Application of google translate among third year students majoring in translation and interpreting felte ulis

VIETNAM NATIONAL UNIVERSITY, HANOI UNIVERSITY OF LANGUAGES AND INTERNATIONAL STUDIES FACULTY OF ENGLISH LANGUAGE TEACHER EDUCATION GRADUATION PAPER APPLICATION OF GOOGLE TRANSLATE AMON

VIETNAM NATIONAL UNIVERSITY, HANOI

UNIVERSITY OF LANGUAGES AND INTERNATIONAL STUDIES

FACULTY OF ENGLISH LANGUAGE TEACHER EDUCATION

GRADUATION PAPER APPLICATION OF GOOGLE TRANSLATE AMONG

THIRD-YEAR STUDENTS MAJORING IN

TRANSLATION AND INTERPRETING, FELTE, ULIS

Supervisor: Vương Thị Thanh Nhàn Student: Lê Diệu Linh

Course: QH2016.F1.E22

HÀ NỘI – 2020

ĐẠI HỌC QUỐC GIA HÀ NỘI

TRƯỜNG ĐẠI HỌC NGOẠI NGỮ KHOA SƯ PHẠM TIẾNG ANH

KHÓA LUẬN TỐT NGHIỆP ỨNG DỤNG GOOGLE DỊCH CỦA SINH VIÊN NĂM

BA CHUYÊN NGÀNH BIÊN PHIÊN DỊCH, KHOA

Signature of Approval

_

Hanoi, June 9, 2020

ACCEPTANCE

I hereby state that I: Lê Diệu Linh, Class QH2016.F1.E22 being a candidate for

the degree of Bachelor of Arts (programme) accept the requirements of the College relating to the retention and use of Bachelor’s Graduation Paper deposited in the library

In terms of these conditions, I agree that the origin of my paper deposited in the library should be accessible for the purposes of study and research, in accordance with the normal conditions established by the librarian for the care, loan or reproduction of the paper

Signature

Lê Diệu Linh

Date: May 11, 2020

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ACKNOWLEDGEMENTS

This part is dedicated to the following people without whom I could not have completed this graduation paper

First of all, I would like to express my deepest and most sincere gratitude to

my thesis supervisor and former teacher, Ms Vuong Thi Thanh Nhan for her enthusiasm, motivation and profound knowledge Her invaluable guidance has considerably assisted me throughout this research

Secondly, I would like to thank 104 third-year students majoring in Translation and Interpreting from six mainstream classes of class QH2017.F1 in FELTE, ULIS, whose participation is significant in this research paper

My completion of this graduation paper could not have been accomplished without the support of my classmates from QH2016.E22, especially my best friend Phuong Ha, who has always given me advice and stimulation during the writing period

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ABSTRACT

The purpose of this research paper is to examine the application of Google Translate among third-year students majoring in Translation and Interpreting, FELTE, ULIS From the perspective of the researcher, thanks to the advent of technology, students’ translation procedures have been affected to some extent By dint of survey questionnaires and semi-structured interviews, along with the participation of 104 third-year students, this study investigates that GT plays an integral part in learning process of these students at university Moreover, GT has both positive and negative influences on students’ both translation process and translation quality Specifically, GT helps improve students’ translation speed, translation accuracy, technical words, idioms and simple texts Meanwhile, translation naturalness is not supported remarkably by GT Based on the findings, several recommendations were proposed to help maximize its positive effects and

minimize all the possible limitations

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ACKNOWLEDGEMENTS……… i

ABSTRACT……… ii

TABLE OF CONTENT……… iii

LIST OF ABBRIEVATIONS……… vi

LIST OF TABLES AND FIGURES……… vii

PART I: INTRODUCTION……… 1

1 Statement of research problems & rationale for the study 1

2 Research objectives and research questions 3

3 Significance of the study 3

4 Scope of the study 4

5 Organization of the research paper 5

PART II: DEVELOPMENT 6

CHAPTER 1: LITERATURE REVIEW 6

1.1 Overview about Translation 6

1.1.1 Definition of Translation 6

1.1.2 Translation Process 8

1.2 Overview about Machine Translation (MT) and Computer-aided Translation (CAT) 9

1.3 Overview about Google Translate 11

1.3.1 Introduction about Google Translate 11

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1.3.2 Working process of Google Translate 13

