ERROR ANALYSIS IN SUBJET-VERB AGREEMENT FOUND IN STUDENTS’ WRITING AT LANGUAGE TRAINING CENTER OF UNIVERSITAS MUHAMMADIYAH YOGYAKARTA G. BAB III ANIKO
24
Chapter Three
Methodology
In this chapter, the researcher explain the methodology in conducting this
research. This research aims at knowing error types and calculating the subjectverb agreement error in essay writing class at the LTC of UMY. These chapter
presents research design, setting and participants of the research, research
instrument and data collection method. It also explains the data analysis
technique.
Research Design
Approach. This study employed a quantitative research. Furthermore, this
study adopted a descriptive statistic to report the data which have been analyzed
and collected. William (2007) asserted that quantitative research explains
phenomena using the collecting numerical data which are analyzed using
mathematical models as the methodology of data analysis exactly in particular
statistics. Descriptive statistic was employed to describe the result of the analysis
using a frequencies and percentage stated by Cohen, Manion and Morrison
(2011). Quantitative research is suitable for this research because in this research
the researcher examined not only subject-verb agreement error but also the
frequency of error when students used subject-verb agreement.
Design. The researcher used error analysis as the design of this research.
According to Corder (1981), error analysis is a part of methodology of
investigating the language learning process. This research studied error when the
students used subject-verb agreement in their writing. Brown (2010) stated that
25
error analysis is a process of identifying, analyzing, and classifying the students’
error. Then, from the error analysis the teacher would know what error that
produced by students when using subject-verb agreement.
Setting and Participant of the Research
Setting. The research was conducted at the Language Training Center
(LTC) of Universitas Muhammadiyah Yogyakarta (UMY). LTC of UMY was a
place where the students of UMY could enrich their own skill in learning foreign
languages especially English. The specific place for this research is essay writing
class at LTC of UMY. The other reason for picked LTC of UMY as the setting
was because the accessibility of the researcher through these place. The researcher
was still being a students in UMY, it was much easier to gather the data.
Also, the researcher chose essay writing class because she made sure that,
in essay writing class, the students learned how to make a good writing, how to
make a good sentence, and how to make a good paragraph. The researcher only
took one of the essay assignments of essay writing class. There are mid-term
essays of essay writing class assessment. This research was conducted from
March to May 2017.
Population. The population of the research was IR students who took
essay writing class at LTC of UMY batch 2016. The population were 246. Based
on Creswell (2012), population is a group of individuals who possess one
characteristic that distinguishes them from other groups. The reason for choosing
IR major as population was to enrich the total number of finding. This research
would measure the English proficiency in non-English department. Based on the
26
researcher experienced, if non- English department compared each other, IR
major has highly adequate competencies in English. It is supported by fact that the
majority or more than 80% member of Unit Kerja Mahasiswa (UKM) Bahasa
Inggris in UMY is IR students. The researher was a member of UKM Bahasa
Inggris since 2013- 2016. Becoming a member of UKM Bahasa Inggris is not
easy, there is an open reqruitment with some test in English first. Students who
passed the English test with committee standardised then finally become the
member of UKM Bahasa Inggris. The researcher wanted to proved the IR
competencies in writing.
The researcher chose batch 2016 as the sample because they were in the
first year. They were freshmen who learn English for one and half semester. The
researcher was sure that they had already learned subject-verb agreement as how
to make a good sentence. Thus, hopefully it will prevent them in making subjectverb agreement error later because the knowledge of subject-verb agreement as
the basic to learn English in the future – to prepare them in produce a good
writing.
Hence, the sampling technique was random sampling. The researcher used
Slovin’s formula (David, Dan & Chris,2007) for calculate the number of sample.
Slovin’s formula is a random sampling technique formula to estimate sampling
size. It used to calculate the sample size (n) given the population size (N) and a
margin of error (e). It is computed as n = N / (1=Ne2).
