G. Jurs, Stephen and Wiersma, William. Research Methods in Education-An Introduction, Boston: Pearson Education, Inc., 2009.
Harmer, Jeremy. The Practice of English Language Teaching, New York: Longman, 1991.
Hedge, Tricia. Writing, Oxford: Oxford University Press, 1990.
Huck, Charlotte S and Keifer, Barbara. Children’s Literature in the Elementary
School, New York: The Mc Graw Hill, 2004.
Hughes, Arthur. Testing for Langiage Teachers, New York: Cambridge University Press, 2003.
Hyland, Ken. Second Language Writing, New York: Cambridge University Press,1996.
Jalongo, Mary Renck. Young Children and Picture Books, Washington, DC: National Association for the Education of Young Children NAEYC, 2004.
Kane, Thomas S. The Essential Guide to Writing, New York: Barkeley Books, 2000.
Kiefer, Barbara Z. Charlotte Huck’s Children’s Literature, New York: McGraw-Hill,
2010.
Lewin, Larry. Paving the Way Reading and Writing, New Jearsey: John Wiley Sons, Inc., 2003.
McElveen, Susan Anderson and Dierking, Connie Campbell. Children‟s Books as Models to Teach Writing Skill: The Reading Teacher, 54, 2001.
Meyers, Alan.Gateways to Academic Writing, New York: Pearson Education, Inc., 2005.
Oshima, Alice and Hogue, Ann. Writing Academic English Third Edition, New York: Longman, 1999.
Pardiyono, Drs. Pasti Bisa Teaching Genre Based Writing, Yogyakarta: Penerbit Andi, 2007
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60
APPENDIX 1 The Analytic FictionNarrative Writing Content Rubric
The analytic fictionnarrative writing content rubric from
Vicki L. Kohen and John Edwin Cowen‟s rubric:
1
Category Excellent
10 points Good
7.5 points Satisfactory
5 points Need
Improvement 2.5 points
Writing Process
Student devotes a lot of time and
effort to the writing process
prewriting, drafting,
reviewing, and editing. Work
hard to make the story wonderful.
Student devotes sufficient time and
effort to writing process
prewriting, drafting,
reviewing, and editing. Work
hard to make the story wonderful.
Works and gets the job done.
Student devotes some times and
effort to the writing process,
but was not very thorough. Does
enough to get by. Student devotes
little time and effort to the
writing process. Does not work
hard.
Setting Many vivid,
descriptive words are used to tell
when and where the story took
place. Some vivid
descriptive words are used to tell
when and where the story took
place. The reader can
figure out when and where the
story took place, but the author did
no supply much detail.
The reader has trouble figuring
out where the story took place.
Characters The main
The main The main
It is hard to tell
1
Vicki L. Kohen and John Edwin Cowen, op-cit, p. 359
characters are named and clearly
described in text. Most readers
could describe the characters
accurately. characters are
named and described. Most
readers would have some idea of
what the characters looked like.
characters are named. The
reader knows little about the
characters. who the main
characters are.
Introduction Organization
The introduction is inviting and
previews the plot of the paper.
The introduction previews the plot
of the paper, but it is not particularly
inviting to the reader.
The introduction is not nothing to
do with the plot, nor is it
particularly inviting to the
reader. There is no clear
introduction.
V. Sequencing Organization
Details are placed in logical order
and the way they are presented
effectively keeps the interest of the
reader. Details are placed
in logical order, but the way they
are presented or introduced
sometimes makes the writing less
interesting. Some details are
not in a logical or expected order,
and this distracts the reader.
Many details are not in a logical or
expected order. There is a little
sense that the writing is
organized.
Transition Organization
A variety of thoughtful
transitions are used. They clearly
show how ideas are connected.
Transitions clearly show how ideas
are connected, but there is little
variety. Some transitions
work well, but connections
between other ideas are fuzzy.
The transitions between ideas are
unclear or nonexistent.
Conclusion Organization
The coclusion is strong and leaves
the reader with a feeling that they
understand what the writer is
„getting at‟ The conclusion is
recognizable and ties up almost all
the loose ends. The conclusion is
recognizable but does not tie up
several loose end. There is no
conclusion, the paper just end.
Grammar and Spelling
Writer makes very few errors in
grammar or spelling and it
does not distract the reader from
the content. Writer makes few
errors in grammar or spelling that
distract the reader from the content.
Writer makes numerous errors
in grammar or spelling that
distract the reader from the content.
Writer makes frequent errors in
grammar or spelling that
distract the reader from the content.
Capitalization and
Punctuation Writer makes
very few errors in capitalization or
punctuation; thus the paper is
exceptionally easy to read.
Writer makes few errors in
capitalization or punctuation, but
the paper is still easy to read.
Writer makes numerous errors
in capitalization andor
punctuation that catch the reader‟s
attention and interrupt the flow.
