attitudes of ceic students towards code-mixing in line

ATTITUDES OF CEIC STUDENTS TOWARDS

CODE-MIXING

IN LINE APPLICATION

BY

MS. THITTAYA WIROJWARANURAK

AN INDEPENDENT STUDY PAPER SUBMITTED IN PARTIAL

FULFILLMENT OF

THE REQUIREMENTS FOR THE DEGREE OF

MASTER OF ARTS IN CAREER ENGLISH FOR

INTERNATIONAL COMMUNICATION

LANGUAGE INSTITUTE

THAMMASAT UNIVERSITY

ACADEMIC YEAR 2017

COPYRIGHT OF THAMMASAT UNIVERSITY

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Independent Study Paper Title ATTITUDES OF CEIC STUDENTS TOWARDS

CODE-MIXING IN LINE APPLICATION

Author Ms. Thittaya Wirojwaranurak

Degree Master of Arts

Major Field/Faculty/University Career English for International Communication

Language Institute

Thammasat University

Independent Study Paper Advisor

Academic Years

Associate Professor Supong Tangkiengsirisin, Ph.D.

2017

ABSTRACT

The purposes of this study were to investigate the attitudes of the students of

Master of Arts Program in Career English for International Communication (CEIC)

toward code-mixing used in messages in Line application; and to explore the reasons

for using code-mixing when sending messages in Line application. The sample was

67 CEIC students in academic year 2017. The questionnaire was used as an

instrument and the Statistic Package for the Social Sciences (SPSS) program was used

for data analysis.

The findings revealed that the overall attitudes of the students toward the use

of code-mixing in messages in Line application were positive. They employed code-

mixing to convey messages more easily. Moreover, the use of code-mixing depended

on the interlocutors.

Keywords: Code-mixing, Line application

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ACKNOWLEDGEMENTS

I would like to express my deep gratitude to Associate Professor Supong

Tangkiengsirisin, Ph.D., my research advisor and Assistant Professor Ketwalee

Porkaew, the chairperson, for their suggestions and patient guidance during this

research. I would also like to thank to all participants for their kind cooperation in

responding to the questionnaires.

I would also like to extend my thanks to my classmate for all the support they

provided.

Finally, I wish to thank my family and friends for their great support and

encouragement during my study.

Ms. Thittaya Wirojwaranurak

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TABLE OF CONTENTS

Page

ABSTRACT i

ACKNOWLEDGEMENTS ii

LIST OF TABLES v

CHAPTER 1 INTRODUCTION 1

1.1 Background 1

1.2 Research Questions 2

1.3 Research Objective 2

1.4 Definitions of Terms 2

1.5 Scope of the study 3

1.6 Significance of the study 3

1.7 Organization of the study 3

CHAPTER 2 REVIEW OF LITERATURE 4

2.1 Code-mixing 4

2.1.1 Concepts and Definitions of Code-mixing 4

2.1.2 The reason of using code-mixing 5

2.2 Attitude towards code-mixing 9

2.3 Previous related studies 10

CHAPTER 3 RESEARCH METHODOLOGY 12

3.1 Participants 12

3.2 Instruments 12

3.3 Data collection 13

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3.4 Data analysis 13

CHAPTER 4 RESULTS 14

4.1 Personal information 14

4.2 Attitudes toward code-mixing used in Line application 16

4.3 The reasons for using code-mixing in Line application 20

CHAPTER 5 DISCUSSION, CONCLUSION AND RECOMMENDATIONS 23

5.1 Summary of the study 23

5.1.1 Objective of the study 23

5.1.2 The instrument of the study 23

5.2 Summary of the finding 23

5.2.1 Research Question 1 23

5.2.2 Research Question 2 24

5.3 Discussion 24

5.4 Conclusion 27

5.5 Recommendations for further study 27

REFERENCES 28

APPENDICES

APPENDIX A 31

BIOGRAPHY 36

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LIST OF TABLES

Tables Page

3.1 Degree of Attitude 13

4.1 Age of the participants 14

4.2 Gender of the participants 15

4.3 Participants’ year of the study 15

4.4 Participants’ language used in Line application 15

4.5 Interpretation of Score of degree of attitude 16

4.6 Participants’ positive attitudes toward code-mixing in Line application 16

4.7 Positive attitudes toward the use of code-mixing in Line application 18

4.8 Uncertain attitudes toward the use of code-mixing in Line application 19

4.9 Percentages, Mean and Standard deviations of reason for using 21

code-mixing

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CHAPTER 1

INTRODUCTION

1.1 Background

It is generally accepted that social media is extensively used for the purpose of

communication. At the beginning, there is simply a profile picture, profile details, and

some form of a wall, which drove most usage via communication (O'Keeffe, Pearson

& Council on Communications and Media, 2011). Individuals use social networks as

a new communication medium for exchanging various bits of information (Baruah,

2012). There are a number of applications, for instance, Twitter, Facebook,

Instragram and Line, which are widely used for various purpose including updating

news, exchanging idea, conducting business and communicating between

interlocutors (Baruah, 2012). This kind of communication is mainly displayed in the

form of written speech; however, few individuals conform to conventional grammar

of the written language (Maynor, 1994). Linguists address the issue of using language

among online communities including emoticons, unconventional spellings,

representation of spoken language, regional dialects and code-mixing (Huffaker,

David and Sandra, 2006). According to Hossain and Bar (2015), code-mixing or

code-switching has recently become one of the most significant issues. According to

Das and Gamback (2013), the interlocutors who are non-English speakers commonly

use a number of codes to write in their own language, for instance, insert English

elements and mix multiple languages, and these issues have been investigated by

several researchers (Bi, 2011). Furthermore, Nakornpanom (2015) points out that “ It

is interesting that code-mixing now is also used at the written level even though it can

be written with already existing words for concepts express in Thai language” (p.478).

Previous work has only focused on code-mixing in social media such as

Facebook and Twitter. Few studies have investigated using code-mixing in Line

Application, which the majority of Thais use as a tool for communication. Line

application is mainly used for instant communication on various devices such as

smartphones, tablet computers and personal computers. Users can exchange text

messages, images, video, audio and files, Users can also create groups to chat and

share media in a group (McCracken, 2015). In fact, Thailand is Line’s second largest

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market in the world after Japan with 33 million users at the end of 2015 (Nation,

2016), which is obvious why Line application is significant to Thais. This study has

therefore aims to examine using Thai and English code-mixing in Line application to

understand more about the attitudes and reasons for using code-mixing.

