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CHAPTER III
RESEARCH METHOD
This chapter covers the description of research design, population and sampling, variables, data collection method and instrument, validity and reliability, normality test, and data analysis. A. Research Design The design of the research was correlational research. According to Ary (2006:27) stated Correlational research gathers data from individuals on two or more variables and then seeks to determine if the variables are related (correlated). Correlation means the extent to which the two variables vary directly (positive correlation) or inversely (negative correlation). The degree of relationship is expressed as a numeric index called the coeffi cient of correlation. Meanwhile, Fraenkel and Wallen ( 2006 :335) stated as follows: Correlational research, like causal-comparative research, is an example of what is sometimes called associational research. In associational research, the relationships among two or more variables are studied without any attempt to influence them. In their simplest form, correlational studies investigate the possibility of relationships between only two variables, although investigations of more than two variables are common. In contrast to experimental research, however, there is no manipulation of variables in correlational research. Correlational research is also sometimes referred to as a form of descriptive research because it describes an existing relationship between variables. When a correlation was found to exist between two variables, it means that scores within a certain range on one variable were associated
with scores within a certain range on the other variable. You will recall that a positive correlation means high scores on one variable tend to be associated with high scores on the other variable, while low scores on one were associated with low scores on the other. A negative correlation, on the other hand, means high scores on one variable are associated with low scores on the other variable, and low scores on one were associated with high scores on the other. If the coefficient had a positive sign, this means that as one variable increases, the other also increases. A negative coeffi cient indicates that as one variable increases, the other decreases. Ary (2006: 350 ) states as follows: The size of the correlation coefficient indicates the strength of the relationship between the variables. The coeffi cient can range in value from +1.00 (indicating a perfect positive relationship) through 0 (indicating no relationship) to −1.00 (indicating a perfect negative relationship). A perfect positive relationship means that for every z - score unit increase in one variable there is an identical z - score unit increase in the other. A perfect negative relationship indicates that for every unit increase in one variable there is an identical unit decrease in the other. Few variables ever show perfect correlation, especially in relating human characteristics. The basic design for correlational research was straightforward. First, the researcher specified the problem by asking a question about the relationship between the variables of interest. The variables selected for investigation were generally based on a theory, previous research, or the researcher’s observations (Ary, 2006:352). The researcher specified his or her population of interest and draws a purposive sample from that population. Finally, the researcher collected the quantitative data on the
were connected indirectly or we can call them as a symmetrical associative correlation. D. Data Collection Method and Instrument In this research, the researcher used some method of collecting data to get the needed data by using the following instrument, they were questionnaire and test. 1. Questionnaire According to Arikunto(201 0 :19 4 ) stated that “Questionnaire is a number of letterally questions that is used to get the information from the respondent in term of personality/self-report or about the thing she or he knows.” The researcher was given the questionnaire to student. Closed questionnaire serves the answer, thus the respondent just needed to choose one of the available option. In this research, the researcher used closed questionnaire in which the questions in the questionnaire was written in Indonesian language. It conducted in order to make easier the respondents to answer the questions. The questionnaire was about 20 questions in form of multiple choice. The researcher asked students to choose one option that they wanted. The researcher provided (5 ) five options for each question. A,B,C,D, and E. To make easy to determine the interval score of the questionnaire set, all answer of the questionnaire would be changed become score by using Likert scale. According to Ary (2006:209) stated as follow:
“Likert scale assesses attitudes toward a topic by presenting a set of statements about the topic and asking respondents to indicate for each whether they strongly agree, agree, are undecided, disagree, or strongly disagree. The various agree - disagree responses are assigned a numeric value, and the total scale score is found by summing the numeric responses given to each item. This total score assesses the individual’s attitude toward the topic.” Based on the Likert scale, the score of each student would be marked as follows: a. Score 5 for A, b. Score 4 for B, c. Score 3 for C, d. Score 2 for D, and e. Score 1 for E Every choice indicated that if respondent chose option “A” the students’ interest in watching English movie was very good, B indicated the students’ interest in watching English movie was good, C indicated the students’ interest in watching English movie was fair, D indicated the students’ interest in watching English movie was poor, and E indicated the students’ interest in watching English movie was very poor. Finally the total scores of students’ answer in questionnaire would present their interest in watching english movie. Based on standard score above, the highest score of the questionnaire is 100 and the lowest score is
Table 3.1 Scoring rubric for speaking Score Criteria Fluency 1 Repeats words and phrases 2 Speaks in single word utterances and short patterns 3 Speaks hesitantly because of rephrasing and searching for words 4 Speaks with near native fluency; any hesitation do not interfere with communication 5 Speaks fluently Structure 1 Use basic structures with frequent errors 2 Use predominantly presentence verbs, demonstrates errors of omissions (leaves words out, word endings off) 3 Uses some complex sentenses, applies rules of grammar but lacks control of irregullar forms (e.g., runned, mans, not never, more higher) 4 Uses a variety of structures with occasional gramatical errors 5 Masters a variety of gramatical structures Vocabulary 1 Uses few vocabulary inappropriately 2 Uses limited vocabulary 3 Uses adequate vocabulary; some word usage irregularities 4 Uses varied vocabulary 5 Uses extensive vocabulary but may lag behind native- speaking peers Pronunciation 1 Almost all pronunciation seriuosly influenced by mother tongue 2 Pronunciation is influenced by the mother tongue but only a few serious phonological errors 3 Pronunciation is still moderately influenced by the mother tongue but no serious phonological errors 4 Pronunciation is slightly influenced by the mother tongue but most utterances are correct 5 Pronunciation is only very slightly influenced by the mother tongue To asses the speaking ability, the researcher used scoring table and students’ clasification see Table 3.2 and Table 3.
