Reza Taufik Maulana, 2014 NUMBERED HEADS TOGETHER NHT: AN ENDEAVOUR TO IMPROVE STUDE
NT’S SCIENTIFIC CREATIVITY AND MASTERY CONCEPT IN LEARNING GLOBAL WARMING
Universitas Pendidikan Indonesia
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1. Quantitative Data Processing
The quantitative data processing is done using Microsoft Excel for pre-test score data and post-test. The value of quantitative data will be gained by the result of
normalized gain. The process of calculating data will be explained as follow:
a Data of Test Score
In this research, the data of test scores is used to measure the improvement of students‟ achievement and problem solving skill. The data processing, have
been carried out in the following way:
1 Score of Scientific Creativity Test
The test consists of four essay question that was related with the topic of the learning. The scoring procedure as follows
Table 3.7 Scoring Procedure of Scientific Creativity Test
Indicator
Fluency Flexibility
Originality Total
Frequency of the Answers 5
5-10 10
Unusual use of object
Sensitivity to science problem
Improvement of Technical product
Percentage
Table 3.8 Scoring Procedure of Scientific Creativity Test
Indicator
Frequency of The Answer
5 5-10
10
3 Point 2 Point
1 Point
Science Problem Solving
Total
The sums of fluency score, flexibility score, and originality score are the scores of Sensitivity to science problem, Improvement of Technical product,
Reza Taufik Maulana, 2014 NUMBERED HEADS TOGETHER NHT: AN ENDEAVOUR TO IMPROVE STUDE
NT’S SCIENTIFIC CREATIVITY AND MASTERY CONCEPT IN LEARNING GLOBAL WARMING
Universitas Pendidikan Indonesia
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Students Scientific Imaginationare. Counting all of the separate responses given by the subjects, regardless of the quality is how to obtain the fluency
score is obtained simply. Counting the number of approaches or areas used in the answer is how to obtain flexibility score for each task. The originality
score is developed from a tabulation of the frequency of all of the responses obtained.Frequencies and percentages of each response are computed. If the
probability of a response is less than 5, we give it 2 points; if the probability is between 5 to 10, we give it 1 point; if the probability of a
response is more than 10, we give it 0 points. The score of science problem skill is computed again by tabulating all answers of all subjects,
and then rating a particular answer for its rarity value. If the probability is less than 5, it gets 3 points; for probabilities from 5 to 10, it gets 2 points;
If the probability is greater than 10, it gets 1 point. We only have one score for each method of division Hu and Adey, 2002.
2 Score of Test Item
The tests used in this research are paper and pencil tests consist of 20test items. Each multiple choice correct answers are given 1 score and
each incorrect answer was given a score of 0
b Calculation of Gain Score and Normalized Gain
The difference of pretest score andpost-test score is a way to obtain a gain score actual gain. The effect of the treatment is assuming fromthe difference in
pretest scores and the post-test. “Normalized gain calculations are intended to
determ
ine the categories of students‟ achievement improvement.gis the single-
student normalized gain, defined as:” Hake, 2002
g = Gain Gain
max
Reza Taufik Maulana, 2014 NUMBERED HEADS TOGETHER NHT: AN ENDEAVOUR TO IMPROVE STUDE
NT’S SCIENTIFIC CREATIVITY AND MASTERY CONCEPT IN LEARNING GLOBAL WARMING
Universitas Pendidikan Indonesia
| repository.upi.edu
| perpustakaan.upi.edu
g = posttest – pretest 100 – pretest
The effectiveness of Numbered Heads Together model in increasing students‟ scientific creativity and mastery concept in learning global warming
will be seen from the result of the normalized gain that achieved by students during the learning process. The calculation of the normalized gain value and its
classification will use these following equations Hake, 1999:
Normalized gain of each student g defined as following formula:
Description: g
= Normalized gain G
= Actual gain G
max
= Maximum gain possible S
f
= Post-test score S
i
= Pretest score Average of normalized gain g which is formulated as:
Description: g
= Normalized gain G
= Actual gain G
max
= Maximum gain possible S
f
= Average of post-test score S
i
= Average of pretest score
Table 3.9 Interpretation of Normalized Gain Value G
Sf- Si g = =
G max 100 - Si
Reza Taufik Maulana, 2014 NUMBERED HEADS TOGETHER NHT: AN ENDEAVOUR TO IMPROVE STUDE
NT’S SCIENTIFIC CREATIVITY AND MASTERY CONCEPT IN LEARNING GLOBAL WARMING
Universitas Pendidikan Indonesia
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Value g
Classification g 0,7
High 0,7
g 0,3 Medium
g 0,3 Low
Hake, 1999
c Normality and Homogeneity test
Using of parametric statistic has a deal with assumption that each variable in this research that will be analyzed form a normal distribution. If, the data is abnormal,
the homogeneity variant test cannot be done or the parametric technique cannot be used. Meanwhile if the data is normal and homogen, the parametric technique can
be used. Normality test is to know whether the sample comes from population that has normal distribution or not. In this research, Normality test uses statistic test from
SPSS 20, Kolmogorov-Smirnov with significancy
level α is 0,05. When significance value 0,05, H
will be accepted and H will be rejected or denied if
significance value 0,05 The hypotheses are: H
: Sample comes from population that has normal distribution. H
1
: Sample comes from population that has not normal distribution. The homogeneity test is also uses statistic test from SPSS 20, with significance level
α is 0,05. When significance value ≥0,05, the data is considered as homogeny Sarwono, 2012.
1 One Sample T-test
One sample T-test was done to determine whether the class had achieved the standard score after the implementation of NHT represented by the
Posttest Score. T-test requires data which is normal and homogen. In SPSS 20, the test is used One Sample T-Test. If the level of significancy sig
≤ 0.05 H
is rejected.If the level of significancy sig 0.05 H is retained. In testing
Reza Taufik Maulana, 2014 NUMBERED HEADS TOGETHER NHT: AN ENDEAVOUR TO IMPROVE STUDE
NT’S SCIENTIFIC CREATIVITY AND MASTERY CONCEPT IN LEARNING GLOBAL WARMING
Universitas Pendidikan Indonesia
| repository.upi.edu
| perpustakaan.upi.edu
the similarity means is used two-tailes hypotheses, the hypotheses is determined as bellow:
H : Students‟ mastery concept score in learning global warming concept has
achieved the school standard of 75 . H
1
: Students‟ mastery concept score in learning global warming concept less than school standard 75
2. Qualitative Data Analysis