1.3.3 Pros and Cons of Google Translate 14

1.3.3.1 Pros of GT 14

1.3.3.2 Cons of GT 14

CHAPTER 2: RESEARCH METHODOLOGY 16

2.1 Sampling method 16

2.2 Participants of the study 16

2.3 Data collection instruments 17

2.3.1 Questionnaire 17

2.3.2 Semi-structured interview 19

2.4 Data collection procedure 19

2.4.1 Collecting data from questionnaires ,.19

2.4.2 Collecting data from semi-structured interviews 20

2.5 Data analysis procedure 20

2.5.1 Data from questionnaires 20

2.5.2 Data from interviews 22

CHAPTER 3: RESULTS AND DISCUSSION 23

3.1 Frequency of students’ use of GT 23

3.2 Effects of GT……… .24

3.2.1 Students’ perspectives about GT 24

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3.2.2 GT’s supports during translation process 26

3.2.3 GT’s supports on translation quality 27

3.3 Recommendations…… 35

PART III: CONCLUSION 38

1 Summary of the findings 38

2 Limitations of the study 39

3 Suggestions for future studies 39

REFERENCES 40

APPENDICES 44

APPENDIX 1: Questionnaire 44

APPENDIX 2: Interview Questions 49

Figure 3 GT’s effects during translation process

Figure 4 Students’ evaluation on GT’s raw

output

Figure 5 Students’ evaluation on their final

translation when using GT

Figure 6 Students’ opinions in using GT in future

career

Figure 7 Students’ recommendations for the

effective use of GT

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PART I: INTRODUCTION

This part briefly introduces the following aspects of this research paper: Statement

of research problems and rationale for the study, (2) Research objectives and Research questions, (3) Significance of the study, (4) Scope of the study and (5) Organization of the research paper

1 Statement of research problems & rationale for the study

Translation, a vital means of exchanging information among different countries and cultures, performs a prominent role in human communication In view of the growing demand for translation in the world, pressing needs emerge to incorporate translation practice into the curricula among universities, and give student translations practical experience that satisfies the needs of workplace after graduation Translation in the modern era also involves the application of technology It is indubitable that by dint of the technology, translation industry worldwide has altered significantly As time passes, increasingly qualified translations have been delivered with less time and less labor Nonetheless, translation with the assistance of technology is still a new phenomenon and has yet been investigated widely in Vietnam, particularly ULIS, VNU, which facilitates the conduct of this research paper

The demand for qualified translators is increasing considerably, and numerous universities all over the world consequently provide translation courses According to Caminade and Pym (1995), as cited in Munday (2001), translation courses have been offered to four-year undergraduate and postgraduate in at least

250 university-level institutions in more than sixty nations University of Languages and International Studies, a renowned one in Vietnam noticeable for training translators also endeavors to enhance and integrate different instructional methods to reinforce undergraduates' translation capability Students majoring in

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Translation and Interpreting are entitled to intensive training from the first semester of the third year, which establishes a concrete foundation for them Students when participating in training are assigned to translate texts in the course-book “Translation Practice” The book includes five units with different topics so students can be provided with theme-based vocabulary and translation skills in different contexts Students will be assessed in the mid-term exam and end-of-term exam with some of the texts taken from the course-book Therefore, translating texts in this course-book definitely strengthen students’ translation skills, enrich their background knowledge and also contributes significantly to their translation performance The researcher when taking part in this course realizes that doing the translation exercise in the course book could be assisted by computer and Internet, one of which is Google Translate

In terms of Translation studies in general, there have been a variety of outstanding studies For instance, the research paper “Translation Studies: An overview” (Cristina, 2007) introduced the major schools and approaches constituting Translation Studies to those who are commencing their studies in this field Hadley (2014) published his study “Theorizing in unfamiliar contexts: New directions in Translation Studies”, which proposed the idea that the understandings

of translation practice have been modified over time, and varied considerably across cultures Moreover, the research paper “The Impact of Translation Technologies on the Process and Product of Translation” (Doherty, 2014) scrutinized the gains and effects that technologies yielded during translation process However, of all the conduct studies, there has not been much intensive research concerning the application of Google Translate in students’ training, especially when Google Translate has evolved to a great extent Therefore, the

researcher decides to conduct this research about the “APPLICATION OF GOOGLE TRANSLATE AMONG THIRD-YEAR STUDENTS MAJORING

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IN TRANSLATION AND INTERPRETING, FELTE, ULIS” to investigate

further into this matter

2 Research objectives and research questions

This paper aims to investigate the extent to which third-year students majoring in Translation and Interpreting at FELTE, ULIS apply Google Translate

in Translation Practice Secondly, this paper also focuses on examining the positive results of the application on students’ performance in Translation Practice

as well as the negative ones if excessive application takes place Finally, from the thorough analysis, some suggestions and recommendations would be proposed to promote the positive use of Google Translate in Translation Practice

The aforementioned objectives can be summarized by the following research questions:

- To what extent do students use Google Translate in their translation process?