Table 3.2Scoring table Name of Students Score of the students’ speaking ability for each criteria Fluency Structure Vocabulary Pronunciation To make easy for reader to understand the whole aspect that was measured, the researcher separated the score of speaking based on each aspect or criteria. The maximal score for each criteria was 5 points and the minimal score was 1. Table 3.3 The students’ classification No. Total Score Qualification
- 0 - 20 Very poor
- 21 - 40 Poor
- 41 - 60 Enough
- 61 - 80 Good
- 81 - 100 Very Good To make easy for the reader to interpret whether the speaking achievement was good or not. The researcher separated the qualification of students’ speaking achievement into 5 qualification. Students who got 0- 20 were very poor, students who got 21-40 were poor, students who got 41 - 60 were enough, students who got 61- 80 were good, and students who got 81-100 were very good. E. Validity and Reliability Sugiyono and wibowo (in Sujianto 2006 : 94 ) states “ the validity of instrument is instrument that is used to obtain the data that is credible and it can measure what are going to mesure. The reliability of instrument
Triton (in Sujianto 2009:97) state “ if the scale grouped by 5 class with the same range, jika skala itu dikelompokkan ke dalam 5 kelas dengan reng yang sama, so the consistency of can be interpreted as follows:” Table 3. 4 Cronbach scale Cronbach values Interpretations 0,00 – 0,20 Less reliable 0,21 – 0,40 Rather reliable 0,4 1 – 0,60 Quite reliable 0,61 – 0,80 Reliable 0,81 – 1,00 Very reliable The instrument that had value between 0,00-0,20 were less reliable, the instrument that had value between 0,21-0,40 were rather reliable, the instrument that had value between 0,41-0, 60 were quite reliable, the instrument that had value between 0, 61 - 0, 8 0 were reliable, and the instrument that had value between 0,81-0,100 were very reliable. Before being distributed to the sample, the instruments were trying out to the other class to get the reliability. From the answer of students’ response in questionnaire the researcher then analyzed using reliability test based on Cronbach’s Alpha. The result of reliability test is: Table 3.5. Reliability statistics
Reliability Statistics Cronbach's Alpha N of Items .821 20 From the data reliability statistics (see Table 3.5) shows that the Cronbach Alpha reliability of the instrument was 0,821. Based on the Cronbach scale in table 3.4 it lies on the cronbach value between 0,81- 1,00. So, it can be said that the instrument was very reliable. F. Normality test Sujianto (2006:77) states that normality testing is test to measure whether the data have normal distribution so it can be used in parametric statistic. Based on the definition above, the purpose of the conducting normality test was to know whether a certain variable normal or not. The data that was normal means the distribution data were normal was one of the condition to conduct parametric test. For the data that abnormal should analyze by using non-parametric test. Santoso(2006), normality test data is usual thing that is conducted before statistics method are applied. AccordingTo know wheteher the distribution was normal or not, can be known from:
- Nugroho (in Sujianto 2006: 78 ) states “ the normality of the data can be seen from skewness and P-P Plots.
students’ interest in watching english movie was 46,97 whereas the mean of students’ speaking test was 44,25. The median of students’ interest in watching english movie was 4 7 whereas the median of students’ speaking test was 45. The mode of students’ interest in watching english movie was 43 whereas the mode of students’ speaking test was 30. The range of students’ interest in watching english movie was 28 whereas the mean of students’ speaking test was
- The minimum score of students’ interest in watching english movie was 33 whereas the minimum of students’ speaking test was 20. The maximum score of students’ interest in watching english movie was 61 whereas the maximum score of students’ speaking test was 75. And the total score both students’ interest in watching english movie and students’ speaking test were 1268 and 1195. Table 3. 7 Normality Testing One-Sample Kolmogorov-Smirnov Test minat movie speaking test N 27 27 Normal Parametersa^ Mean 46.9630 44. Std. Deviation 7.47036 14. Most Extreme Differences Absolute .072. Positive .072. Negative - .068 -. Kolmogorov-Smirnov Z .377. Asymp. Sig. (2-tailed) .999. a. Test distribution is Normal.
Based on the table 3. It can be seen that the score Asymp. Sig. (2- tailed) in variable x (interest in english movie) was 0,999 and the score Asymp. Sig. (2-tailed) in variable y (speaking test) was 0,613. Both of them were larger that significant value= 0,05. So it can be concluded that both variable x and variable y were normal While the result of normality test can be seen from P-P Plot (see graphic 3.1). Figure 3. 1 P-P Plot of interest in English movie Based on the Figure 3.1. The data in variable that was used called normal or closely normal. A certain variable were normal if the picture of
G. Data Analysis Because the purpose of the research was to measure the correlation between interest on watching english movie and speaking of second year students, the researcher used statistics method. In this research all the data were gained from the result of questionnaire and the test in the form of number. All the data analyzed quantitatively. Since this research was to know the correlation between two variables, the researcher applied bivariate correlation analysis by using pearson product moment in SPSS 16.