1.2 Research Questions

1.2.1 What are the attitudes of CEIC students toward code-mixing used in messages

in Line application?

1.2.2 What are the reasons CEIC students use code-mixing when sending messages

in Line application?

1.3 Research Objective

The objectives of the study are as follows:

1.3.1 To investigate attitudes of CEIC students toward code-mixing used in

messages in Line application.

1.3.2 To explore the reasons CEIC students use code-mixing when sending


1.4 Definition of Terms

The definition of the terms commonly used in this study is as follows:

1.4.1 Code-mixing refers to the mix between Thai and English found within one

sentence, as used in the Line application.

1.4.2 Attitude refers to feeling toward using of code-mixing in Line application

including positive and negative ways.

1.4.3 CEIC students refer to first and second year students of a Master of Arts

Program in Career English for International Communication in academic year 2017.

1.4.4 Line application refers to an application for instant communications on

devices, for instance, smart phones, tablets and computers, with this study focusing on

the exchange of text messages.

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1.5 Scope of the study

First and second year CEIC students in academic year 2017 will be used as

respondents of this study. Copies of questionnaires were distributed and returned

to analyze.

1.6 Significance of the study

This study will firstly enable the researcher in order to understand the reasons

of using code-mixing in Line application. Secondly, the study may facilitate Line

application users in communicating their messages clearly and understanding the

reasons and influences of using code-mixing.

1.7 Organisation of the study

There are five chapters contained in this research study.

Chapter One: Introduction consists of Background, Research questions,

Research objective, Definition of terms, Scope of the study, Significance of the study,

and Organization of the study.

Chapter Two: Review of the literature covers three topics. The concepts and

definitions of code-mixing, the reasons for using code-mixing and the attitudes toward

code-mixing.

Chapter Three: Methodology contains the participants, the research

instrument, data collection and data analysis.

Chapter Four: Results of the study

Chapter Five: Conclusion and Recommendations

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CHAPTER 2

LITERATURE REVIEW

This chapter is divided into three main sections. The first section examines the

concepts and definitions of code-mixing (section 2.1.1) and the reasons for using

code-mixing (section 2.1.2). The second section looks at the attitudes toward code-

mixing. The third section describes previous related studies.

2.1 Code-Mixing

2.1.1 Concepts and Definitions of Code-mixing

Kachru (1978, p.28) defined code-mixing as “ the use of one or more

languages for consistent transfer of linguistic units from one language into another,

and by such a language mixture developing a new restricted- or not so restricted- code

of linguistic interaction”. Similarly, Muysken (2000) gives a definition of code-

mixing as “all cases where lexical items and grammatical features from two languages

appear in one sentence.” Meanwhile, code-mixing is referred to by Bauer (2010) as

“linguistic behavior of a bilingual speaker who imports words or phases from one of

his/her language into the other one” (p.4). Furthermore, the “Commonwealth” school,

by McClure (1977) and by Blom & Gumperz (1972, p.429-30) Speaker uses more

than two languages. The second language occurs in the middle of another, which

might be used in additive fashion. On the other hand, the first language is usually

dominant, which is different from borrowing from the second language. Moreover,

code-mixing is used by bilinguals while borrowing is used by monolinguals. (as cited

in Gibbons, 1946, p.78, 80).

However, a number of researchers acknowledge that code-mixing and code-

switching share the same concept (Cardenas & Isharyanti, 2009). According to

Wardhaugh (1992, p.107), he defines code–mixing as “the deliberate use of two

languages without an associated topic change. It is basically found in multilingual

places. It is closely related to code-switching.” (as cited in Hossain and Bar, 2015,

p.127).

Fischer (1972) supports the hypothesis that code-switching and code-mixing

share the same characteristic. He explains that code-mixing has been identified as

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being one types of code-switching, which can be called intra-sentential code-

switching. It is difficult for some people to differentiate code-mixing and code-

switching (Kim, 2006). Grosjean (1982) states that “code-mixing transfers elements

of all linguistic levels and units ranging from a lexical item to a sentence, so that it is

not always easy to distinguish code-switching from code-mixing” (as cited in Kim,

2006, p.45).

Nevertheless, there are some difference between code-switching and code-

mixing. Wei (1998) examined the difference between code-mixing and code-

switching and found that it depends on where the language occurs; code-switching

occurs at above the clause level while code-mixing occurs below that level. Similarly,

Fischer (1972) points out that code-mixing happens when two or more languages are

used below the clause level.

On the other hand, Myers-Scotton (1993) states that code-switching occurs

when bilinguals change between two codes throughout one interaction with another

bilingual person. Likewise, code-mixing employing words, affixes, phrases and

clauses from more than one code within the same sentences. Moreover, Mesthrie

(2011) found that the difference between code-switching and mixing is the break

between the two codes, with code-switching being smooth and more or less

understandable across clauses or functionally to emphasize the meaning for people

who know only one code. For instance, switching from a native language like Luhya

to another language of wider communication like Swahili at a marketplace in Kenya.

Therefore, code-switching depends on the conversation, the situation or the use, while

code-mixing is blurred, ragged and constantly changing back and forth within clauses.

Since people in conversations can communicate in more than one code and may

change them for special reasons, code-mixing leans more towards a metaphorical

function that representing a lifestyle or attitude to language.

2.1.2 Reasons for Using Code-Mixing

Despite the fact that code-mixing allows for shifts of language, it is significant

to recognize the factors that cause code-mixing (Luke, 2015). According to Hoffman

(1991), there are several reasons for code-mixing. Those are:

1. Talking about a particular topic

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Individuals do code-mixing when talking about specific topics; for instance,

political and religious topics. Sometimes, addressees feel free to express their

emotions in one language that they are familiar with. For example, In Lebanese

society, it is easier and more comfortable to discuss emotional and sexual topics in

English or French than the native language of the society (Leung, 2006).

2. Quoting somebody else

This occurs when famous expressions or utterances are quoted by the

addressee, to show that the addressee is a modern person who always keeps himself or

herself up to date on new information. The quotations are generally from a public

figure or famous people.