27
Whereas :
n
=
Number of samples
N
=
Total puopulation
e
=
Error margin
The researcher figured out a confidence level of 95 percent, so the error margin is
0.05. This error margin is used for social study like this research. So, it would be
n
=
N / (1+ Ne2)
=
246 / (1+246 x 0.052)
=
71.5
72
From the calcutation, it conclude that the minimum samples for this research was
72 essays from IR students batch 2016 who took an essay writing class at LTC of
UMY. Moreover, for enrich the finding the researcher used 99 essay documents as
sample for this research.
Research Instrument
To identify the errors made by students in the use of subject-verb
agreement, the researcher used documents as a data instrument in this research.
The documents were essays from IR students batch 2016 who took an essay
writing class at LTC of UMY. Before having the documents, the researcher
should meet the teacher who taught IR essay writing class batch 2016 at LTC of
UMY. The researcher discuss with the teacher about essay documents that needed
in order to support the research. Then, from the discussion found the essay
documents were from mid-term assesstment essay writing class of IR students
batch 2016 at LTC of UMY.
28
Data Collection Method
The purpose of this study is to investigate subject-verb agreement error in
the students’ writing at LTC of UMY. The method used by the researcher to
collect the data was document analysis. The researcher collected students’
midterm essay writing assessment, and the researcher did document analysis on
students’ essay writing. In beginning, the researcher made a permission letter
from Language Education Faculty for the equipment in gathering the data at the
LTC of UMY.
The researcher need to determined the data or called language corpus
because the scope of the research was on it. The data were collected from 100 of
mid-term assessment essay writing class which were essay documents of IR batch
2016. But, the fact only 99 essay documents which available to be a sample of this
research because 1 essay document could not be download by the researcher. One
students submited his essays in his blog which the address could not be access by
researcher. So, the total document that researcher gathered only 99 essays
documents.
Therefore, the teacher did not give a special topic, so the students have
their freedom to choose the topic for the essay. It implied from the title of the
essay it self. The essay document gathered from three different teacher that taught
essay writing class batch 2016. The researcher copied the students’ essay with
permission from the teacher. The data were in form of hardcopy, so the researcher
should firstly change into softfile. Some data could be easy transfered into softfile
by scanning it, and some others need to type.
29
Moreover, the researcher checked the validity of the document. The
researcher gave the document back to the students and asked whether or not the
documents belonged to them. That was how the researcher conducted member
checking to ensure the validity. After all data already verified, the researcher
change the format of softfile documents into plain text. It must save in plain text
format because it was the format for Ant Concordance. Then, that is how the
researcher collecting the data before analyze later.
Data Analysis Technique
After collecting the data, the next step was analyzing the data gained from
the text. Data analysis can be defined as the process of bringing the order,
structure, and interpretation to the mass of collected data (Sugiyono, 2010 as cited
in Adib, 2012). Then, there were several steps that should be followed to conduct
error analysis. Adapted from Gass and Selingker (2001) as cited in Agustina
(2016), there are six steps to conducted error analysis. They were collecting the
data, identifying the error, classifying the error, explaining the errors, analyzing
sources, and remediation. The researcher only used step one until step four which
were collecting the data, identifying the error, classifying the error, and explaining
the error. The researcher did not analyze the source of error because the data
source and to whom the data belong were clear. Then, the remediation was not
included in this study because this research only wanted to investigate the subjectverb agreement error that found in essay writing class at LTC of UMY. However,
the researcher after analyzing, also did a step which is quantifying the error in
order to know the number of error that produced by students’ in their essays.
30
Furthermore, here was how the research was conducted. Collecting the
data means that the researcher gathered the written data and sort them using seven
keywords. The researcher used concordance as a tool to help to short the data.
According to Seale (2004), “concordance is a computer software which will analyze
texts in number of ways, including producing keyword lists and word frequencies,
identifying main ideas, analyzing patterns of word use, and comparing vocabulary
between texts” (p.369). Concordance is software related to linguistic. It is because
concordance is able to shorting text, identifying main idea of the text, analyzing
pattern of word use and comparing vocabulary between texts. The data is in form of
essays which consist paragraph, and paragraph consist some sentences. The
researcher is focus on the level of sentences. The sentences that researcher use
later is the sentences which the subject is the keywords.
