In house training 151114 qualitative research

Hiram Ting Huong Yiew

Qualitative Research and Procedures

In-House Training (2)

SEGi College Sarawak, Kuching

November 15, 2014

Organized by Sarawak Research Society

In Collaboration with SEGi College Sarawak1

AcknowledgementThe training instructor wishes to express his gratitude to

Prof Dr Ernest Cyril de Run and Prof Ramayah Thurasamy

for their guidance on the training and its contents.

In-House Training (2) – Qualitative Research

November 15, 2014

2

About MyselfProfile:

Hiram Ting Married to Rebecca Sii Father to Carlyne & Henna

Academia:

B. Com at Canterbury University, NZ Corporate MBA at UNIMAS PhD at UNIMAS (viva candidature)

Employment:

Youth & social worker in a Christian organization PT lecturer at Swinburne University Sarawak PT Msc lecturer at Open University Malaysia PT MBA lecturer at SEGi College Sarawak Research tutor under Zamalah contract RA/RO of consultancy projects

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Research Experience (2012-2014):

10 conference proceedings (local and international) 5 published journal articles (local and international) 6 manuscripts under review, 5 working papers Invited speaker at graduate seminar in 2013 Assisting 3 consultancy projects Reviewing of manuscripts and theses/drafts

Progress Recognition (2012-2014):

3 best paper awards (IBBC2012, APMMC2013, IBBC2014) Silver and Bronze awards in R&D Exposition 2013 2 intellectual properties awards in 2013 Full Zamalah scholarship (2011-2013) DPI (internal grant) co-investigator (2011-2013) FRGS (MOHE grant) co-researcher (2014-2017)

About Myself (cont.)

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Contents

Research Paradigms

Research Designs

Research Approaches

Comparisons between

Qualitative and Quantitative

Approaches

Mixed-Methods Designs

Why Qualitative?

Overview of Qualitative

Research

Preliminary Decisions

Enumerators and Coders

Population and Sample

Sampling Strategy

Research Methods

Data Processing

Data Analysis

CAQDAS

Findings and Discussions

Potential Errors/Bias

Introduction to ATLAS.ti

(Afternoon session)

7

“… we shall never understand the complex reality of

organizations if we persist in studying them from a

distance, in large samples with gross, cross-sectional

measures. We learn how birds fly by studying them

one at a time, not by scanning them on radar screens”.

Henry Mintzberg

8

Research Paradigms

Paradigm framework is made up by philosophy, ontology,

epistemology and methodology. Epistemology is the philosophy

of knowledge or how we come to know (Trochim, 2000).

Understanding the differences in epistemology among research

paradigms begins primarily as a philosophical exercise to address

the question of whether there is one knowable reality or that

there are multiple realities (Olson,1995)

The underlying belief system of the researcher (ontological

assumptions) largely defines the choice of method

(methodology) (Dobson, 2002)

9

Research Paradigms (cont.)

In the positivist paradigm, the object of study is independent of

researchers; knowledge is discovered and verified through direct

observations or measurements of phenomena; facts are

established by taking apart a phenomenon to examine its

component parts.

An alternative view, the naturalist or constructivist view, is that

knowledge is established through the meanings attached to the

phenomena studied; researchers interact with the subjects of

study to obtain data; inquiry changes both researcher and

subject; and knowledge is context and time dependent (Coll &

Chapman, 2000; Cousins, 2002).

10

Research Paradigms (cont.)

Researchers generally align with one of three research paradigms

(Teddlie & Tashakkori, 2009): (a) a positivist paradigm

(quantitative researchers), (b) a constructivist paradigm

(qualitative researchers), or (c) a pragmatist paradigm (mixed-

methods researchers).

Pragmatism “rejects the either/or choices associated with the

paradigm wars, advocates for the use of mixed methods in

research, and acknowledges that the values of the researcher play

a large role in interpretation of results” (Tashakkori & Teddlie,

2003, p. 713). Researchers mix methods in ways that make the

most sense given their research questions, integrating qualitative

and quantitative approaches and data analysis procedures and

attempting “to open up inquiry to all possibilities while tying that

search to practical ends” (Maxcy, 2003, p. 86).

11

Research Designs

What is Research Design:

Procedures for collecting, analyzing, interpreting and reporting

data in research studies.

They are useful because they help guide the methods decisions

that researchers make.

Set the logic by which they make interpretations at the end of

their studies.

Research designs are generally categorized into exploratory,

descriptive and causal research design.

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Research Approaches

Qualitative vs. Quantitative

A qualitative study is defined as an inquiry process of

understanding a social or human problem, based on building a

complex, holistic picture, formed with words, reporting detailed

views of informants, and conducted in a natural setting.

Alternatively a quantitative study is an inquiry into a social or

human problem, based on testing a theory composed of

variables, measured with numbers, and analyzed with statistical

procedures, in order to determine whether the predictive

generalizations of the theory hold true (Creswell, 1994)

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Research Approaches (cont.)

Inductive vs. Deductive

When using inductive approach, Yin (2003) suggests that, where

you have made use of existing theory to formulate your research

question and objectives, you may also use the theoretical

propositions that helped you do this as a means to devise a

framework to help you to organize and direct your data analysis.

The alternative to the deductive approach is to start to collect

data and then explore them to see which themes or issues to

follow up and concentrate on (e.g. Glaser and Strauss, 1967;

Strauss and Corbin 2008). This is also referred to as a grounded

approach because of the nature of the theory or explanation that

emerges as a result of the research process.