- To what extent does Google Translate support students in their translation process?

- What are some recommendations for the effective use of Google Translate

in the translation process?

3 Significance of the study

With this study, the researcher expects to gain and provide a profound understanding about the application of Google Translate among students majoring

in Translation and Interpreting at FELTE, ULIS in “Translation Practice” The study would be of great importance for the students’ improvement in their translation performance with the help of machine This research paper would be a lucrative source of information for teachers and students to enhance the quality of Translation courses in general and Translation Practice in particular at FELTE,

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ULIS Finally, although the study is on a small scale, the researcher hopes that it could become a vital resource for other researchers with the same interest in the topic related to machine-assisted translation to use for their future investigations

4 Scope of the study

This research focuses on students majoring in Translation and Interpreting

at FELTE, ULIS, VNU and their utilization of Google Translate for “Translation Practice” Specifically, the target population of the study is third-year mainstream students of Translation and Interpreting major in the school year of 2019-2020 The researcher decides to choose third-year students because this is the time they begin to get used to translation training, starting with “Translation Practice” Mainstream students are chosen to be the target population since the results gained from their responses may be the most general Therefore, conducting research with these students may produce noticeable results when they carry out translation exercises in “Translation Practice” Due to the time limit and restrained resources, the researcher will conduct research on four third-year mainstream classes majoring in Translation and Interpreting

This research paper also focuses mainly on Translation Practice as the course-book used for training is well-designed with six common topics, namely Population, Environment, Education, Vietnam, Economy and Medicine, along with various text types of appropriate length for translation practice at introductory level At the end of the course, students can develop background knowledge of topics of common interest and build up their own theme-based glossary of common topics In terms of skills, students may be able to translate simply-structured phrases, sentences and paragraphs from the source language to the target language without loss of meaning as well as analyze and edit source and target texts of average level of difficulty Considering the content and objectives

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of the course book, it is possible that students may employ GT to assist them during their translation process

5 Organization of the research paper

In this research paper, there are a total of three parts

Part I: Introduction This part outlines the research problems and

rationale of the study, research objectives, significance and scope of the study as well as the organization of chapters

Part II: Development This part contains three smaller chapters:

Chapter 1: Literature review This chapter presents a review of relevant

literature on the researched topic Three concepts related to the study namely

“translation”, “machine translation” “Google Translate” are illustrated in this chapter

Chapter 2: Research methodology This chapter demonstrates the target

population of the study, types of data collection instruments, and the data collection and analysis procedures

Chapter 3: Results and discussion In this chapter, the results and findings

from the qualitative and quantitative analysis are provided

Part III: Conclusion This part summarizes the main points discussed in

this study The implications, limitations of this research as well as recommendations are also specified in this final part

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PART II: DEVELOPMENT

CHAPTER 1: LITERATURE REVIEW

This first chapter in the development of the research provides an in-depth look at the theoretical background of the study In this chapter, key concepts of Translation, Machine Translation and Google Translate will be elaborated, along with the analysis of several previous research in the same field

1.1 Overview about Translation

1.1.1 Definition of Translation

Torop (2002) opined that translation, as a process of delivering information from one language into another, adheres to the sociocultural language of a specific context and the researcher also depicted translation process as a boundary-crossing between two languages Clandinin and Connelly (2000) advocated the view of Lapadat and Lindsay (1999) that translation is basically a conversational process

of switching field texts to research texts through making decisions at various stages to acquire equivalence in implications and interpretations

Larson (1984) stated that translation “consists of transferring the meaning

of source language into receptor language This is done by going from the form of the first language to the form of a second language by way of semantic structure It

is meaning which is transferred and must be held constant Only the forms change Translation consists of studying the source language text (lexicon, grammatical structure, communication situation, and cultural context); analyzing it in order to determine its meaning; then reconstructing this SAME meaning using the lexicon and grammatical structure which are appropriate in the receptor language and its cultural context.”

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In his book “Translation and Translating: Theory and Practice”, Bell (1991) defined Translation as “the expression in another language (target language) of what has been expressed in one language (source language), preserving semantic and stylistic equivalencies.”

