Table 3.3. The Blueprint of the Interview
RESEARCH QUESTION
CATEGORY INTERVIEW QUESTIONS
How does IPALL
enhance vocational high
school
students‟ vocabulary
learning strategies?
Background experience - Can you tell me how you learned vocabulary
before using IPALL? - Is there any differences between learning
vocabulary before and after using IPALL? - What strategies do you use before?
- What do you think about the strategy?
Action Finding the meaning
of new words - What do you do to find the meaning of the
new words in IPALL? - Can you find another ways to find the
meaning of the new words? - Can you explain and give the examples?
Retaining the words in long term memory
- What do you do to memorize the new words in IPALL?
- Can you tell me different ways you use? - What do you know about the words?
Recalling the words at will
- How do you do to recall the meaning of new words in IPALL?
- Can you mention different way you use? - How do you explain them and give example?
Using the words in spoken or written
- How do you learn to speak or pronounce new words in IPALL?
- How do you learn to write new words? - How do you learn the form of new words and
their inflections? - Can you explain or give example?
Intention - What is your present and future intention in
learning vocabulary by using IPALL? - Can you explain further?
- What do you expect in learning vocabulary by using IPALL?
- ......?
....? = questions possibly emerge during the interview
4. Data Analysis
The first step of analyzing the data was by processing the data gathered from the questionnaires. The data from the questionnaire provided both
quantitative and qualitative. Therefore, the analysis was from the close-ended items and the open-ended items. The close-ended items were the for Likert scale.
The scale was consist of four scale. Then, the scale 4, 3, 2, 1 were converted into - 2, -1, 1, -2. The converted items were tabulated using Excel 2007. After that, the
researcher calculated the result score and percentage for each items. In calculating the close-ended questionnaire, the researcher found the ideal mean Mi and ideal
standard deviation SDi. The ideal mean was the adiition of the highest ideal score and the lowest ideal score divided by two. The ideal standard deviation was
subtractting the highest ideal score from the lowest ideal score, and then divided by five. The formulas and calculations were presented as follows
Ideal Mean Mi = ½ maximum score + minimum score
= ½ 2+ -2 = 0
Ideal Standard Deviation SDi =
15 maximum score-minimum score = 15 2
– -2 = 0.8
Figure 3.3. Ideal Mean and Ideal Standard Deviation Sudijono, 2009
After the ideal mean Mi and ideal standard deviation SDi are calculated, the mean criteria can be formulated. The formulation is adapted from
Sudijono‟s quantitative data conversion as shown in the following figure:
Very High Mi + 1.5 SDi
High Mi + 0.5 SDi
Fair Mi
– 0.5 SDi Low
Mi – 1.5 SDi
Very Low
Figure 3.4 The Mean Criteria Formulation Sudijono, 2009: 175
Since this research used 4 Likert scale. There was no „fair‟ criteria. The researcher adjusted Sudijono‟s mean criteria formulation into the mean criteria to
this research. Thus, the mean criteria can be seen in the following Table 3.4.
Table 3.4 The Mean Criteria Sudijono, 2009: 175
Mi + 1.5 SDi | = | 0 + 1.5 . 0.8 | = | 1.2 Mi + 0.5 SDi | = | 0 + 0.5. 0.8 | = | 0.4
Mi - 0.5 SDi | = | 0 – 0.5 .0.8 | = | -0.4
Mi – 1.5 SDi | = | 0 – 1.5 . 0.8 | = | -1.2
The mean criteria above were used to interpret the mean of every indicator in order to know the students‟ vocabulary learning strategies adopted in IPALL.
In other words, the researcher would be informed the most and the least strategies used by students in learning vocabulary adopted in IPALL. The very high score
indicated that the indicators received the most strategies used by the students. The range was from 1.2
– 2. In line with it, the high score showed that the students used the indicators. The range was from 0.4
– 1.1. Next, the low score pointed out that the respondents did not use the strategies. The range was from -0.4
– 1.0. The last, the very low score specifies that the respondents did not strongly use the
indicators. The range was from -2 – -0.3.
The second step was done by transcribing the recorded interview and then classified the responses into four concepts of the theories used. After gaining the
complete information, the researcher analyzed and interpreted the statements from the participants according to vocabulary learning strategies and principles of
CALL. Then, the description of the qualitative data was built. Next, the open- ended items were classified and categorized.
Score range Criteria
1.2 – 2
Very High 0.4
– 1.1 High
-0.4 – 1.0
Low -2
– -0.3 Very Low
To classify open-ended questionnaire and interview result, the researcher made coding. It is aimed to make the statements are easy to identify and analyze
later on. For open-ended questionnaire, the researcher used Saldana‟s coding
system for qualitative research. The formula was number of appendix_open ended AB_participant number_ page number.
Table 3.5 Coding System for Open-Ended Questionnaire Coding
Meaning
App4 Appendix 4
OEA Open-Ended A
32 Participant number
182 Page number
Then, for interview result, the researchers made students‟ coding first. The
formula was name, student’s code, and statement’s number. The example was
shown in table 3.6.
Table 3.6 Coding for Participant Number of Interview Coding
Meaning
LA1 LA2 etc...
Levyn, Student A, Statement 1 Levyn, Student A, Statement 2 dst..
AD 1 AD 2 etc...
Adenzha, Statement 1 Adenzha, Statement 2 dst..
LB 1 LB 2 etc...
Levyn, Student B, Statement 1 Levyn, Student B, Statement 2 dst..
AL 1 AL2 etc...
Alicia, Statement 1 Alicia, Statement 2 dst..
LC1 LC2 etc...
Levyn, Student C, Statement 1 Levyn, Student C, Statement 2 dst..
R 1 R 2 etc...
Rinda, Statement 1 Rinda, Statement 2 dst..
LD 1 LD 2 etc...
Levyn, Student D, Statement 1 Levyn, Student D, Statement 2 dst..
W 1 W 2 etc...
Wenna, Statement 1 Wenna, Statement 2 dst..
After that, to classify interview result, the researcher also used Saldana‟s coding system for qualitative research. The formula was number of appendix_
interview123_participant number_ page number.
Table 3.7 Coding System for Interview Coding
Meaning
App10 Appendix 10
Int1 Interview 1
AD1 Adenzha, Statement 1
182 Page number
Since this study was a survey research. The researcher had to check the pre-requisites tests before analysing the data. To check the normality, the
researcher used Kolmogorov-Smirnov test. Then, the result was the data were not normal. Therefore, the researcher had to use non-paramateric statistical technique
later. To check the homogeneity, the researcher used Levene test. Homogeneity was used for checking the homogeneity of variance. The variance was
systematically in the same variance. The variance was the standard deviation between score and the average. The result showed that the data were
homogeneous. In this study, the researcher had used three statistical techniques. Since this
study was a survey research, the first statistical technnique was descriptive statistics. It was used to discover the mean, median, standard deviation, minimum,
maximum and range of students‟ strategies and scores. As the triangulation, the researcher
used experimental research to know students‟ before, after and gain scores. Therefore, the second was Wilcoxon test. Wilcoxon test was used since
the data were not normal. It was to measure the before and after score in the same subjects.