The researcher used Ant Concordance as a tool to help in shorting the text
of the students’ essays. The first step of data analysis was to change the hard file
document into soft file document. Second, the researcher changed the format
Microsoft Word into plain text. Third, the researcher inputted the plain text into
Ant Concordance. Fourth, the researcher used the keyword (I, we, you, they, she,
he, and it) to short the sentences. Fifth, the researcher copied the sentences
containing those seven keywords into Microsoft Excel by naming every sheet
with the each keywords. From the Ant Concordance programs, the total sentences
obtained contain the keywords were 2,581 sentences.
Identifying the error means that the researcher separated the subject-verb
agreement error from the correct ones. Identifying the error from the data which
already shorted with Ant Concordance or called as corpus. From the corpus data,
31
the sentences later identified by using the grammatical features involving the
subject-verb agreement, such as verb form, auxiliary verb and modals. The Ant
Concordance program used only for helping the researcher in shorting the
sentences using a certain keywords. The one who classified and identified the
sentences later was the researcher itself. The researcher identified which correct
sentences and error sentences. Then, the researcher would be focus on the error
sentences only.
Classifying the error means that the researcher classified the subject-verb
agreement error into the four error types such as omissions, additions,
misformation and misordering. The researcher would clasiffy the error into four
classification which were four types of error. Accoding to Ellis (2003), there were
four error types, addition, misformation, misordering and omission.
Explaining the error means that the researcher explained the reason why
those error sentences belongs to each error type. At last, quantifying the error
means counting the amount of error that occurs. Then the final step was counting
the percentage of subject-verb agreement error production.
To count the subject-verb agreement error production made by students,
the researcher used a formula according Bluman (2004):
F
P=
x 100%
N
Which:
P = percentage of subject-verb agreement errors
F = frequency of subject-verb agremeent errors
N= number of sentences containing seven keywords
32
The researcher classified the level based on Sugiono (2010) written as follows:
66%-100% of errors were classified as high.
36%- 65% of errors were classified as middle.
0%- 35% of errors were classified as low.
Chapter Three
Methodology
In this chapter, the researcher explain the methodology in conducting this
research. This research aims at knowing error types and calculating the subjectverb agreement error in essay writing class at the LTC of UMY. These chapter
presents research design, setting and participants of the research, research
instrument and data collection method. It also explains the data analysis
technique.
Research Design
Approach. This study employed a quantitative research. Furthermore, this
study adopted a descriptive statistic to report the data which have been analyzed
and collected. William (2007) asserted that quantitative research explains
phenomena using the collecting numerical data which are analyzed using
mathematical models as the methodology of data analysis exactly in particular
statistics. Descriptive statistic was employed to describe the result of the analysis
using a frequencies and percentage stated by Cohen, Manion and Morrison
(2011). Quantitative research is suitable for this research because in this research
the researcher examined not only subject-verb agreement error but also the
frequency of error when students used subject-verb agreement.
Design. The researcher used error analysis as the design of this research.
According to Corder (1981), error analysis is a part of methodology of
investigating the language learning process. This research studied error when the
students used subject-verb agreement in their writing. Brown (2010) stated that
25
error analysis is a process of identifying, analyzing, and classifying the students’
error. Then, from the error analysis the teacher would know what error that
produced by students when using subject-verb agreement.
Setting and Participant of the Research
Setting. The research was conducted at the Language Training Center
(LTC) of Universitas Muhammadiyah Yogyakarta (UMY). LTC of UMY was a
place where the students of UMY could enrich their own skill in learning foreign
languages especially English. The specific place for this research is essay writing
class at LTC of UMY. The other reason for picked LTC of UMY as the setting
was because the accessibility of the researcher through these place. The researcher
was still being a students in UMY, it was much easier to gather the data.
