A. Finding
1. Student Reading Comprehension in Implementing Blended Learning with Quizizz App
57 CHAPTER IV
FINDING AND DISCUSSION
analyzing, classifying the student score on pre-test and post-test, and hypothesis testing.
a. Assumption Testing 1) Normality Test Table 4.1 Normality test
Tests of Normality
Outcomes
Class
Kolmogorov-Smirnova Shapiro-Wilk Statistic df Sig. Statistic df Sig.
Pre-test for Experimental
Class ,157 25 ,115 ,947 25 ,210
Post-test for Experimental
Class ,153 25 ,135 ,923 25 ,059
Pre-test for Control Class ,141 24 ,200* ,952 24 ,298
Post-test for Control Class ,155 24 ,143 ,932 24 ,108
Guidelines for drawing conclusions as described in CHAPTER III that, if the significance value or probability value is greater or (Sig. >= 0.05), then the data that has been collected is normally distributed. The purpose of conducting a normality test on research data is to serve as a guide for researchers in conducting data analysis. If the data that has been collected is normally distributed, then the data analysis is carried out by parametric statistical analysis and if the data is not normally distributed, the data will be analyzed by non-parametric analysis. In conducting the normality test of the data in this study, the researcher used the computer program SPSS version 25 for 32bit windows. Testing the normality of the data on the SPSS using the Kolmogorov-Smirnov test. Thus, the results are obtained as shown in table 4.1 above. The significance value in the
Kolmogorov-Smirnov test is greater than 0.05. So it can be concluded that the data obtained in the field is normally distributed. Thus, the data analysis in this study was carried out by parametric analysis.
2) Homogeneity test of variance
Table 4.2 Test of Homogeneity of Variance Levene
Statistic df1 df2 Sig.
Student learning outcomes
Based on Mean ,593 1 47 ,445
Based on Median ,691 1 47 ,410
Based on Median
and with adjusted df ,691 1 46,754 ,410 Based on trimmed
mean ,653 1 47 ,423
Research data that has been tested normally distributed can be tested for hypotheses. However, to get a higher level of data validity, the researchers conducted a homogeneity test. The homogeneity test aims to determine whether the population variance is homogeneous or not. If the population variance is homogeneous, it can be concluded that changes in the behavior of the research sample are caused by the treatment that has been given. Furthermore, the homogeneity test carried out in this study is Levine’s Test. As a guideline in decision making is if the significance value (Sig.> 0.05) then the data is homogeneous. On the other hand, if the significance value is (Sig. <0.05), then the data is not homogeneous.
The significance value in the table above shows that the significance value of the homogeneity test results with Levine’s test based on the mean is 0.445.
Based on these results, the significance value of the homogeneity test results is greater than 0.05 at the 5% confidence level or (Sig. 0.445>0.05). Thus, it can be concluded that the population variance is homogeneous. Data from population variance that have been tested are homogeneous, it can be assumed for a while that changes in behavior that occur in the research sample are based on the treatment that has been given.
b. Descriptive analyzing
Table 4.3 Descriptive analyze of the student score on pre-test and post-test of experimental class.
Test Max. Min. Median Range Mean Std.
Deviation
Pre-test 80 50 70 30 68 8.16
Post-test 100 80 90 20 90 6.12
Table 4.3 above shows the data regarding the data from the descriptive analysis of the scores obtained by the students when the researchers conducted the pre-test and post-test. The results of the data analysis showed that the maximum score obtained by students in the pre-test was only 80. On the other hand, the lowest score obtained by students was 50. Furthermore, the standard deviation of the data collected in the pre-test was 8.16 with the mean score is 68. Furthermore, after giving treatment, the researcher gave a post-test to find out whether there was an increase in students' ability to understand English reading comprehension texts or not. The score that can be obtained by students in the post-test as shown in table 4.3 above is the minimum score obtained by students is 80 while the
maximum value is 100. Furthermore, the average score of students is 90. Thus, it can be concluded that, the average students' abilities increased significantly after the treatment, namely the application of the blended learning model with the Quizizz application. In fact, the standard deviation of the data obtained is decreasing. This shows that students' abilities are more evenly distributed after being given treatment in the form of applying a blended learning model with the Quizizz application. Furthermore, the following is a table of frequency distribution of data collected by the researcher when doing of pre-test and post-test. Furthermore, the following is a descriptive statistical table of the pre-test and post-test scores of students in the control class.
Table 4.4 Descriptive analyzing of pre-test and post-test in control class
Test Max. Min. Median Range Mean Std.
Deviation
Pre-test 85 50 65 35 64 9.70
Post-test 90 60 70 30 73 9.44
Table 4.4 above shows the scores obtained by students in the control class, both at the time of pre-test and post-test. The minimum score obtained by students in the pre-test is 50 and the maximum score is 85. Meanwhile, in the post-test the increase in scores is not too significant. In table 4.4 above, the minimum score obtained by the students on the post-test is 60 and the maximum score is 90.
