-test and Post-tes of Experimental Class
Test of Homogeneity of Variance
Levene
Statistic df1 df2 Sig.
Pre Test .171 1 50 .681
Post Test 1,477 1 50 .230
Levene
Statistic df1 df2 Sig.
Hasil Belajar Siswa
Based on
Mean 1,477 1 50 .230
Based on
Median 1,638 1 50 .206
Based on Median and with adjusted df
1,638 1 42,741 .207
Based on trimmed mean
1,659 1 50 .204
As mentioned in the Table 4.4, the results of the data showed that the significance of the experimental and controller class pre-test is 0,681.
It implies 0,681 above 0,05. The information from both classes was therefore homogeneous.
The findings of the data showed that sign in Table 4.4. The post- test score value was 0,230. Since the data was greater than the meaning point (0,230 > 0, 05), it was found that the post-test data was homogeneous.
c. Hypothesis Test
At SMA Negeri 10 Maros, the study was to find out the impact of Decoding Skills for student automaticity in reading comprehension.
For this reason, the test of hypothesis is essential in order to find the test outcome. The effect size test therefore contributes to the T-test consequences. The experiment used data from the experimental and controlled class post-test scores to be compared. The outcome of the data can be seen as follows:
Table 4.5 The Result of T-test Calculation
Group Statistics
Class N Mean Std.
Deviation
Std.
Error Mean
Pre_Test
Experimental
Class 26 57,50 11,158 2,188
Control Class 26 60,58 12,274 2,407
Post_Test
Experimental
Class 26 79,23 7,306 1,433
Control Class 26 65,12 10,486 2,056
Source: SPSS 21
Table 4.5 information showed a significant distinction between the experimental class standard deviation pre-test and post-test score. The standard deviation in the experimental class decreased from 11,158 to 10,486 based on both tables. Furthermore, both classes‟ pre and post-test score increases considerably. In other words, the comprehension of teaching reading through Decoding Skills was implemented successfully in the classroom and all students have shown together their progression.
Table 4.6 T-test Result of Pre-test and Post-test Scores
Independent Samples Test Levene's
Test for Equality of
Variances
t-test for Equality of Means
F Sig. T Df Sig.
(2- tail ed)
Mean Differe nce
Std Error Differ
ence
95%
Confidence Interval of the
Difference Lower Upper
Pre-test
Post-test
Equal variances assumed
Equal variances not assumed
Equal variances assumed
Equal variances assumed
.171
1.477
.681 -.946
-.946
5.632
5.632 50
49.552
50
44.646 .349
.349
.000
.000
-3.077
-3.077
14.115
14.115
3.253
3.253
2.506
2.506
-9.611
-9.612
9.081
9.066
3.457
3.459
19.150
19.165
Based on the table 4.6 , the independence sample test findings indicate that p-value or sig (2-tailed) = 0.000, meaning that the null hypothesis (Ho) is dismissed and alternative hypothesis (Ha) is accepted because the p-value (0,000) is lower than sig a = 0.05(0.000 < 0.05).
Accordingly, the use of Decoding Skills for students‟ automaticity in reading comprehension at tenth-grade students of SMA Negeri 10 Maros has a statistical significance.
d. Cohen Effect Size
The final stage after the t-test is the effect size test. The purpose of the effect size test is to determine the level meaning (weak, medium or strong) of the impact of using Decoding Skills for students automaticity in reading comprehension.
In this research, Cohen‟s d effect size calculation was chosen by the researcher for adaptation in the research. In addition, the researcher needs the mean score and standard deviation from the experimental class and controlled class to conduct the effect size test.
D = (Mean of Group A- Mean of Group B) Pooled standard deviation
Louis Cohen et.al (2007)
Pooled standard deviation 7.306 + 10.486 = 8,89 2
D= 79,23 - 65,12
8.89
D = 1.58
The above calculation outcome showed that this research‟s effect size was 1,58. Based on the Cohens effect size criteria, 1,58 was classified as a strong impact. In other words, using Decoding skills has an important impact on the increase reading comprehension by students‟.
B. Discussion
In this part, the writer presents the discussion about the data analysis on the research that has been presented in the previous sub chapter. In this
Criteria of Cohen Effect Size:
0 - 0,20 = Weak Effect 0 - 0.50 = Modest Effect 0 - 1.00 = Moderate Effect
> 1.00 = Strong Effect
> 1,58 Strong Effect
case the writer divides discussion about data analysis, which is intended to find out the any significant effect of using Decoding Skills for students‟
automaticity in reading comprehension, it can be identified through the result of pre-test and post- test experiment class and control class.
The calculated outcome of this research showed that decoding skills was efficient for tenth-grade students‟ reading comprehension of descriptive text in SMA Negeri 10 Maros. The researcher discovered that the autonomous t-test stated that the decoding skills were statistically efficient. From post-test data analysis, this can be seen as the p-value or sig (2-tailed) = 0,000 <sig a= 0,05.