For example

Dlem salah, gerak dikit salah, owalah to mbak n mas, kalo situ ngerasa bener

woles kali, kalo kesindir ya kerasa kan kalo salah… Don’t get stuck up on ur

miserable drama

(Walangitan, 2015, p.16)

3. Being emphatic about something

Normally, when individuals who are speaking in a language that is not their

native language in communication, he or she will change his or her second language

to the first language when they want to be emphatic about something.

Kongkerd (2015) also points out that the interlocutors code-mix to enhance

understanding and express authentic feelings. For example, Thai words and idioms

are chosen to display the clear and exact meaning in English conversation among

Thais.

For example

F: My girlfriend lives in Lumpoon and how about your boyfriend?

A: Haha no one now. Haha study study and study

F: Haha

A: Maybe I am on คานทอง haha

F: Haha

(Kongkerd, 2015, p.129)

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4. Interjections

A short exclamation like: Hey!, Well!, Look!, etc that has no grammatical

value is used by the interlocutors. Hoffman (1991) states that “language switching and

language mixing among bilingual or multilingual people can sometimes be marked by

an injection or sentence connector.”

For example

Look 漫画喽! (Look man hua lou!)

(Look comic books ah!) (Bi, 2011, p.66)

5. Repetition used for clarification

Hoffman (1991) declare that “when a bilingual wants to clarify his or her

speech so that it will be understood better by the listener, he or she can sometimes use

both of the languages that he or she mastered by saying the same utterance”.

For example:

English_Hindi

Son was called by his father while he was walking through a train compartment,

“Keep straight. Sidha jao” (keep straight).

(Gumperz, 1982, p.78)

6. Intention of clarifying the speech content for interlocutor

A message in one code is repeated in the other language with the objective of

making the speech run smoothly or illustrate the ideas so as to understand easily.

7. Expressing group identity

Individuals code-mix to express group identity since each group has a

different way when they communicate with their group and person from other groups.

Code-mixing is used to express identity and group membership (Kongkerd, 2015).

According to the Ministry of Culture (2013), individuals used dialects to express their

solidarity when they communicate (as cited in Kongkerd, 2015).

For example:

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A: P lob ban pao ka pid term na (Will you go to your hometown this summer?)

F: I am planning to go to Chiang Mai krab.

(Kongkerd, 2015, p.130)

Furthermore, Saville-Troike (1986, p.69) adds some additional reasons for

doing code-mixing. There are:

8. To soften or strengthen requests or commands

Code-mixing is used to strengthen commands or soften requests to sound more

polite or display power. Similarly, Kongkerd (2015) also explains that interlocutors

use code-mixing to express courteousness and respect. According to Hua Hin (2013),

it is significant in Thai culture that younger people should convey politeness or

respect their senior. This can be done by employing sentence ending words such as

“ka” and “krub” in conversation (Thai Language Lessons, 2014)

For example

A: Good morning krub.

B: Hi

A: Where are you and How are you krub?

(Kongkerd, 2015, p.129)

9. Because of a real lexical need

Due to lack of equivalent lexicon in the language, interlocutors code-mix to

express clear messages and avoid vague meaning (as cited in Luke, 2015).

Moreover, Grosjean (1982) points out that the reason why code-switching and

code-mixing occur is the lack of appropriate word when talking about particular

topics, i.e., there is no item or appropriate translation for the vocabulary needed in the

language being used. Also, some bilinguals mention that code-switching and code-

mixing is used when they are exhausted, lazy, or annoyed (Grosjean, 1982).

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2.2 Attitudes toward code-mixing

According to Hogg & Vaughan (2005), An attitude is “a relatively enduring

organization of beliefs, feelings and behavioral tendencies towards socially significant

objects, groups, events or symbols”. Furthermore, Eagly & Chaiken (1993, p.1) also

point out that an attitude is “a psychological tendency that is expressed by evaluating

a particular entity with some degree of favor or disfavor. (as cited in Mcleod, 2009).

In the language world, Gibbons (1987) states that “language attitudes

frequently reflect the history and current position of different linguistic groups within

a society” (as cited in Regan).

According to Bhatia and Ritchie (2004), the majority of studies have shown

negative attitudes towards code-mixing and code-switching. Lin (1966) states that the

perception of using code-switching is negative, such as for those with lower status and

for people who are weak in language performance (as cited in Alenezi, 2010). More

importantly, De Houwer (2009) showed that code switching in language teaching also

has been perceived in negative ways. It can be said that code-switching affects the

competency of young people in learning a target language including lack of choosing

the appropriate language choice or poor cognitive control (as cited in Dewaele & Wei,

2014).

Another research finding indicated that bilinguals had a negative attitude

toward code-mixing. Bhatia and Ritchie found that code-mixing or code switching are

considered by the majority of bilinguals to be a sign of “laziness”, an “inadvertent”

speech act, and an “impurity”. Moreover, it is viewed as linguistic decadence and an

danger to their native language. On the other hand, Zentella (1999) claims that “code

switching is more common during informal interpersonal interactions, including those

that take place between family members in natural contexts” (as cited in Kim, 2006).

Nevertheless, Mustafa (2011) investigated code switching in Short Message

Service (SMS) among teenagers in Jordan. The research aimed to explore the attitudes

towards code-switching and the findings showed that a high percentage of teenagers

preferred switching to English when texting because they pride themselves on

knowing this language. Moreover, some teenagers believed that English language is

used by those who belong to a higher socioeconomic class. Some teenagers preferred

to code-switch because it maintains their language competency.

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Furthermore, Bi (2011). who explored English mixing in Chinese Internet language,

explains that English words in Chinese media are widely used and quite popular. Bi

(2011)’s findings showed that the general attitudes from the respondents were

positive.

2.3 Previous related studies

There are several previous studies that have investigated the use of code-mixing.

Alenezi (2010) examined the attitude of students towards using Arabic and

English switching as a medium of instruction in the college of health sciences. The

participants of this study comprised 17 students who studied in a science class of

Human Development for Occupational Therapy at the Allied Health Science College

in Kuwait University by using a questionnaire and open-ended questions as the

instrument. The findings showed that students strongly prefer the use of Arabic and

English code-switching as a medium of teaching and have a positive attitudes towards

code-switching. Although most students strongly agreed that using one language is

useful to them, they found that code-switching made the course easier to understand

than using only one language.