Writer makes frequent errors in
capitalization andor
punctuation that catch the reader‟s
attention and interrupt the flow.
Instrument of the Experimental and Control Class’ Pretest
PRETEST Name:
Class:
63
Write a narrative text of not less than 15 sentences about a story you like most from story books you have ever read or movies you have ever watched. You have 60 minutes to do
this.
Instrument of the Experimental and Control Class’ Posttest
POST-TEST Name:
Class:
64
Direction:
Write a narrative text fable of not less than 15 sentences Your writing must have:
-
Orientation
-
Sequence of events
-
Resolution
-
Coda moral value. You have 80 minutes to do this.
65
APPENDIX 4
The followings were the table which presented the experimental and the control class‟ pretest and posttest score:
Table 4.1 The Score of the Experimental and Control Class‟ Pretest
Student’ Number
Pretest Score Experimental Class
Control Class
1. 50
25 2.
22.5 27.5
3. 32.5
40 4.
30 32.5
5. 35
67.5 6.
60 62.5
7. 55
67.5 8.
35 52.5
9. 60
50 10.
55 67.5
11. 67.5
30 12.
42.5 47.5
13. 30
67.5 14.
62.5 40
15. 30
47.5 16.
27.5 45
17. 40
72.5 18.
40 32.5
19. 25
60 20.
27.5 32.5
21. 25
45 22.
30 25
23. 50
22.5
24. 42.5
22.5 25.
50 25
26. 27.5
25 Total
1052.5 1132.5
Mean 40.48
43.56
Table 4. 2 The Score of the Experimental and the Control Class‟ Posttest
Student’ Number
Posttest Score Experimental Class
Control Class
1. 60
35 2.
32.5 32.5
3. 50
55 4.
67.5 42.5
5. 62.5
35 6.
77.5 55
7. 62.5
67.5 8.
67.5 60
9. 70
55 10.
67.5 70
11 80
50 12.
45 55
13. 32.5
45 14.
77.5 32.5
15. 65
50 16.
60 77.5
17. 75
75 18.
65 45
19. 27.5
47.5 20.
57.5 50
21. 57.5
45 22.
50 45
23. 72.5
52.5 24.
72.5 60
25. 77.5
55 26
50 55
Total 1582.5
1347.5 Mean
60.87 51.83
68
APPENDIX 5 The Calculation of Frequency Distribution of the Pretest and
Posttest
Descriptive Statistics Pretest Score
Experiment N
Valid 26
Missing Mean
40.481 Std. Error of Mean
2.6458 Median
37.500 Mode
30.0 Std. Deviation
13.4911 Variance
182.010 Range
45.0 Minimum
22.5 Maximum
67.5 Sum
1052.5 Control
N Valid
26 Missing
Mean 43.558
Std. Error of Mean 3.2851
Median 42.500
Mode 25.0
a
Std. Deviation 16.7507
Variance 280.587
Range 50.0
Minimum 22.5
Maximum 72.5
Sum 1132.5
a. Multiple modes exist. The smallest value is shown
Frequency Distribution of Pretest Score
Class Frequency
Percent Valid
Percent Cumulative
Percent Experiment
22.5 1
3.8 3.8
3.8 25.0
2 7.7
7.7 11.5
27.5 3
11.5 11.5
23.1 30.0
4 15.4
15.4 38.5
32.5 1
3.8 3.8
42.3 35.0
2 7.7
7.7 50.0
40.0 2
7.7 7.7
57.7 42.5
2 7.7
7.7 65.4
50.0 3
11.5 11.5
76.9 55.0
2 7.7
7.7 84.6
60.0 2
7.7 7.7
92.3 62.5
1 3.8
3.8 96.2
67.5 1
3.8 3.8
100.0 Total
26 100.0
100.0 Control
22.5 2
7.7 7.7
7.7 25.0
4 15.4
15.4 23.1
27.5 1
3.8 3.8
26.9 30.0
1 3.8
3.8 30.8
32.5 3
11.5 11.5
42.3 40.0
2 7.7
7.7 50.0
45.0 2
7.7 7.7
57.7 47.5
2 7.7
7.7 65.4
50.0 1
3.8 3.8
69.2 52.5
1 3.8
3.8 73.1
60.0 1
3.8 3.8
76.9 62.5
1 3.8
3.8 80.8
67.5 4
15.4 15.4
96.2 72.5
1 3.8
3.8 100.0
Total 26
100.0 100.0
Descriptive Statistic Posttest Score
Experiment N
Valid 26
Missing Mean
60.865 Std. Error of Mean
2.8486 Median
63.750 Mode
50.0
a
Std. Deviation 14.5248
Variance 210.971
Range 52.5
Minimum 27.5
Maximum 80.0
Sum 1582.5
Control N
Valid 26
Missing Mean
51.827 Std. Error of Mean
2.3475 Median
51.250 Mode
55.0 Std. Deviation
11.9699 Variance
143.279 Range
45.0 Minimum
32.5 Maximum
77.5 Sum
1347.5 a. Multiple modes exist. The smallest value is shown
Frequency Distribution of Posttest Score
Class Frequency Percent
Valid Percent
Cumulative Percent
Experiment 27.5
1 3.8
3.8 3.8
32.5 2
7.7 7.7
11.5 45.0
1 3.8
3.8 15.4
50.0 3
11.5 11.5
26.9 57.5
2 7.7
7.7 34.6
60.0 2
7.7 7.7
42.3 62.5
2 7.7
7.7 50.0
65.0 2
7.7 7.7
57.7 67.5
3 11.5
11.5 69.2
70.0 1
3.8 3.8
73.1 72.5
2 7.7
7.7 80.8
75.0 1
3.8 3.8
84.6 77.5
3 11.5
11.5 96.2
80.0 1
3.8 3.8
100.0 Total
26 100.0
100.0 Control
32.5 2
7.7 7.7
7.7 35.0
2 7.7
7.7 15.4
42.5 1
3.8 3.8
19.2 45.0
4 15.4
15.4 34.6
47.5 1
3.8 3.8
38.5 50.0
3 11.5