Also, the researcher chose essay writing class because she made sure that,
in essay writing class, the students learned how to make a good writing, how to
make a good sentence, and how to make a good paragraph. The researcher only
took one of the essay assignments of essay writing class. There are mid-term
essays of essay writing class assessment. This research was conducted from
March to May 2017.
Population. The population of the research was IR students who took
essay writing class at LTC of UMY batch 2016. The population were 246. Based
on Creswell (2012), population is a group of individuals who possess one
characteristic that distinguishes them from other groups. The reason for choosing
IR major as population was to enrich the total number of finding. This research
would measure the English proficiency in non-English department. Based on the
26
researcher experienced, if non- English department compared each other, IR
major has highly adequate competencies in English. It is supported by fact that the
majority or more than 80% member of Unit Kerja Mahasiswa (UKM) Bahasa
Inggris in UMY is IR students. The researher was a member of UKM Bahasa
Inggris since 2013- 2016. Becoming a member of UKM Bahasa Inggris is not
easy, there is an open reqruitment with some test in English first. Students who
passed the English test with committee standardised then finally become the
member of UKM Bahasa Inggris. The researcher wanted to proved the IR
competencies in writing.
The researcher chose batch 2016 as the sample because they were in the
first year. They were freshmen who learn English for one and half semester. The
researcher was sure that they had already learned subject-verb agreement as how
to make a good sentence. Thus, hopefully it will prevent them in making subjectverb agreement error later because the knowledge of subject-verb agreement as
the basic to learn English in the future – to prepare them in produce a good
writing.
Hence, the sampling technique was random sampling. The researcher used
Slovin’s formula (David, Dan & Chris,2007) for calculate the number of sample.
Slovin’s formula is a random sampling technique formula to estimate sampling
size. It used to calculate the sample size (n) given the population size (N) and a
margin of error (e). It is computed as n = N / (1=Ne2).
27
Whereas :
n
=
Number of samples
N
=
Total puopulation
e
=
Error margin
The researcher figured out a confidence level of 95 percent, so the error margin is
0.05. This error margin is used for social study like this research. So, it would be
n
=
N / (1+ Ne2)
=
246 / (1+246 x 0.052)
=
71.5
72
From the calcutation, it conclude that the minimum samples for this research was
72 essays from IR students batch 2016 who took an essay writing class at LTC of
UMY. Moreover, for enrich the finding the researcher used 99 essay documents as
sample for this research.
Research Instrument
To identify the errors made by students in the use of subject-verb
agreement, the researcher used documents as a data instrument in this research.
The documents were essays from IR students batch 2016 who took an essay
writing class at LTC of UMY. Before having the documents, the researcher
should meet the teacher who taught IR essay writing class batch 2016 at LTC of
UMY. The researcher discuss with the teacher about essay documents that needed
in order to support the research. Then, from the discussion found the essay
documents were from mid-term assesstment essay writing class of IR students
batch 2016 at LTC of UMY.
28
Data Collection Method
The purpose of this study is to investigate subject-verb agreement error in
the students’ writing at LTC of UMY. The method used by the researcher to
collect the data was document analysis. The researcher collected students’
midterm essay writing assessment, and the researcher did document analysis on
students’ essay writing. In beginning, the researcher made a permission letter
from Language Education Faculty for the equipment in gathering the data at the
LTC of UMY.
The researcher need to determined the data or called language corpus
because the scope of the research was on it. The data were collected from 100 of
mid-term assessment essay writing class which were essay documents of IR batch
2016. But, the fact only 99 essay documents which available to be a sample of this
research because 1 essay document could not be download by the researcher. One
students submited his essays in his blog which the address could not be access by
researcher. So, the total document that researcher gathered only 99 essays
documents.
Therefore, the teacher did not give a special topic, so the students have
their freedom to choose the topic for the essay. It implied from the title of the
essay it self. The essay document gathered from three different teacher that taught
essay writing class batch 2016. The researcher copied the students’ essay with
permission from the teacher. The data were in form of hardcopy, so the researcher
should firstly change into softfile. Some data could be easy transfered into softfile
by scanning it, and some others need to type.