Mustafa (2011) found the same results. He investigated code-switching in

Short Message Service (SMS) among teenagers in Jordan. The research aimed to

explore the most frequently used phrases, the reasons for using English Arabic code-

switching, the attitude towards code-switching and the factors that made the use of

code-switching spread among teenagers in Jordan. The participants were 150 male

and female teenagers in Jordan, selected by purposeful sampling from five different

schools. The instruments of this study consisted of a questionnaire and interviews.

Moreover, the researcher also collected 1,500 text message of the sample in the

questionnaire to fulfill the objectives of study. The findings of this study revealed that

there were a number of reasons including, the economy, euphemisms, prestige,

unfamiliarity with Arabic, and using academic, scientific and technical terms, The

ability to use abbreviations and acronyms and the attractiveness of English language

might be a factor that influences teenagers to employ code switching between Arabic

and English. Moreover, the findings showed that teenagers greatly preferred switching

to English when texting.

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Kongkerd (2015) investigated code-switching and code-mixing in Facebook

conversations in English among Thai users. She found that English was used to

communicate on Facebook among a number of Thais, which can lead to code-

switching and code-mixing since Thais infrequently communicate in English. In her

research, Kongkerd (2015) aimed to investigate the reasons for using code-switching

and code-mixing in regard to learning and communicating in English. The results

revealed that there were three main reasons. First, code-mixing and code-switching

were used to express politeness and respect. Second, they were used to emphasize

authentic feelings and to show solidarity. Third, the users had an opportunity to

practice English in daily life. However, using code-mixing and code-switching in

email writing or formal documents can be considered as unprofessional.

Luke (2015) studied the use of Pamonese and Indonesian language code-

mixing among Pamonese in Parata Ndaya closed group Facebook. The researcher

aimed to investigate the types of code-mixing and the reason of doing code-mixing.

The data of this study was collected from the comments of members in the closed

group, which focused mainly on political issues that happened during Regional House

Representative Election in 2014. The results showed that 72% of comments were

code-mixing, which means members of Parata Ndaya preferred to switch the language

to Indonesian. The intra-lexical mixing was the first ranked among other types like

changing of pronunciation and intra-sentential. The results also revealed that the most

frequent reason for using code-mixing was expressing group identity at 24%.

Na Nakornpanom (2015) explored the code- mixing of Japanese, English and

Thai in Line chat and the occurrences of code-mixing under the heading of insertion

and translation. The participants of this study were 26 students of the third year

majoring in Japanese and minoring in English. All of them used Thai as their native

language. The data was collected from a Line chat room of the participants and the

findings showed that it was a common that Thai words were inserted in the other two

languages in a sentence for instance, “Celebก็เง้ียするไรก็ไมน าเกลียด, which means

Whatever the Celebrity does, it is acceptable”.

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CHAPTER 3

RESEARCH METHODOLOGY

This chapter describes: (1) participants, (2) instrument, (3) data collection, and (4)

data analysis.

3.1 Participants

The objective of this study is to study the attitudes and the reasons that CEIC

students use code-mixing in Line application. The participants of this study were

calculated by using Yamane’s (1973) formula. This was calculated from 80 first and

second year students of the Master of Arts Program in Career English for

International Communication in academic year 2017 who use Line application. CEIC

students are appropriate to be the sample in this study because code-mixing generally

happens with individuals who are bilinguals. In fact, CEIC students speak Thai as

their native language or mother tongue and English is their second language;

therefore, they tend to use or are familiar with code-mixing. Moreover, it is highly

likely that the majority of CEIC students use Line application for communication such

as text messages and thus were suited to be the participants of this study that aimed to

investigate attitude of using code-mixing in Line application. After calculating using

Taro Yamane’s formula, the number of participants was 67 students. Convenience

sampling was used to choose the participants to conduct this survey.

3.2 Instruments

The instrument used for data collection was a questionnaire.

The questionnaire was adapted from a previous study and consisted of close-

ended questions.

The questionnaire was divided into three parts:

PART 1: The first part was personal information of participants including,

gender, age, nationality, and language used in Line application as checklist

questions.

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PART 2: The second part focused on CEIC students’ attitudes toward code-

mixing in Line application using a five point Likert scale. For each question, the

participants had to select the degree of their agreement and disagreement with the

given statement that related to their feelings toward using code-mixing in Line

application.

PART 3: The third part related to the reasons for using code-mixing in Line

application such as for practice, technical terms, expressing feelings and prestige

by using a five point Likert scale. The participants had to select one of them,

which affected the level of agreement and their agreement with the given

statement.

Table 3.1 Responses from the Likert scale questions were calculated as follows.

3.3 Data collection

A questionnaire was distributed to participants using convenience sampling.

The questionnaires were distributed to more than 67 students in order to obtain

reliable data and prevent data error; for instance, participants not answering all the

questions. The participants could take as much time as they needed to complete

the questionnaire.

3.4 Data analysis

After collecting the questionnaires, the data of this study was analyzed using

the Statistical Package for the Social Sciences (SPSS) to calculate as follows:

The data from the second and the third part was also analyzed in the form of

descriptive statistics including, percentage, mean and standard deviation.

Degree of Attitude Positive Statement Negative Statement

Strongly Agree 5 1

Agree 4 2

Uncertain 3 3

Disagree 2 4

Strongly Disagree 1 5

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CHAPTER 4

RESULTS

This chapter presents the results of this study, which is divided into three

sections: 1) personal information, 2) attitudes of CEIC students toward code-mixing

used in Line application and 3) the reasons CEIC students use code-mixing in Line

application.

4.1 Personal information

The first part of the questionnaire focused on the participants’ demographic

data, which are illustrated in the form of frequency and percentage as follows:

Table 4.1 Age of the Participants

Age Frequency Percentage (%)

18-24 8 11.9

25-34 52 77.6

35+ 7 10.4

Total 67 100

According to Table 4.1, the age range is divided into three groups: 18-24

years, 25-34 years and 35+ years. The majority of the participants were 25-34 years

(77.6%), followed by 18-24 years (11.9%) and 35+ years (10.4%).

