Results from Students’ Interview

Beside the score before and after IPALL, the gain score is also provided to know the development of student‟s score. Table 4.8 displays the students‟ total score of four classes. Both X MM and X AK 1 have used IPALL. However, X AK 2 and X UPW do not use IPALL in their vocabulary learning. Their detail score is presented in the appendices. Table 4.7. Total Score Before, After, and Gain CLASS TOTAL SCORE BEFORE TOTAL SCORE AFTER TOTAL SCORE GAIN X MM 1906 2500 637 X AK 1 1849 2785 957 X AK 2 1970 2170 292 X UPW 2124 2345 257 After preparing and organizing data from the questionnaire, the data must be analyzed by descriptive statistics. Bluman states that descriptive statistics consists of the collection, organization, summarization and presentation of data 2012:4. According to Creswell 2012 descriptive statistics indicate general tendencies in the data mean, mode, median, the spread of scores variance, standard deviation, and range, or a comparison of how one score relates to all others. Table 4.8 Descriptive Statistics of Vocabulary Learning Strategies X AK 1 X MM TOTAL N 32 32 64 Mean 13.56 8.16 10.86 Mean Weight .452 .272 .362 Median 11.50 11.00 11.00 Range 58 63 70 Mode 8 22 22 Std.Deviation 17.129 16.627 16.966 Minimum -15 -27 -27 Maximum 43 36 43 Mean T ot al 12.5 10 7.5 5 2.5 Klp Eksp MM Eksp AK 1 8.156 13.562 Table 4.8 analyzes the descriptive statistics of students Vocabulary Learning Strategies IPALL. Both X AK 1 and X MM have similar numbers of participants. The descriptive statistics are from students‟ scores in vocabulary class. However, the mean of X AK 1 is higher than X MM. Figure 4.1 The Total Mean of Experiment Group The total mean is found by adding the values of the data and divided by the total number of values. The value is from the students score of vocabulary. The total mean of X AK 1 is 13.56. However, the total mean of X MM is 8.16. However, the result of two experiment groups and two control groups are also obtained. The experiment groups consist of X MM and X AK 1 class while the control groups consist of X UPW and X AK 2 class. Table 4.9. Descriptive Statistics of Experiment and Control Group Group BEFORE AFTER GAIN EXPERIMENT N 64 64 64 Mean 58.67 82.58 23.91 Median 58.50 85.00 25.50 Std. Deviation 12.183 19.231 18.358 Minimum 35 15 -31 Maximum 84 100 59 CONTROL N 64 64 64 GAIN AFTER BEFORE M ea n 100 80 60 40 20 NON-EXPERIMENT EXPERIMENT Kekompok Group BEFORE AFTER GAIN Mean 63.97 70.55 6.58 Median 62.50 73.00 8.00 Std. Deviation 10.303 12.867 10.634 Minimum 36 32 -20 Maximum 88 96 27 Total N 128 128 128 Mean 61.32 76.56 15.24 Median 61.50 77.00 14.00 Std. Deviation 11.548 17.380 17.289 Minimum 35 15 -31 Maximum 88 100 59 The descriptive statistics used in this research are mean, median, standard deviation, minimum and maximum score. However, the result shows that the mean score of experiment group before is 58.67 while after the use of IPALL has increased to 82.58. Then, for the control group the mean score before is 63.97 while in the end of the semester is 70.55. This following figure shows the mean score of both experimental and control group. Figure 4.2. The Total Mean of Experiment and Control Group The blue line belongs to experiment group and the green line belongs to control group. Both of them increase their score. However, the experiment group shows a higher result of score after IPALL rather than the control group. 5. Results from Quasi-Experimental Analysis Another data is from the quasi experimental analysis. The quasi experimental analysis is conducted to discover the effectiveness of the variable of IPALL X1 and variable of Vocabulary Learning Strategies X2. The data used in the quasi-experimental analysis ar e from the percentages of students‟ before, after and gain scores from both experiment and control groups. The data are from lecturer‟s document. Since the data are students‟ score, therefore, the data in quasi-experimental analysis are quantitative data. Before analyzing the statistical result, it is necessary to test the normality of the data to confirm the data and decide whether the test should use parametric or non-parametric. Therefore, the test of One-Sample Kolmogorov-Smirnov was used to test the null hypothesis that the data is normally distributed. The null hypothesis is accepted if the value of the probability was more than 0.05, meaning that the data are normally distributed. If the value of the probability was the same or less than 0.05 then the null hypothesis was rejected, meaning that the data are not normally distributed. The result of the test of normality is presented in Table 4.10. Table 4.10. One-Sample Kolmogorov-Smirnov Test Experiment Group BEFORE AFTER N 64 64 Normal Parametersa,b Mean 58.67 82.58 Std. Deviation 12.183 19.231 Most Extreme Differences Absolute .083 .182