Also by comparing the results of this research between the Experimental classes were treated by Decoding Skills and the Control class was not treated equally. Then reading tests between both classes produces contrasting achievements. By the data in Table 4.1 showed the growing mean score from the experimental class in the descriptive statistics following the implementation of the Decoding Skills from 57,5 to 79. Meanwhile, the control class rating also enhanced significantly, although the strategy that emerged in Table 4.2 was not applied. Its 61 has grown to 65.
According to Hamednalla (2017), Decoding is the process of recognizing letters and sounds to read words.Reading comprehension is a process that involves memory, thinking abstractly, visualization, and
understanding vocabulary as well as knowing how to properly decode, (Ness, 2010: 25).The experimental class did not perform as well as the control class in the pre-test. The experimental class that received the treatment was noted to create interesting changes in their ability to understanding reading comprehension of descriptive text. The use of these decoding skills was proven to help students who have difficulty understanding especially of them.
Therefore, using these decoding skills can increase students‟ reading comprehension. This finding was also in line with the previous research study from Yan,M., at al. (2020), who explained in their result that the decoding vocabulary in reading comprehension ability 666 Chinese children was measured in kindergarten. The result of regression showed that decoding and vocabulary accounted for 32% to 76% of the variance for reading comprehension across grades, and the unique contribution of decoding decreased over the grades while that of vocabulary increased.
The implication and future research direction relating to the influence of decoding and vocabulary on reading development are discussed. So, that decoding was great importance for reading comprehension at the beginning of schools.
Setiawati (2019), in her research, with the title The Students‟ Decoding Ability in Comprehending Reading Text, applied a quantitative method, show that the students' decoding ability in comprehending reading text is the result mean values that researcher obtained through analyzing the data
that has been collected from sixth components of decoding ability. They are previewing, reading for main idea, using context for vocabulary, scanning detail, making inference and locating reference is around 76.73 and from the data, the researcher can conclude that the value is in the 'average' category. In the early grades, decoding instruction is of great importance. Decoding is the ability to capture a certain code and identify the message contained (Adams 1990 etc.).
Moreover, the results of this study certainly support the previously thought related research and showed that the using decoding skill was efficient for students in understanding the text and support. It also showed that teaching reading comprehension of descriptive text using decoding skills made students became active.
It also found from the outcomes that the alternative hypothesis (H1) was approved and that the null hypothesis (Ho) was dismissed. It is also confirmed, the effect size test outcomes is 1.58. Based on the d-effect size criteria of Cohens, 1.58 was classified as a strong effect. In other words, using decoding skill has a significant effect on the increase of the reading comprehension in descriptive text by the students. Therefore, the data processed given responses to the submitted study questions. In conclusion, the study outcome showed that the using decoding skills for students‟
automaticity in reading comprehension was effective on students‟ increase reading comprehension for tenth grade of SMA Negeri 10 Maros.
CHAPTER V
CONCLUSION AND SUGGESTION A. Conclusion
This research was intended to demonstrate the effect of using decoding skills for student‟s automaticity in reading comprehension for tenth-grade students of SMA Negeri 10 Maros in academic year 2021/2022. The researcher used two classes: the experimental class and control class. For both classes, the pre-test and post-test are conducted. The experimental class was taught using decoding skills, while decoding skills has not been given to the controlled class.
Based on data analysis, it can be concluded that using decoding skills was successful for teaching reading comprehension of descriptive text to the tenth-grade students of SMA Negeri 10 Maros. In addition, the outcome of Cohens‟ d‟s effect size test is 1,58. It suggested that this research‟s scope impact is strong. Moreover, it can be concluded is significantly increase the students‟ scores. It also can be proven by the test result and the difference in pre-test and post-test between the two means of score. The pre-test average score was 57,5. The post-test average score was 79. In other words, using decoding skills in teaching of reading comprehension would increase the ability of students and the score of students in reading descriptive text.
It was found that the outcome of the standard deviation from the pre- test of both classes is lower than the post-test; there were 11,158 and 12,274
became 7,306 and 10,486. This mean that decoding skills is implemented effectively in the classroom and all students demonstrated together their progress. It means that Ho was rejected and H1 was accepted. There was a significant effect using decoding skills for students‟ automaticity in reading comprehension.
B. Suggestion a. English Teacher
The English teacher should be more creative to choose, method, strategy, and approach in teaching learning, so that the students would be more interested and motivated to study English for Reading Comprehension.
b. Students
The students should be more active, not nervous and not afraid making mistakes during teaching learning process, especially in reading class. They should more practice in reading English text and enjoying reading class.
c. Other researcher
This research can be a guide for other researchers who are interested in doing similar research. The author also hopes that other researchers will be able to explore more with different skills and research design.