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Table 4.2 Gender of the Participants

Gender Frequency Percentage (%)

Female 57 85.1

Male 10 14.9

Total 67 100

As displayed in Table 4.2, from total of 67 person who participated in this

study, most of the participants were female (85.1%) and the remaining (14.9%) were

male.

Table 4.3 Participants Year of the Study

Years Frequency Percentage (%)

1st year 19 28.4

2nd year 48 71.6

Total 67 100

As shown in Table 4.3, the majority of the participants were second year

students, which was 71.6%. This might be due to the amount of first year students that

in this academic year was less than second year students.

Table 4.4 Participants’ Language used in Line application

Language Frequency Percentage (%)

Thai 14 20.9

English 5 7.5

Thai and English 48 71.6

Total 67 100

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According to the table above, most of the participants used Thai and English

when sending messages in Line application at 71.6%. It is highly likely that code-

mixing was used in communication. The least used language in Line application was

English (7.5%).

4.2 Attitudes toward code-mixing used in Line application

This section elicited the participants attitudes toward code-mixing used in Line

application using a five point Likert scale to measure the level of agreement or

disagreement with the given statements related to code-mixing used. The SPSS

program was used to analyze the results in the second part of the questionnaire into

mean scores, standard deviations and the percentages.

Table 4.5 Interpretation of Scores of Degree of Attitude

Table 4.6 Participants’ positive Attitudes toward code-mixing in Line application

Statement Mean SD Level

1. Mixing of Thai and English in Line chat provides

opportunities to learn English.

3.73 .978 Positive

2. I find English words easy to understand. 4.13 .815 Positive

3. Mixing of Thai and English in Line chat is a sign

of globalization.

3.70 1.059 Positive

4. It draws my attention when I see mixing of Thai

and English languages in Line chat.

3.31 1.117 Uncertain

5. I think mixing Thai and English in Line chat will

‘distort’ Thai language.


Mean Score Level of Interpretation

4.21-5.00 Extremely positive

3.41-4.20 Positive

2.61-3.40 Uncertain

1.81-2.60 Negative

1.00-1.80 Extremely negative

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17

Table 4.6 Continued

6. Mixing Thai and English in Line chat may

disadvantage monolinguals.


7. I will continue to read and write in that way. 3.90 .923 Positive

8. I feel comfortable with mixing Thai and English in

Line chat.

3.99 .826 Positive

9. It confuses me when interlocutors mix Thai and

English in Line chat


10. Using Thai in Line chat increases my chances of

understanding the messages.

3.55 1.145 Positive

11. Using English in Line chat increases my chances

of understanding the messages.

3.76 .854 Positive

12. Mixing of Thai and English in Line chat

increases my chances of understanding the messages.

3.70 .954 Positive

13. Those who mix Thai and English in Line chat do

so to show off.

3.48 1.050 Positive

14. Those who mix Thai and English in Line chat

belong to a higher socioeconomic class.


15. Those who mix Thai and English dissociate

themselves from Thai culture.

3.46 1.223 Positive

Total 3.56 1.042 Positive

Table 4.6 demonstrates the attitudes of participants toward code-mixing used

in messages in Line application. As can be seen from the table above, overall

participants had a positive attitudes toward code-mixing used in messages in Line

application as presented by mean score of 3.56. There are two main overall levels of

attitudes derived from this study, which are positive and uncertain. Interestingly, there

were no negative attitudes toward the use of code-mixing in Line application.

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18

It is apparent from this table that most of participants thought that English

words are easy to understand at the mean score of 4.13, which was the highest mean

score and found to be relatively positive. They also felt comfortable with mixing Thai

and English used in Line chat and will continue to read and write in that way as

reported by mean score of 3.99 and 3.90, which were positively viewed by the

participants.

On the other hand, they were undecided whether they agreed or disagreed that

mixing Thai and English in Line chat “distorts” Thai language and disadvantages

monolinguals as indicated by mean scores of 3.12 and 3.03, respectively.

Table 4.7 Positive attitudes toward the use of code-mixing in Line application

Statement Strongly

agree

Agree Uncertain Disagree Strongly

disagree

Mean

1. Mixing of Thai and English in Line

chat

provides opportunities to learn English.

14

(20.9%)

31

(46.3%)

13

(19.4%)

8

(11.9%)

1

(1.5%)

3.73

2. I find English words easy to

understand.

24

(35.8%)

31

(46.3%)

9

(13.4%)

3

(4.5%)

-

4.13


chat is a sign of globalization.

17

(25.4%)

24

(35.8%)

17

(25.4%)

7

(10.4%)

2

(3.0%)

3.70

7. I will continue to read and write in

that way.

18

(26.9%)

30

(44.8%)

14

(20.9%)

4

(6.0%)

1

(1.5%)

3.90

8. I feel comfortable with mixing Thai

and English in Line chat.

17

(25.4%)

36

(53.7%)

11

(16.4%)

2

(3.0%)

1

(1.5%)

3.99

10. Using Thai in Line chat increases my

chances of understanding the messages.

13

(19.4%)

28

(41.8%)

14

(20.9%)

7

(10.4%)

5

(7.5%)

3.55

11. Using English in Line chat increases

my chances of understanding the

messages.

13

(19.4%)

30

(44.8%)

19

(28.4%)

5

(7.5%)

-

3.76


chat increases my chances of

understanding the messages.

12

(17.9%)

31

(46.3%)

19

(28.4%)

2

(3.0%)

3

(4.5%)

3.70

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As can be seen in table 4.7, there were high mean scores for participants’

attitudes toward code-mixing used in messages in Line application. From the above,

35.8% participants strongly agreed, 46.3% of them agreed and only one disagreed that

English words used in Line are easy to understand. The majority of participants

(25.4% strongly agreed and 53.7% agreed) felt comfortable with mixing Thai and

English in Line. Moreover, most of the participants (26.9% strongly agreed and

44.8% agreed) stated that they will continue to read and use code-mixing in Line chat.

The table also showed that 41.8% of the participants agreed that using Thai in Line

chat increases the chances of understanding the messages and 44.8% agreed that using

English in Line chat helps them understand the messages better.

On the other hand, 46.3% agreed that mixing of Thai and English in Line chat

increases the chances of understanding the messages.

