Writing Test Research Instruments and Data Gathering Technique
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of the descriptions Cohen, Manion, and Morrison, 2011. Two types of descriptive statistics were used in this research:
1. Mean scores from measures of central tendency
Central tendency is descriptive statistics which describes the majority of scores in a set of scores. According to Cohen, Manion, and Morrison 2011,
“Central tendency of a set of scores is the way in which they tend to cluster round the middle of a set o
f scores, or where the majority of scores are located” p.627. The researcher used only the mean scores from the measures of central tendency to
analyze the result of the writing test. The mean scores are the average scores of all scores. The formula is:
X = Total mean score
∑X = Total scores of all participants N
= The number of participants
The mean scores were calculated from the result of peer assessment among the students; the first two scores from two meetings in cycle one came from peer
assessment in group, and the last scores from the third meeting in cycle two came from peer assessment in pair. There were seven sets of scores based on the
categories of critical writing and the final scores in the scoring rubric: arguments, evidences, target audience, organization, sources, total raw mean scores, and final
Figure 2: Formula of total mean score
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mean scores. The mean scores were calculated from the scores of 19 students as the participants N=19. The range of the score from each category was 1-4; the
lowest score was 1, the highest score was 4. The range of the score from the total raw mean score was 4-20; the lowest score was 4, the highest score was 20. The
range of the final mean score was 20-100, which was the converted raw scores into the scale of 0-100; the lowest score was 20, the highest score was 100. The results
of the mean scores were presented in form of tabulation, as presented in table 3.2. 2.
Percentage difference Percentage difference is a descriptive statistics which compares two
numerical data to see the associations between two of them Cohen, Manion, and Morrison, 2011. According to Cohen, Manion, and Morrison 2011:
The percentage difference is a simple asymmetric measure of association. An asymmetric measure is a measure of one-way association. That is to
say, it estimates the extent to which one phenomenon implies the other but not vice versa p.631
Below is the formula of percentage difference:
PD = Percentage difference
X2 = Cycle 2 mean score
X1 = Cycle 1 mean score
Scale = Data scale
Figure 3: Formula of percentage difference