29
Moreover, the researcher checked the validity of the document. The
researcher gave the document back to the students and asked whether or not the
documents belonged to them. That was how the researcher conducted member
checking to ensure the validity. After all data already verified, the researcher
change the format of softfile documents into plain text. It must save in plain text
format because it was the format for Ant Concordance. Then, that is how the
researcher collecting the data before analyze later.
Data Analysis Technique
After collecting the data, the next step was analyzing the data gained from
the text. Data analysis can be defined as the process of bringing the order,
structure, and interpretation to the mass of collected data (Sugiyono, 2010 as cited
in Adib, 2012). Then, there were several steps that should be followed to conduct
error analysis. Adapted from Gass and Selingker (2001) as cited in Agustina
(2016), there are six steps to conducted error analysis. They were collecting the
data, identifying the error, classifying the error, explaining the errors, analyzing
sources, and remediation. The researcher only used step one until step four which
were collecting the data, identifying the error, classifying the error, and explaining
the error. The researcher did not analyze the source of error because the data
source and to whom the data belong were clear. Then, the remediation was not
included in this study because this research only wanted to investigate the subjectverb agreement error that found in essay writing class at LTC of UMY. However,
the researcher after analyzing, also did a step which is quantifying the error in
order to know the number of error that produced by students’ in their essays.
30
Furthermore, here was how the research was conducted. Collecting the
data means that the researcher gathered the written data and sort them using seven
keywords. The researcher used concordance as a tool to help to short the data.
According to Seale (2004), “concordance is a computer software which will analyze
texts in number of ways, including producing keyword lists and word frequencies,
identifying main ideas, analyzing patterns of word use, and comparing vocabulary
between texts” (p.369). Concordance is software related to linguistic. It is because
concordance is able to shorting text, identifying main idea of the text, analyzing
pattern of word use and comparing vocabulary between texts. The data is in form of
essays which consist paragraph, and paragraph consist some sentences. The
researcher is focus on the level of sentences. The sentences that researcher use
later is the sentences which the subject is the keywords.
The researcher used Ant Concordance as a tool to help in shorting the text
of the students’ essays. The first step of data analysis was to change the hard file
document into soft file document. Second, the researcher changed the format
Microsoft Word into plain text. Third, the researcher inputted the plain text into
Ant Concordance. Fourth, the researcher used the keyword (I, we, you, they, she,
he, and it) to short the sentences. Fifth, the researcher copied the sentences
containing those seven keywords into Microsoft Excel by naming every sheet
with the each keywords. From the Ant Concordance programs, the total sentences
obtained contain the keywords were 2,581 sentences.
Identifying the error means that the researcher separated the subject-verb
agreement error from the correct ones. Identifying the error from the data which
already shorted with Ant Concordance or called as corpus. From the corpus data,
31
the sentences later identified by using the grammatical features involving the
subject-verb agreement, such as verb form, auxiliary verb and modals. The Ant
Concordance program used only for helping the researcher in shorting the
sentences using a certain keywords. The one who classified and identified the
sentences later was the researcher itself. The researcher identified which correct
sentences and error sentences. Then, the researcher would be focus on the error
sentences only.
Classifying the error means that the researcher classified the subject-verb
agreement error into the four error types such as omissions, additions,
misformation and misordering. The researcher would clasiffy the error into four
classification which were four types of error. Accoding to Ellis (2003), there were
four error types, addition, misformation, misordering and omission.
Explaining the error means that the researcher explained the reason why
those error sentences belongs to each error type. At last, quantifying the error
means counting the amount of error that occurs. Then the final step was counting
the percentage of subject-verb agreement error production.
To count the subject-verb agreement error production made by students,
the researcher used a formula according Bluman (2004):
F
P=
x 100%
N
Which:
P = percentage of subject-verb agreement errors
F = frequency of subject-verb agremeent errors
N= number of sentences containing seven keywords
32
The researcher classified the level based on Sugiono (2010) written as follows:
66%-100% of errors were classified as high.
36%- 65% of errors were classified as middle.
0%- 35% of errors were classified as low.