The majority of the participants (22.4% strongly disagree and 32.8%

disagreed) disagreed that individuals who mix Thai and English dissociate themselves

from Thai culture. This indicates that participants do not think that a person who

code-mixes between Thai and English dissociates themselves from Thai culture.

Therefore, this could imply that the participants had positive attitudes toward code-

mixing used in Line messages.

Table 4.8 Uncertain attitudes toward the use of code-mixing in Line application

Table 4.7 Continued

13. Those who mix Thai and English in

Line chat do so to show off.

1

(1.5%)

13

(19.4%)

18

(26.9%)

23

(34.3%)

12

(17.9%)

3.48

15. Those who mix Thai and English

dissociate themselves from Thai culture.

5

(7.5%)

11

(16.4%)

14

(20.9%)

22

(32.8%)

15

(22.4%)

3.46

Statement Strongly

agree


disagree

Mean

4. It draws my attention when seeing

mixing of Thai and English languages in

Line chat.

12

(17.9%)

17

(25.4%)

20

(29.9%)

16

(23.9%)

2

(3.0%)

3.31

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From Table 4.8, we can see that participants ’attitudes were at the moderate

level. As the results showed in table 4.8, many participants (32.8%) were undecided

about whether they agreed or disagreed that individuals who mix Thai and English in

Line chat belong to a higher socio-economic class, and 29.9% participants were

uncertain that seeing code-mixing in Line chat draws their attention. However, the

participants’ attitudes were likely positive as shown in 5) and 9) that 44.8%

participants disagreed and 7.5% of them strongly disagreed that it confuses them

when interlocutors mix Thai and English in Line chat (13.4% strongly disagreed and

29.9% disagreed) did not think that using code-mixing distorts Thai language. In

contrast, 9% of the participants strongly agreed and 29.9% of them agreed that mixing

Thai and English in Line chat may disadvantage monolinguals, which indicated that

the participants highly likely had negative attitudes.

4.3 The reasons for using code-mixing in Line application

This section demonstrates the reasons of CEIC students used code-mixing

when sending messages in Line application. The results were derived from part three

of the questionnaire. The results were computed into mean scores, standard deviation

and percentages.

Table 4.8 Continued

5. I think mixing Thai and English in Line

chat will ‘distort’ Thai language.

7

(10.4%)

16

(23.9%)

15

(22.4%)

20

(29.9%)

9

(13.4%)

3.12

6. Mixing Thai and English in Line chat

disadvantages monolinguals.

6

(9.0%)

20

(29.9%)

20

(29.9%)

8

(11.9%)

13

(19.4%)

3.03

9. It confuses me when interlocutors mix

Thai and English in Line chat.

5

(7.5%)

11

(16.4%)

16

(23.9%)

30

(44.8%)

5

(7.5%)

3.28

14. Those who mix Thai and English in

Line chat belong to a higher

socioeconomic class.

6

(9.0%)

9

(13.4%)

22

(32.8%)

21

(31.3%)

9

(13.4%)

3.27

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Table 4.9 Percentages, means and standard deviations of reasons for using code-

mixing

Statement Strongly

agree


disagree

Mean SD

1. Mixing Thai and English in Line

chat to talk about taboo issues

3

(6.3%)

24

(50%)

15

(31.3%)

4

(8.3%)

2

(4.2%)

3.46 .898


chat to express loyalty to English.

-

15

(31.3%)

14

(29.2%)

14

(29.2%)

5

(10.4%)

2.81 1.003


chat to gain prestige.

4

(8.3%)

14

(29.2%)

14

(29.2%)

12

(25%)

4

(8.3%)

3.04 1.11


chat because English is full of

academic, scientific and technical

terms.

14

(29.2%)

25

(52.1%)

5

(10.4%)

3

(6.3%)

1

(2.1%)

4.00 .923


chat because I do not know the Thai

equivalent.

10

(20.8%)

23

(47.9%)

9

(18.8%)

4

(8.3%)

2

(4.2%)

3.73 1.026


chat because English contains

abbreviations and acronyms.

11

(22.9%)

27

(56.3%)

8

(16.7%)

2

(4.2%)

- 3.98 .758


chat according to the receiver of the

message.

13

(27.1%)

26

(54.2%)

8

(16.7%)

1

(2.1%)

- 4.06 .727


chat to express authentic feelings.

14

(29.2%)

21

(43.8%)

9

(18.8%)

2

(4.2%)

2

(4.2%)

3.90 1.016


chat to increase status in the eyes of

the opposite sex.

5

(10.4%)

10

(20.8%)

11

(22.9%)

17

(35.4%)

5

(10.4%)

2.85 1.185


chat to soften requests or strengthen

commands.

15

(31.3%)

21

(43.8%)

7

(14.6%)

5

(10.4%)

- 3.96 .944


chat to convey messages more easily.

21

(43.8%)

22

(45.8%)

4

(8.3%)

1

(2.1%)

- 4.31 .719

Total 3.64 0.93

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Table 4.9 provides the reasons for using code-mixing in Line application of

CEIC students. From this table, it can be seen that the main reasons for using code-

mixing in Line chat was to convey messages more easily as shown by the mean score

of 4.31, which was at a high level. A total of 43.8% of the participants strongly agreed

and 45.8% of them agreed; moreover, no one strongly disagreed with this reason.

Another reason was mixing Thai and English in Line chat according to the receiver of

the message, with a mean score 4.06, with over half of the participants (54.2%)

agreeing with this reason, followed by mixing Thai and English in Line chat since

English is full of academic, scientific and technical terms (4.00), with most of the

participants (52.1%) agreeing that they code-mix when they employ academic,

technical and scientific terms. Only 1% disagreed. There were three reasons that were

at the moderate level and the least frequent reason selected with the mean score of

2.81 was that mixing Thai and English in Line chat expresses loyalty to English.

This chapter displayed the results of the study in terms of personal

information, attitudes of CEIC students toward code-mixing and reasons for using

code-mixing. The findings will be discussed and summarized in Chapter 5.

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CHAPTER 5

DISCUSSION CONCLUSION AND RECOMMENDATIONS

This chapter contains the summary of the study, the summary of the finding,

discussion of the study, the conclusion, and recommendations for further study.