11.5 50.0
52.5 1
3.8 3.8
53.8 55.0
6 23.1
23.1 76.9
60.0 2
7.7 7.7
84.6 67.5
1 3.8
3.8 88.5
70.0 1
3.8 3.8
92.3 75.0
1 3.8
3.8 96.2
77.5 1
3.8 3.8
100.0 Total
26 100.0
100.0
73
APPENDIX 6 The Result of Normality Test
A. Normality Test Calculation of the Experimental and Control
Class’ Pretest
The result of normality test of the experimental and the control class’
pretest was gained from Lilliefors test using IBM Statistics SPSS 19. The result of normality test of the experimental and control
class’ pretest was presented in this following table:
Table A.1
Tests of Normality
Class Kolmogorov-Smirnov
a
Statistic Df
Sig. Pretest Score
Experiment .166
26 .063
Control .168
26 .056
a. Lilliefors Significance Correction
After gaining the result of normality test of the experimental and control class’ pretest, it was continued to interpret the result using the degree
of significance 5 α = 0.05. The criteria of taking the decision is as follow:
1. Hypothesis which was determined: H
: sample data is normally distributed. H
1
: sample data is not normally distributed. 2. Criteria to test the hypothesis:
If the significance level or probability value p ≥ 0.05, H
is accepted. If the significance level or probability value p 0.05, H
is rejected. The result of the normality test above showed that the significance level or the
probability value p of the experimental class was 0.063 and the control one was 0.056. It meant that the probability value p of both experimental and
control class was higher than the degree of significance 5 α = 0.05.
Therefore, it could be concluded that the data of both the experimental and the control class’ pretest was normally distributed.
B. Normality Test Calculation of the
Experimental and Control Class’ Posttest
The result of normality test of the experiment al and control class’
posttest was also gained from Lilliefors test using IBM Statistics SPSS 19. The following was the result of normality test of the experimental and control
class’ posttest which was presented in this table:
Table B.1
Tests of Normality
Class Kolmogorov-Smirnov
a
Statistic Df
Sig. Posttest Score
Experiment .139
26 .200
Control .165
26 .068
a. Lilliefors Significance Correction . This is a lower bound of the true significance.
After gaining the result of normality test of the experimental and control class’ posttest, it was continued to interpret the result using the degree
of significance 5 α = 0.05. The criteria of taking the decision is as follow:
1. The hypothesis which was determined: H
: sample data is normally distributed. H
1
: sample data is not normally distributed. 2. The criteria to test the hypothesis:
If the significance level ≥ 0.05, H is accepted.
If the significance level 0.05, H is rejected.
The result of the normality test above showed that the significance level or the probability value p of the experimental class was 0.200 and the control one
was 0.068. It meant that the probability value p of both the experimental and the control class was higher than the degree of significance 5
α = 0.05. Thus, it could be proved that the data of both the experimental and control
class’ posttest was normally distributed.
76
APPENDIX 7 The Normal Histogram
A. The Histogram of
the Experimental and Control Class’ Pretest
These following histograms also showed that the data of the experimental and control class‟ pretest score met the criteria of normal distribution:
Figure A.1. Normal Histogram of the Experimental Class‟ Pretest Score
Figure A .2. Normal Histogram of the Control Class‟ Pretest Score
Both the figure A.1 and A.2 above represented the histogram which had a shape like a bell-curve indicating that the distribution data was normal. Even
though the histog ram‟s bell-curve in the figure A.2 was fatter and shorter than
the figure one, but both curves were symmetrical. Hence, it could be said that the data of the experimental
and control class‟ pretest met the criteria of normality.