In another book “Approaches to Translation”, “Translation is considered as the process of “rendering the meaning of a text into another language in the way that the author intended the text” (Newmark, 1988, 2001, p.5) In his opinion, a translation process should commence with a detailed analysis of the source text, such as the intention of the text and the translator, its readership, quality of the text, text types and so on Furthermore, Newmark also regards translation as “a craft consisting in the attempt to replace a written message and/or statement in one language by the same message and/or statement in another language” (Newmark,

1982, 2001, p.7)

In the book “Constructing Cultures: Essays on Literary Translation”, Susan Bassnett was in favor of Andre Lefevere and considers translation not simply as a linguistic transfer but a cross-cultural activity Together with Lefevere, she identified that “there are different types of faithfulness that may be adequate in different situations (Bassnett & Lefevere, 1998, 2000, p.3)”

Definitions of Translation presented by some experts and researchers above bear some resemblance It can be concluded that translation is a process transmitting message from source language to target language It is impossible to consistently translate literally or idiomatically so translation process is a mixture

of literal and idiomatic forms of language A translator also has to take into consideration the context and the culture in the target text, so that the message can

be acknowledged by the readers Therefore, when assessing a translation, the message and accuracy of the information meant to be revealed in the source

of expression Douglas Robinson believed that for some translators, “the entire purpose of translation is achieving equivalence The target text must match the source text as fully as possible” (p.73)

In the linguistic model, translation is viewed as a substitution of every component in SL by its TL equivalent component It considers translation as a basic transcoding of textual units in terms of phonology, punctuation, and lexicology This approach makes use of Halliday's (1961) scale and category grammar in which the structure of language is viewed as a set of scales and categories working at various levels (phonic, linguistic, lexical, realistic)

Since the context is not considered, the substitution of units usually fails to produce adequate TL texts Translation is not only a mechanical replacement of lexical and grammatical units from SL into TL Therefore, linguistic model cannot

be seen as a representation of translation process which pursues an appropriate rendering of ST into TL as it does not deal with the whole text or the context of the text

Tou (1989) proposed a translation process including four stages: the study

of meaning in terms of cultural context, lexicon and grammar, the discovery of

1.2 Machine translation (MT) and Computer-aided translation (CAT)

Before the twenty-first century, translation studies were formed, including translation methods, translation procedures, equivalence in translation and translation assessment criteria This period also marked the introduction of computer-aided translation (CAT) and machine translation (MT) CAT tools and

MT have presented various remarkable alterations in the way translation practices were performed Translators can utilize computers and CAT tools to produce much faster and high quality translations In other words, the “printed culture” gradually gave way to the “screen culture” (Olivia Craciunescu, Constanza Gerding-Salas & Susan Stringer-O'Keeffe, 2004)

According to Hutchins (1992), Machine Translation (MT) is the name for computerized systems accounting for producing translations from one language into another, with or without human assistance MT is a technology that automatically translates text using term bases and advanced grammatical, syntactic and semantic analysis techniques MT is a full automatic translation process

Computer-aided/assisted translation (CAT) is the use of computer software

to assist a human translator in the translation process CAT is also called automatic translation In CAT, translators are responsible for the process of translation, but they can make use of a variety of computerized tools to help them complete the task and increase their productivity (Bowker, 2002) Based on the definitions, it is clearly seen that (MT) refers to translation produced principally

semi-10

by computer systems, while CAT only serves as an assistant to a human translator

in his/her translation process

Machine translation is ideal when dealing with a large amount of content requiring fast translation but just a general meaning There is a variety of free machine translation software available online, one of which is Google Translate While still far from perfect, machine translation is ceaselessly advancing One of these advances is neural machine translation, in which a large neural network is developed to maximize translation performance

There are three types of machine translation, which are Rule-based MT,

Statistical MT, Hybrid MT

Rule-based machine translation (RBMT) systems apply a large collection of

linguistic rules, manually developed over time by experts, in three different stages: analysis, transfer and generation The software analyzes text and creates a transitional representation from which target text is generated This process requires extensive lexicons with morphological, syntactic, and semantic information, and large sets of rules The software uses these complex rule sets and then transfers the grammatical structure of the ST into the TT Users can contribute to the improvement of the translation quality by adding their

terminology into the translation process

Statistical Machine Translation (SMT) systems use computer algorithms

looking at every possible way of joining smaller pieces of text together, with a view to producing the best translation According to Weaver (1949), SMT uses statistical translation models whose parameters are derived from the analysis of monolingual and bilingual corpora Developing statistical translation models is a not a matter of time, but the technology depends crucially on existing multilingual corpora It requires a minimum of 2 million words for a specific domain and even