5.1 Summary of the study

This section recapitulates the objectives of the study and the instrument of the

study.

5.1.1 Objectives of the study

The objectives of the study were to investigate attitudes of CEIC students

toward code-mixing used in messages in Line application and to explore the reasons

these students used code-mixing when sending messages in Line application.

5.1.2 The instrument of the study

The participants of this study were 67 first and second year students of Master

of Arts Program in Career English for International Communication in academic year

2017. A questionnaire was used as the instrument of this study, which was divided

into three parts: the participants’ personal information, participants’ attitudes toward

code-mixing used in Line application and the reasons for using code-mixing in Line

application.

5.2 Summary of the finding

5.2.1 Research Question 1: What are the attitudes of CEIC students toward

code-mixing used in messages in Line application?

The overall attitudes of the students toward code-mixing used in messages in

Line application were positive with the mean score of 3.56. As can be seen in Table

4.6, some of the participants agreed that using English word is easy to understand

with the mean score of 4.13. Moreover, over half of participants also agreed that they

feel comfortable with mixing Thai and English in Line chat with the mean score of

3.99. Nevertheless, they were undecided whether they agreed or disagreed that mixing

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Thai and English in Line chat may disadvantage monolinguals, which had the lowest

mean score of 3.03.

5.2.2 Research Question 2: What are the reasons CEIC students use code-

mixing when sending messages in Line application?

The main reasons for using code-mixing was to convey messages more easily

as reported by mean score of 4.31 which is the highest mean score, followed by

mixing Thai and English in Line application because of the receiver of the message

with the mean score 4.06, and that English is full of academic, scientific and technical

terms with the mean score 4.00. On the other hand, using code-mixing in Line chat to

express loyalty to English was the least common reason with the mean score of 2.81.

5.3 Discussion

5.3.1 The first question in this study sought to investigate CEIC students’ attitudes

toward code-mixing used in Line application, with the results of this study indicating

that the majority of the students’ overall attitudes were positive. Most of the

participants found that English words easy to understand and they feel comfortable

using Thai-English code-mixing in Line chat. This result is consistent with the study

of Bi (2011) who found that English words in Chinese media were widely used and

quite popular, with the majority of respondents having showed positive attitudes

toward them. To be more specific, the respondents (78%) said that there were no

difficulties in understanding them.

The findings showed that a high percentage of the students agreed that mixing

of Thai and English in Line chat provides opportunities to learn English. This seems

to be in line with the study of Kongkerd (2015) who found that employing code-

switching and code-mixing on Facebook may have positive effects on those who mix

Thai and English as they have an opportunity to practice, learn and memorize English

words or phrases in their daily life. This also increases their motivation in English

learning.

The findings showed that a high percentage of students agreed that mixing

Thai and English in Line chat increases the chance of understanding the messages.

This finding further supports Alenzi (2010) who found that his students had a strong

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preference toward Arabic-English code-switching used in teaching over using one

language. They found it more desirable and believed that using code-switching made

the course easier to understand. However, this is in contrast with the study of De

Houwer (2009), which revealed that code-switching affected the competency of

young people in learning the target language (as cited in Dewaele & Wei, 2014).

The current study found that a high percentage of students disagreed with

those who thought that individuals who mix Thai and English in Line chat do so to

show off. This results failed to support the findings of Mustafa (2011) that a high

percentage of teenagers agreed that students use English in their text messages to

show off. However, Mustafa’s (2011) findings showed a negative attitude toward

switching to English, which was a dissociation from the Arabic culture, with his

participants disagreeing with the dissociation issue. They believed that using English

does not mean separating themselves from the Arab world. This also accords with the

finding of this study, which showed that most of the students (22.4% strongly

disagreed, 32.8% disagreed) showed disagreement with the issue of dissociation. This

supports a positive view towards code-mixing used in Line chat.

However, most students were still undecided as to whether they agreed or

disagreed with using Thai and English when sending messages in Line chat. The

results indicated that they were uncertain whether mixing Thai and English in Line

chat ‘distorts’ Thai language; this is in opposition to Bhatia and Ritchie (2004), who

found that the majority of bilinguals viewed code-mixing as linguistic decadence and

a potential threat to their native language.

The resulted also showed that students were undecided that mixing Thai and

English in Line chat may disadvantage monolinguals. To be more specific, 29.9% of

the participants were uncertain whereas 9% of the participants strongly agreed and

29.9% of them agreed. This result was the same as the finding of Bi (2011) that most

participants agreed that code-mixing expression used in various media may

disadvantage monolingual speakers.

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5.3.2 The second question in the research was what are the reasons that CEIC

students use code-mixing in Line application?

The most interesting finding was that the majority of students mixed Thai and

English in Line chat because it is easier to convey message in that way. This result is

consistent with Mustafa (2011) who revealed that the teenagers thought they could

express their messages more easily in English and Arabic, they could use Arabic

which is their mother tongue language and use abbreviations and acronyms in

English.

Another important reason for using code-mixing in Line chat was the receiver

of the message. This also supports the finding of Mustafa (2011) that teenagers

switched between Arabic and English because they communicate with foreign friends

who might not be familiar with the Arabic equivalent of the word and Arab speakers

or individuals are not aware of the English terms of English language

Another reason was English is full of academic, scientific and technical terms;

thus, students mix Thai and English in Line chat. This result seems to be in line with

Mustafa (2011) who found that teenagers frequently switch to English because of

academic, technical and scientific terms. This also agrees with Chaiwichian (2007),

who investigated the phenomenon of code switching among students who attended an

English program. The results revealed that “interlocutors excessive use of academic

terms in English urge students to switch more to English and the topics of

conversations interlocutors tackle in classroom influence students’ use of CS (as cited

in Mustafa, 2011).”

The results of this study showed that a high percentages of students mixed

Thai and English in Line chat to soften requests or strengthen commands. The present

findings seem to be consistent with Hoffman (1991) and Kongkerd (2015)m which

found that code-mixing was employed to strengthen commands or soften requests to

sound more polite and show powers. Moreover, the interlocutors used code-mixing to

express courteousness and respect.

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5.4 Conclusion

The following conclusions are made based on the discussion above.

5.4.1 Most of the participants have positive attitudes towards code-mixing used in


5.4.2 The majority participants found that using English word is easy to understand.

5.4.3 Most of the students were uncertain whether it is good or bad to use code-

mixing in Line chat.