Furthermore, the mean score of the students on the pre-test is 64 and the average score of the students on the post-test is 73. This value is still below the minimum criteria of competences value (KKM) which is 75. This shows that the average student in the control class has not been able to understand the reading material
given through the online learning model using worksheets. Furthermore, the decrease in the standard deviation value is not significant. Thus, students' ability to understand reading texts is very uneven and only a few students get scores above the minimum criteria of competences (KKM).
c. Classifying the student score on pre-test and post-test
Table 4.5 Classifying the student score on pre-test and post-test of experimental class
Score Pre-test Post-test
Classification Freq. Percent Freq. Percent
≥ 95 0 0% 9 36% Excellent
80 – 94 3 12% 16 64% Very good
75 – 79 5 20% 0 0% Good
60-74 14 56% 0 0% Fairly Good
50-59 3 12% 0 0% Poor
0-49 0 0% 0 0% Fairly Poor
Total 25 100% 25 100%
The table above shows the results of the frequency distribution of the experimental class scores on the pre-test and post-test. The scores obtained by students in the experimental class in the pre-test, there were 3 students who got scores with the predicate of Very Good. There are 4 students who got scores with the predicate of Good. The percentage of students who scored above the KKM was only 32% of the total number of students as a sampled in this study in the experimental class. Furthermore, there were 14 students who scored with the Fairly Good predicate. In fact, there were 4 students who scored with the predicate Poor. The percentage of students who scored below the KKM was 68%.
Thus, it can be concluded that the average student's ability to understand reading texts is still low.
The data that have collected in the pre-test will be used by the researcher as a comparison to the data collected in the post-test. The post-test was carried out after the researcher gave treatment to the sample. The results of the post-test, as shown in the table above. The table in the post-test column shows a very significant difference, in which the scores obtained by all students have passed the KKM. In fact, there were 9 students who got scores with the predicate of Excellent or 36%. Furthermore, students who got scores with the Very Good predicate were 16 students or 64%. It can be concluded that the students' ability to understand English reading texts increased significantly.
Table 4.6 Classifying the student score on pre-test and post-test of control class
Score Pre-test Post-test
Classification Freq. Percent Freq. Percent
≥ 95 0 0% 0 0% Excellent
80 – 94 2 8% 8 33% Very good
75 – 79 4 17% 3 13% Good
60-74 12 50% 13 54% Fairly Good
50-59 6 25% 0 0% Poor
0-49 0 0% 0 0% Fairly Poor
Total 24 100% 24 100%
The table above shows that the average ability of students in understanding English reading texts on the pre-test is still very low. It can be seen that the number of students who score above the Minimum Criteria of Competences (KKM) is still small. Only 2 students got scores with very good predicate or 8%
of the total sample in the control class. Only 4 students got scores with the predicate of Good or 17%. The total number of students who got scores above the KKM score of 75 was 6 students or 25%. On the other hand, students who scored below the KKM score were 18 students or 75%. Each student who scored with the Fairly Good predicate was 12 students or 50%. Students who scored with the Poor predicate were 6 students or 25%. This means that in the pre-test the average ability of students in understanding English reading texts is still very low.
In this study, the control class was treated with the implementation of an online learning model, namely delivering the material or worksheet online. After the treatment was given, the researcher carried out a post-test to find out whether the students' ability to understand English reading texts increased or not. The data obtained in the post-test as shown in the table above shows that there is no significant difference in the average ability of students in understanding English reading texts. In the table above, students who scored above the KKM score were 11 people or 46%. Each student who scored with the Very Good predicate was only 8 students or 33%. Only 3 students scored with the predicate of Good or 13%.
On the other hand, students who got scores below the KKM score were still very large, namely 54%. Each student who scored with the Fairly Good predicate was 13 people or 54%. It can be concluded that the average ability of students in understanding English reading texts is still very low, namely 54% of students who have not been able to pass the KKM. Thus, it can be concluded that
there is no significant increase in students' ability to understand English reading texts after learning by giving online worksheets to the control class.
d. Hypothesis testing
Table 4.7 Hypothesis testing paired sample test (2-tailed) Paired Samples Test
Paired Differences
t df
Sig.
(2-tailed)
Mean Std.
Deviation Std.
Error Mean
95% Confidence Interval of the
Difference Lower Upper Pair 1 Pre-Test -
Post-Test -22,000 5,590 1,118 -24,308 -19,692 -19,677 24 ,000
Guidelines for drawing conclusions as described in CHAPTER III that, if the results of the Paired Sample Test (2-Tailed) Sig. < (α) 0.05, then H0 is rejected and Hi is accepted. If the significant value of the Paired Sample Test (2-Tailed) test result is Sig.>(α) 0.05, then H0 is accepted and Hi is rejected. Based on the results of the Paired Sample Test conducted using the SPSS Version 25 computer program for Windows 32bit, it can be seen the value of Sig. (2-tailed) is 0.000.
Thus, the significant value is less than (α) 0.05 or (Sig.(2-tailed) 0.00<0.05).
Based on these results, H0 is rejected and Hi is accepted. In other words, There is a significant difference of the student's learning outcomes in learning English reading text after the implementation of blended learning using the Quizizz application.
2. Student Learning Interest in Implementing Blended Learning with