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Technique of Collecting the Data

Dalam dokumen OF MAN 2 KAMPAR (Halaman 62-67)

CHAPTER III RESEARCH METHOD

E. Technique of Collecting the Data

Collecting data is one of the most crucial parts in a research.

Pertaining to Arikunto (2013) instrument of the research as a tool or facility that the researcher used to collect data in order to make the research process easier and got the better result, accurate, complete, methodical, and easy to evaluate. In order to got the data which were needed to complete this research, the researcher used the test. The test did twice, the first was pre-test that gave before treatment, and the second was

post-test that gave after treatment intended to obtained students‟ writing ability in descriptive text at the tenth grade of MAN 2 Kampar.

1. Test

Test used to written test by using Quizizz on students‟ writing descriptive text. Pertaining to Brown (2007, p.3), test means that a method of measuring of a person‟s ability, knowledge, or performance in given domain. To obtain the students‟ writing ability in descriptive text by using quizizz, the writer gave the test.

a. Pre-test

Pre-test gave before treatment. According to Creswell (2012) pre-test provide a measure on some attribute or characteristic that you asses for participant in an experimental before they receive the treatment. Pre-test used to collect the data about witing descriptive text using quizizz of the students‟ before giving treatment to the experimental class and before giving no treatment to the control class. The test gave to class X MIA 1 as control class and class X MIA 2 as experiment class.

b. Post-test

Post test gave after teaching several time. It gave to both of the class. Post test to collect the data about writing ability in descriptive text using quizizz of the students‟ after giving treatment to the experimental class and after giving no treatment to the control class. According to Gay (2012) post test score compared to

determine the effectiveness of the treatment. So that score of test compared to know the effect of the treatment. The test gave to class X MIA 1 as control class and class X MIA 2 as experiment class.

Table III. 4

Blueprint of Pre-Test and Post Test

Test Instruction Score

1. pre-test

Please write your full name, class,

and date! This score as judge by a rubric

consist of content, organization, grammar, vocabulary, and mechanics in general statment and part description.

Please create a descriptive text that decribe about yourself. You describe detaily in 3-5 paragraphs and you have 30 minutes to finish this task. Good luck my students!

2. post-test

Please write your full name, class, and date!

This score as judge by a rubric.

consist of content, organization, grammar, vocabulary, and mechanics in general statment and part description.

Please create a descriptive text that decribe about yourself You describe detaily in 3-5 paragraphs.

Describe detail and you have 40 minutes to finish this task. Good luck my students!

Table III. 5

The rubric for Assessing writing descriptive text (Brown 2007)

Aspect Score Performance Descriptive Weighting

4 The topic is complete and clear and the details are relating to the topic

Content (C) 30% 3X

Topic 3

The topic is complete and clear but the details are almost relating to the topic

Detail 2

The topic is complete and clear but the details are not relating to the topic

1 The topic is not clear and the details are not relating to the topic

Organization (O) 20 %

4

Identification is complete and descriptions are arranged with

proper Connectives 2X

Identificatio

n 3

Identification is almost complete and descriptions are arranged with almost proper connectives

Description 2 Identification is not complete

1

Identification is not complete and descriptions are arranged with misuse of Connectives

Grammar (G) 20%

4 Very few grammatical or agreement

Inaccuracies 2X

3

Few grammatical or agreement inaccuracies but not effect on meaning

2 Numerous grammatical or

agreement Inaccuracies

1 Frequent grammatical or agreement Inaccuracies

Vocabulary (V) 15%

4 Effective choice of words forms 1,5%

3

Few grammatical or agreement inaccuracies but not effect on meaning

2 Limited range confusing words and word Forms

1 Very poor knowledge or words, words form, and not understandable

Mechanics (M) 15%

4 It uses correct spelling, punctuation

and capitalization 1,5%

3 It has occasional errors of spelling, punctuation and capitalization 2 It has frequent errors of spelling,

punctuation and capitalization 1 It has dominated by errors spelling

punctuation and capitalization.

Score = 3C + 2O + 2G + 1.5V + 1.5M 5 x 10

= 400/5

= 80

Table III.6

The classification of Students’ Score Likert scale (Harmer 2006, 24-25)

Score Categories 80 – 100 Very good

66 – 79 Good 56 – 65 Enough 40 – 45 Less 30 – 39 Fail

In term of the normality test of the data, it was analyzed by using Shapiro-Wilk technique with SPSS 22 version. The SPSS result of Shapiro- Wilk test can be interpreted as follows:

Ho : The data are normally distributed Ha : The data are abnormally distributed Testing Criteria:

If the probability (sig) > 0.05 Ho is accepted If the probability (sig) < 0.05 Ho is rejected

After knowing that the data were normally distributed the researcher need independent sample T-test analysis in order to know whether or not there is significant difference between students‟ writing ability without and by using the Write Pair Square technique of descriptive

texts. Furthermore, the SPSS 23 result of Independent Sample T-test can be interpreted as follows:

Hypothesis:

Ho : Variance population was identical Hypothesis:

Ha : Variance population was not identical Testing Criteria:

If the value in Sig. (2-tailed) ≤ 0.05, then Ha is accepted.

If the value in Sig. (2-tailed) ≥ 0.05, then Ho is accepted.

Furthermore, in order to find out whether or not there is significant effect of using the Write Pair Square Technique on the students‟ writing ability of descriptive texts, the researcher needed to provide the effect size or (Eta squared) by using SPSS 23 software.

Gain Score Hake,R.R, (1999)

Percentace Category

< 40 No effective

40 – 50 Less effective 56 – 75 Enough effective

> 76 Effective

Dalam dokumen OF MAN 2 KAMPAR (Halaman 62-67)

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