5.4.4 Mixing Thai and English in Line chat to convey messages more easily was rated

as the most common reason that students code mix.

5.4.5 The least common reason that students selected was mixing Thai and English in

Line chat to express loyalty to English.

5.5 Recommendations for further study

Based on the findings and conclusion of the study, the following

recommendations are made for future research.

5.5.1 Open-ended question should be included to elicit additional information.

5.5.2 This study investigated only attitudes toward code-mixing and the

reasons for using code-mixing in Line application, Future study should explore the

factors that have an influence on using code-mixing.

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REFERENCES

Alenezi, A. A. (2010). STUDENTS'LANGUAGE ATTITUDE TOWARDS USING

CODE-SWITCHING AS A MEDIUM OF INSTRUCTION IN THE

COLLEGE OF HEALTH SCIENCES: AN EXPLORATORY STUDY.

Annual Review of Education, Communication & Language Sciences, 7.

Bi, N. Z. (2011). An investigation into English mixing in Chinese Internet language.

World Journal of English Language, 1(2), 60.

Cakrawarti, D. A. (2011). Analysis of code switching and code-mixing in the teenlit

Canting Cantiq by Dyan Nuranindya (Doctoral dissertation, University of

Diponegoro).

Dewaele, J. M., & Wei, L. (2014). Attitudes towards code-switching among adult

mono-and multilingual language users. Journal of Multilingual and

Multicultural Development, 35(3), 235-251.

Gibbons, J. (1987). Code-mixing and code choice: A Hong Kong case study (Vol. 27).

Clevedon: Multilingual Matters.

Hossain, D., & Bar, K. (2015). A case study in code-mixing among Jahangirnagar

University students. International Journal of English and Literature, 6(7),

123-139.

Kim, E. (2006). Reasons and Motivations for Code-mixing and Code-switching.

Issues in EFL, 4(1), 43-61.

Kongkerd, W. (2015). Code Switching and Code-mixing in Facebook Conversations

in English among Thai Users. วารสาร นัก บริหาร (Executive Journal), 35(1), 126-

132.

Luke, J. Y. (2015). The Use of Code-Mixing among Pamonanese in Parata Ndaya

Closed-Group Facebook. Lingua Cultura, 9(1), 40-46.

McCracken, H. (2015). How Japan’s LINE app became a culture-changing, revenue-

generating phenomenon. Fast Company.

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Mesthrie, R. (2001). Code-mixing. Concise encyclopedia of sociolinguistics, 442-

443.

Mustafa, R., & Hussein, R. F. (2011). SMS Code-switching among Teenagers in

Jordan. Middle East University.

McLeod, S. (2014). Attitudes and behavior. Retrieved on March, 10, 2015.

Muysken, P. (2000). Bilingual speech: A typology of code-mixing (Vol. 11).

Cambridge University Press.

Nakornpanom, P. N. (2015). The Code-Mixing of Japanese, English and Thai in Line

Chat. World Academy of Science, Engineering and Technology, International

Journal of Social, Behavioral, Educational, Economic, Business and

Industrial Engineering, 9(2), 478-481.

Walangitan, M. A. (2015). Reasons for Mixing English Words on Facebook Post

(Doctoral dissertation, Program Studi Pendidikan Bahasa Inggris FBS-

UKSW).

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APPENDICES

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APPENDIX A

QUESTIONNAIRE

Introduction

This questionnaire is designed to investigate using code-mixing between Thai and

English in Line application. Please be assured that the information in response to

the questionnaire will be strictly confidential and used for the sole purpose of this

study.

Part 1: Personal data

Please answer the following questions.

1. Age

18-24 years old

25-34 years old

35+ years old

2. Gender

Female Male

3. Nationality

Thai Other………….

4. Academic years

First year Second year

5. Do you use Line application?

Yes No

6. In what language have you used in Line application?

Thai English

Thai and English

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Part 2:

Please read the following statement carefully and mark (x) in one of the columns

which best describes your degree of agreement or disagreement.

No.

Item description

Strongly

agree

Agree

Uncertain

Disagree

Strongly

disagree

1. Mixing of Thai and


provides opportunities to

learn English.

2. I find English word is

easy to understand.


English in Line chat is a

sign of globalization.

4. It draws my attention

when seeing mixing of

Thai and English

languages in Line chat.

5. I think mixing Thai and

English in Line chat will

‘distort’ Thai language.

6. Mixing Thai and English

in Line chat may make

monolinguals

disadvantaged.

7. I will continue to read

and write in that way.

8. I feel comfortable with

mixing Thai and English

in Line chat.

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33

Part 2 Continued

9. It confuses me when

interlocutor mixes Thai

and English in Line chat.

10. Using Thai in Line chat

increases my chances of

understanding the

messages.

11. Using English in Line

chat increases my

chances of

understanding the

messages.



increases my chances of

understanding the

messages.

13. Those who mix Thai and

English in Line chat do

so to show off.



belong to a higher socio-

economic class.


English dissociate

themselves from Thai

culture.

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Part 3:

Please read the following statement carefully and mark (x) in one of the columns

which best describes your degree of agreement or disagreement.

No.

Item description

Strongly

agree

Agree

Uncertain

Disagree

Strongly

disagree

1. Mixing Thai and

English in Line chat to

talk about taboo issues.

2. Mixing Thai and


express loyalty to

English.

3. Mixing Thai and


gain more prestige.

4. Mixing Thai and


because English is full

of academic, scientific

and technical terms.

5. Mixing Thai and


because do not know

the Thai equivalent.

6. Mixing Thai and


because English

contains abbreviations

and acronyms.

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Part3 Continued

7. Mixing Thai and


according to the

receiver of the message.

8. Mixing Thai and


express authentic

feelings.

9. Mixing Thai and


increase status towards

opposite sex.

10. Mixing Thai and


soften request or

strengthen command.

11. Mixing Thai and


convey message more

easily.

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BIOGRAPHY

Name Ms. Thittaya Wirojwaranurak

Date of Birth October 15, 1990

Educational Attainment

2013: Bachelor of Business Administration

(Accountancy), Kasetsart University

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attitudes of ceic students towards code-mixing in line

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