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more for general language SMT ensures better translation quality but most companies do not have such large amounts of existing multilingual corpora to build the adequate translation models Moreover, SMT is CPU intensive and requires a broad equipment setup to run translation models for average

performance levels

In order to overcome quality and time limitations, the core technology of rule-based machine translation is integrated into statistical machine translation technology, which is referred to as “Hybrid” machine translation The traditional rule-based MT providing high out-of-domain quality and being predictable needs

to be equipped with dictionary-based customization to reassure improved quality and compliance with corporate terminology However, the customization needed

is seen to be long and expensive Statistical MT provides outstanding quality with large and qualified corpora While the translation sounds fluent, it is neither predictable nor consistent A combination of the two technologies will do translators good

1.3 Overview about Google Translate (GT)

1.3.1 Introduction about GT

Google Translate (GT) is a free multilingual machine translation It utilizes Statistical Machine Translation (SMT) to translate texts SMT sees translating as a machine learning problem Lopez (2008) pointed out that “SMT treats translation

as a machine learning problem This means that we apply a learning algorithm to a large body of previously translated text The learner is then able translate previously unseen sentences.” GT learned from United Nations and European Parliament transcripts when it was launched in April of 2006 GT had to translate the required text into English before translating into the selected language As

In November 2016, Google Translate system was transitioned into which is called “Neural Machine Translation” Brownlee (2017) clarified that NMT uses neural network models to learn a statistical model It makes use of Deep Learning techniques to translate the whole sentences at a time and ensure higher contextual accuracy Instead of translating small pieces like SMT, NMT translates whole sentences at a time With the end-to-end learning system installed on NMT, GT will definitely improve over time as it learns to produce better, more natural translations (Turovsky, 2016)

In 2018, GT translates more than 100 billion words a day and supports 103 languages Not all of the functions are supported in all of these, and not all of them use NMT The merits of Google Translate over other machine translators are that

it is free to use and easily accessible via the different features

Google Translate can translate multiple forms including text, images, speech, and videos Specifically, GT can carry out Written Words Translation, Website Translation, Document Translation, Speech Translation, Mobile App Translation, Image Translation and Handwritten Translation GT provides the pronunciation, dictionary, and listening to translation for most of its features Therefore, presently GT provides functional assistance to translators to produce qualified translation

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1.3.2 Working process of GT

In April 2006, GT was launched with a statistical machine translation

engine GT does not translate from one language to another directly Instead, it translates first to English and then to the target language (Blanchon, Boitet, Seligman & Bellynck, 2010)

When producing a translation, GT inspects patterns in hundreds of millions

of documents to help select the best translation By identifying patterns in documents that have already been translated by human translators, GT makes intelligent guesses as to what a suitable translation should be

In September 2016, a research team at Google led by the software engineer Harold Gilchrist announced the development of the Google Neural Machine Translation system (GNMT) to enhance fluency and accuracy in GT and in November announced that GT would switch to GNMT

GT's NMT system adopts a large artificial neural network capable of deep learning GNMT enhances the quality of translation as it uses an example-based machine translation (EBMT) method in which the system "learns from millions of examples It translates "whole sentences at a time, rather than just piece by piece

It uses this broader context to help it figure out the most relevant translation, which it then rearranges and adjusts to be more like a human speaking with proper grammar” (Turovsky, 2016) The GNMT network is able to produce interlingual machine translation, which delivers the "semantics of the sentence rather than simply memorizing phrase-to-phrase translations", and the system does not formulate its own global language, but uses "the commonality found in between many languages" (McDonald, 2017)

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GNMT can translate directly from one language to another, which outclasses the previous versions of GT which first translated to English and then to the target language

1.3.3 Pros and Cons of GT

1.3.3.1 Pros of GT

First of all, GT is free Users can translate what they need without paying any fees Secondly, Google Translate is really speedy In fact, human translators are incapable of competing with the speed and the quantity of translations that GT can generate Thirdly, despite the fact that GT isn't as reliable as human translation, it can give generally precise translation McGuire (2018) implied that

GT can translate text with the general use of words and phrases in a consistent manner Due to its identical choice of words without considering the flexibility of opting for alternative expressions, it yields relatively similar translation to human translation in terms of formality, referential cohesion, and conceptual cohesion (Li, Graesser & Cai, 2018) Google carried out a test that asked native speakers of each language to rate the translation on a scale between 0 and 6, and GT scored 5.43 on average (McGuire, 2018)

