Scoring Element
Scale Quality
Description
2 Very Poor
No mastery of conventions – dominated by errors of spelling, punctuation,
and capitalization – handwriting illegible – OR
not enough to evaluate.
I. Statistical Hipothesis
The statistical hypothesis of this research was as follow: H
o
: µ
1
= µ
2
H
a
: µ
1
≠ µ
2
H
o
: There was no significant difference between students’ achievement in writing narrative text using story mapping and without using story mapping
technique. H
a
: There was a significant difference between students’achievement in writing narrative text by using story mapping strategy and without using story
mapping technique. And then, the criteria used as follows:
1. If t-test t
o
t-table t
t
in significant degree of 0.05, H
o
null hypothesis is rejected. It means that the rates of mean score of the post-test are higher
than the pre-test.The using of story mapping is effective to teach students’ writing ability of narrative text.
2. If t-test t
o
t-table t
t
in significant degree of 0.05, H
o
the null hypothesis is accepted. It means that the rates of the means score of the
post-test are same as or lower than the pre-test. The using of story mapping is not effective to teach students’ writing ability of narrative text.
33
CHAPTER IV RESEARCH FINDINGS AND INTERPRETATION
A. RESEARCH FINDINGS
1. Description of the Data
The research was done at the second grade of SMAN 90 Jakarta. Because the research was a pre-experimental research, there was only one class in the research.
There were six meetings and all the students followed the teaching learning process from the first meeting until the last meeting.
The material which was taught in this research was narrative text. The researcher gave pre-test to the students to know the initial students’ competence in writing
narrative text.After that, the researcher gave post-test in the last meeting to know the improvementof students’ understanding of narrative text after implementing story
mapping technique. The test was in the form of essay and the researcher only provided a theme to the students. Then, in scoring students’ writing, the writer used
rubric of writing scoring that belongs to Jacob et al. Here, describe briefly how is scoring. After the writer analyzed students’ work, she calculated pre-test and post-test
score. The following table is descriptive statistics of pre-test and post-test that is calculated by using SPSS 20:
Table 4.1 Descriptive Statistics
N Range
Minimum Maximum Sum
Mean Std.
Deviation Variance
Statistic Statistic Statistic
Statistic Statistic Statistic
Std. Error
Statistic Statistic
Pre-test X
40 32
40 72
2491 62.27
1.233 7.795
60.769
Post-test Y
40 25
60 85
2942 73.55
.923 5.835
34.049
Valid N 40
From the descriptive analysis above, it can be seen that the minimum score in pre-test X is 40 and the minimum score in post-test was 60. The maximum score in pre-test
was 72 and the maximum score in post-test was 85. Then, the mean of pre-test was 62.27 and the mean of post-test was 73.55. It means that there is an improvement in
students’ writing achievement because the mean of post-test score is higher than the mean of pre-test score. Here are the complete lists of pre-test and post-test score:
a. Pre-test score
Pre-test was conducted before the implementation of story mapping in order to know students’ writing ability of narrative text before the experiment. From the table
below, it can be seen that the highest score in pre-test was 72 and the lowest score was 40. And the average of the pre-test score was 62.27.
Table 4.2 The Result of Pre-test Score before Implementing Story Mapping
Students’ Number Pre-test
Student 1 58
Student 2 60
Student 3 72
Student 4 43
Student 5 65
Student 6 65
Student 7 68
Student 8 40
Student 9 64
Student 10 68
Student 11 72
Student 12 57
Student 13 62
Student 14 60
Student 15 63
Student 16 60
Student 17 68
Student 18 65
Student 19 68
Student 20 60
Student 21 50
Student 22 71
Student 23 61
Student 24 70
Student 25 60
Student 26 68
Student 27 58
Student 28 68
Student 29 69
Student 30 72
Student 31 68
Students’ Number Pre-test
Student 32 66
Student 33 58
Student 34 55
Student 35 50
Student 36 68
Student 37 69
Student 38 50
Student 39 67
Student 40 55
Total 2491
Average ∑
62.27
b. Post-test score
Post-test was conducted after the implementation of story mapping in order to see the improvement that made by students in writing narrative text. The following
table is the result of post-test score after implementing story mapping technique in teaching variable Y post-test. The table shows that the highest score in post-test
was 85 and the lowest score was 60. And the mean of the pre-test score was 73.55.
Table 4.3 The Result of Post-test Score after Implementing Story Mapping
Students’ Number Post-test
Student 1 70
Student 2 76
Student 3 85
Student 4 65
Student 5 80
Student 6 75
Student 7 70
Student 8 68
Student 9 80
Student 10 75
Student 11 82
Student 12 70
Student 13 70
Student 14 76
Student 15 77
Student 16 80
Student 17 75
Student 18 67
Student 19 70
Student 20 78
Student 21 72
Student 22 70
Student 23 83
Student 24 72
Student 25 78
Student 26 74
Student 27 70
Students’ Number Post-test
Student 28 60
Student 29 81
Student 30 85
Student 31 75
Student 32 73
Student 33 76
Student 34 70
Student 35 73
Student 36 63
Student 37 65
Student 38 70
Student 39 70
Student 40 73
Total 2942
Average ∑
73.55
The writer compared the data in both pre-test and post-test score. The highest score in pre-test was 72 and the highest score in the post-test was 85. Meanwhile, the
smallest score in pretest was 40 and the smallest score in post-test was 60. In addition, the tables indicate that the mean of pre-test score was 62.27 and the mean of
post-test score was 73.55. It means that the mean of post-test is higher than the mean of pre-test, so the writer concludes that there was an improvement in students’ score
in writing narrative text after they were taught by using story mapping technique.
2. Analysis of Data
From the data above, the writer analyzed the data using t-test in both manual calculation and using SPSS 20. This analysis was done to examine the difference of
score between pretest and posttest. First, the writer manually analyzed the score from pre-test and post-test by calculating the result score into the formula as follows:
1. Seek D Diference between score of variable I X and score of variable II Y
and then D = X-Y 2.
Add D then getting ∑ D
