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3.4 Technique of Collecting Data
The technique of data collection in this study involves several steps, those are: a.
Copying the answer sheet in final test of the subject. b.
Collecting the item test and analyzes the result of the item test to know the validity and reliability.
c. Finally, the writer computes the data.
3.5 Technique of Data Analysis
The data to be analyzed in this study were taken from the students’ answer sheet in final test for the seventh grade of SMP students in the academic year
20082009. These students’ answer sheets were used to analyze the quality of the test items. From this item analysis, we would know that the item is too easy or too
hard. Here, the item analysis consists of the following:
a. Difficulty level analysis
A good test item is an item which is not too difficult or too easy. The difficulty of the test items is the percentage of students who get the right items. Here the index
of item difficulty level P used Nitko formula to analyze. Then, the writer divided the level of items difficulty P into three categories. The criteria of item difficulty
level could be seen in the table below:
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No Index Difficulty level P
The categories
1. 0.00- 0.30
Difficult 2. 0.30-
0.70 Moderate
3 0.70- 1.00
Easy Heaton,1975:172
The formula is: P = R
T Where: P = difficulty level or index of difficulty.
R = the number of students who respond correctly to an item. T = the total number of students who respond to the item.
Nitko, 1983:288
b. Discrimination power analysis
The discrimination power of the test items tells how well the item performs in separating the upper group and the lower group. The formula to compute item
discrimination power is as follows D = RU – RL
Where: D = the index of discrimination power
RU = the number of students in the upper group who answer
the items correctly RL
= the number of students in the lower group who answer the items 12T
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correctly ½ T
= one half of the total number of students included in the items analysis.
Gronlund, 1982:103 The criteria of item discrimination power could be seen in the table below which
is proposed by Ebel and Frisbie 1991: 232 are:
Discrimination index Item evaluation
0.70 ≤ DP≤ 1.00
Excellent 0.40 DP
≤ 0.70 Good
0.20 DP ≤ 0.40
Satisfactory 0.00 DP
≤ 0.20 Poor
c. Analysis of reliability
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