1.3.3.2 Cons of GT

The accuracy of GT’s outputs varies greatly between languages GT produces better results in some language pairs than others According to Freitas & Liu (2017), Western languages such as English and Spanish are typically accurate, but the accuracy of African languages is often the most insufficient, followed by Asian and European languages Moreover, GT performs properly especially when English is the target language and the source language is from the European Union, in view of the prominence of translated EU Parliament notes

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Moreover, in its Written Words Translation function, there is a word limit

on the amount of text that can be translated at once Moreover, MT often does not recognize the double meanings of a word A word in the source language may have different meanings in the translated language; thus, ambiguity in translation

or mistranslation can lead to misunderstanding Furthermore, grammatical errors remain a major limitation to the accuracy of Google Translate

The researcher selects definitions of the key terms in this study from distinguished researchers and theorists in different periods of time in order to gain both extensive and intensive knowledge about the research topic and also to prove that the research field is of great concern among researchers and worth studying in different aspects In-depth observation of previous research has indicated that the application of Google Translate among students beginning to study translation as well as the techniques to apply GT in translation training have yet been studied widely, which forces the conduct of this research paper

in terms of both cost and efforts as the list of classes was easily accessible All the names of the classes were anonymized in this research paper and will be labeled from First to Fourth only

2.2 Participants of the study

A quantity of 104 third-year students from four mainstream classes majoring in Translation and Interpreting, ULIS, VNU, Hanoi were chosen to be participants of the study, who are getting used to translation practice More importantly, under the pressure of employment after graduation, most of them are acutely aware of their vocational orientation, always eager for things that help maximize their translation competence On the contrary, freshman and second-year students seem to take less notice of those technological aids as they are kinds

of new to translation and have yet undergone the basic training That is the reason why this study gives a prime focus to third-year students in the major, specifically mainstream students

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Table 1: Number of third-year mainstream student translators

Number of students Actual number of

students completing the questionnaire

2.3 Data collection instruments

To collect data for this paper, the researcher employed two types of data collection instruments, which were questionnaire (for quantitative data) and semi-structured interviews (for qualitative data)

2.3.1 Questionnaire

Questionnaire was used as a means of collecting data due to its advantages Questionnaires are a very conducive method of collecting useful comparable data from a large quantity of individuals Using questionnaire provided fast and convenient data collection, since the participants only had to read and tick the options or write short answers (Wallace, 1998) The researcher designed a questionnaire including 10 closed questions and 3 open-ended follow-up questions

to answer the first two research questions:

reader-2.3.2 Semi-structured interview

Along with questionnaire, semi-structured interview was adopted for the information collection for this research since it permitted the researcher to gain detailed information that cannot be obtained through observation Because of its interactive nature, additional information could be exploited when the initial answers fail to provide a clear idea A set of open-ended questions was designed

by the researcher for the interview in order to get answers from the participants Apart from the prepared question as the outline for the researcher to carry out the interviews, there were more follow-up questions based on the situation The researcher included six main questions in the interviews with a view to answering the two research questions, particularly the latter question:

- To what extent does Google Translate support students in their translation process?

- What are some recommendations for the effective use of Google Translate

in the translation process?

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Four representatives were chosen, all of whom are monitors from each class

to participate in the interviews The reason was that it was more effortless to contact them, and all the monitors, as a leader group, cooperated actively in the interviews They could also summarize and supply general information about their class if needed Indeed, the respondents did not only answer the given questions, but also provided other necessary information related to the field for the sake of the researcher’s data analysis

2.4 Data collection procedure

2.4.1 Collecting data from questionnaires

The procedure consisted of three steps as follows:

Stage 1: Piloting the questionnaire In this stage, the researchers randomly

chose 5 to 10 students from the sample and gave them the survey questionnaires to complete This stage aims to address any problems related to the wording that may cause misunderstandings, and also to confirm the extent of relevance of the additional items written by the researcher to the student translators’ experience

Stage 2: Distributing the questionnaires The researcher contacted the

teachers of four classes in advance to ask for permission to distribute the questionnaires in the class and arrange the appointments with the teachers At the appointment, the researcher first acknowledged the students about the aims of her research in general and the questionnaires in particular Then the researcher asked for consent from the classes before giving them the questionnaires Intensive instructions were provided to the students before and during their questionnaire completion to avoid misunderstanding and unproductive answers

Stage 3: Collecting the questionnaires The researcher collected the

questionnaires from four classes and numbered them so as to keep track of the completed questionnaires and to easily recheck the student translators’ answers