After that , the writer tries to know the class percentage which pass the KKM 65, the writer uses the formula:
8
P : The class percentage F : Total percentage score
N : Number of students After getting mean of students’ score per actions, the writer identifies
whether or not there might have any improvement of students’ imperative sentence from pre-
test up to students’ average score in cycle 1 and cycle 2. In analyzing that, the writer uses the formula:
9
P : P ercentage of students’ improvement
y : Pre-test result y1 : Post-test 1
8
Anas Sudijono, Pengantar Statistik Pendidikan …, p. 43.
9
David E. Meltzer, The Relationship between Mathematics Preparation and Conceptual Learning Gain in Physics: A Possible Hidden Variable in Diagnostic Pretest Scores, Iowa:
Departement of Physics and Astronomy, 2008, p.3.
F P =
── X 100 N
y1 - y P =
─── X 100 y
P : P ercentage of students’ improvement
y : Pre-test result y2 : Post-test 2
J. Trustworthiness
In this research the writer used data from other sources, such as observation, questionnaire, and interview.
“Triangulation involves gathering data from a number of different sources so that the research findings or
insights can be tasted out against each other ”.
10
To analyze the examined test items, the writer implements the trustworthiness of the test. There are some phases including:
1. Discriminating Power
“The analysis of discriminating power of test items is to know the performance of the test through distinguishing students who have high
achievement and low achievement. Discriminating power provides a more detailed analysis of the tes
t items than doe’s item difficulty, because it show how the top scores and lower scores performed on each item
”.
11
The computing of discriminating power uses the formula as following:
12
10
Anne Burns, Collaborative Action Research …, p. 25.
11
Kathleen M. Bailey, Learning about Language Assessment: Dilemmas, Decisions, and Direction, London: Heinle Heinle Publisher, 1998, p. 135.
12
Wilmar Tinambunan, Evaluation of Student Achievement, Jakarta: Depdiknas, 1998, p. 139.
y2 – y
P = ─── X 100
y
U – L
D = ────
N In which, D : The index of discriminating power
U : The number of pupils in the upper group who answered the item correctly
L : The number of pupils in the lower group who answered the item correctly
N : Number of pupils in each of the groups Next, the discriminating scale uses:
13
DP REMARK
≤ 0.40 Used
0.20 – 0.39
Revised ≤ 0.10
Discarded
13
J. B. Heaton, Classroom Testing, New York: Longman Inc, 1990, p. 174.
2. Difficulty Item
“The good items are an item that is not very easy or difficult. An easy item doesn’t make the students to solve the problems. And the
difficult item can make them pessimistic and don’t have enthusiasm to try
solving the problems because they can not reach it ”.
14
The difficulty item analysis concerns with the proportion of comparing students who answer correctly with all of students who follow
the test. “Item difficulty is one of conventional quantitative analysis which
was simple and easy ”.
15
The formula as following:
16
B P =
── JS
In which, P : Index of difficulty B : The total number of students who selected the correct answer
JS: The total number of students including upper and lower group.
14
Suharsimi Arikunto, Dasar-dasar Evaluasi Pendidikan, Jakarta: Bumi Aksara, 2009, p. 207.
15
Ahmad Sofyan et-al, Evaluasi Pembelajaran Berbasis Kompetensi, Jakarta: UIN Jakarta Press, 2006, p. 103.
16
Suharsimi Arikunto, Dasar-dasar Evaluasi Pendidikan …, p. 208.
The criterion that is used is as:
17
ID REMARK
– 0.25 Difficult
0.26 – 0.75
Moderate 0.76
– 1.00 Easy
17
Ahmad Sofyan et-al, Evaluasi Pembelajaran Berbasis Kompetensi …, p. 104