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Comparison between Approaches

15

Qualitative Research: Quantitative Research:

Action research

Case study research

Ethnography

Grounded theory

Semiotics

Discourse analysis

Hermeneutics

Narrative and metaphor

Surveys

Laboratory experiments

Simulation

Mathematical modeling

Structured equation modeling

Statistical analysis

Econometrics

Mixed-Methods Designs

Mixed-methods research is a combination of “elements of

qualitative and quantitative research approaches (e.g., use of

qualitative and quantitative view points, data collection, analysis,

inference techniques) for the purposes of breadth and depth of

understanding and corroboration” (p. 123).

Mixed-methods research has several purposes and can address

many types of research questions. Mixed methods can illustrate

and explain quantitative findings, describe both process and

product, check reasons for unexpected effects, develop the basis

for instruments, show the extent of generality, validate and

triangulate other data, and fulfill social or political purposes

(Krathwohl, 2009).

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Mixed-Methods Designs (cont.)

Creswell and Plano Clark (2011) described six possible designs.

Convergent Design: Quantitative and qualitative data are

collected concurrently, analyzed separately, and then merged.

Explanatory Design: Quantitative data are collected and

analyzed first; results are used to inform follow-up qualitative

data collection.

Exploratory Design: Qualitative data are collected and

analyzed first, results are used to inform follow-up quantitative

data collection.

Embedded Design: Qualitative and quantitative data can be

collected sequentially, concurrently, or both. One form of

data is embedded within another.

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Creswell and Plano Clark (2011) described six possible designs.

Transformative Design: The researcher frames the study

within a transformative theoretical perspective. Qualitative and

quantitative data can be collected concurrently, sequentially,

or both.

Multiphase Design: Both sequential and concurrent strands

are included in a study over a period of time (e.g., in a large-

scale evaluation).

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Priority Decision

Quantitative Qualitative

Qualitative Preliminary

Qual QUANT

Quantitative Preliminary

Quant QUAL

Qualitative follow-up

QUANT Qual

Quantitative follow-up

QUAL Quant

Comp

Prelim

Comp

Follow-up

Sequence

Decision

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Why Qualitative

It is useful when:

It is difficult to develop specific and actionable decision,

statements or research objectives.

The research objective is to develop a detailed and in-depth

understanding of some phenomena.

The research objective is to learn how a phenomenon occurs in

its natural setting or to learn how to express some concept in

colloquial terms.

The behavior the researcher is studying is particularly context-

dependent.

A fresh approach to studying the problem is needed.

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Why Qualitative (cont.)

Qualitative research methods are designed to help researchers

understand people and what they say and do.

They allow a researcher to see and understand the context within

which actions and decisions take place.

It is the context that helps to “explain” why someone said

something or acted the way they did.

Also by talking to people, or reading what they have written, we

can find out what they are or were thinking.

Types of questions: What is happening here? Why is it

happening? How has it come to happen this way? When did it

happen?

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Overview of Qualitative Research

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Written Record(Thesis, book, report, article ...)

Data Analysis Approach(Hermeneutics, semiotics,

narrative analysis . ..)

Data Collection Technique(interviews, participant

observation, documents)

Research Method(action research, case study,

ethnography, grounded theory ...)

Philosophical Assumptions(positivist, interpretive, critical)

Overview of Qualitative Research

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Overview of Qualitative Research (cont.)

1. Identify and diagnose the

problem

2. Generate a programmatic

solution to solve problem

3. Design and test intervention to

solve the problem

4. Ensure results are used

5. Disseminate results

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Preliminary Decision

Descriptive of rules and systematic procedures are necessary for

the validation of qualitative research (Kolbe & Burnett, 1991).

1. Problem and Propositions

2. Sampling decisions

3. Research method and instrument design

4. Pilot study/pre-test (Dicicco-Bloom & Crabtree, 2006)

5. Enumerators, transcribers, coders and translators are

carefully selected and/or trained (Hemsley, 2000).

6. Data processing and ethic considerations

7. Dealing with potential errors/bias (Childers & Skinner, 1985;

Steele, Schwendig & Kilpatrick, 1992)

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Enumerators/Coders

Inexperienced enumerators all started at about the same level

and thus could be trained together or separately (Dijkstra, 1983)

but they can commit mistakes. Experienced enumerators would

perform well but cost more, and would be much more diverse.

Moreover, young adults are more flexible in terms of time and

pliable in intellectual capabilities. Females in their young

adulthood could easily stabilize possible confounders of gender,

age and language differences (Moerman, 2010).

Consistency must be preserved across the enumerators while

generating productive discussion during interviewing process.

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Enumerators/Coders (cont.)

Enumerators who interview are encouraged to transcribe the

recorded interviews due to their familiarity with the topics

discussed during interview sessions.

Translators and back-translators should not be the same persons.

Enumerators/transcribers are also encouraged to be

coders/judges due to their familiarity with the topics.

Training and stringent procedures are mandatory to ensure the

transcribing and coding behaviours are consistent and

appropriate.

Do you have/need enumerators/coders? Who should be your

enumerators/coders? Can they do it?

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Population and Sample

Stake (1994) elucidates that generalization is not the criteria for

case selection in qualitative study; rather the replication of each

case that predicts similar results or patterns of findings is what

matters.

Eisenhardt (1989), Lincoln and Guba (1985) advocate that cases

and respondents should be added until data saturation or

replication is obtained or the point of redundancy is arrived at.

As far as the sample size is concerned, there are no clear guides

as to how many cases or respondents should be included in

qualitative studies (Patton, 1990; Perry, 1998).

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Population and Sample (cont.)

Eisenhardt (1989) suggests four to ten cases to achieve credible

purpose.

Hedges (1985) advocates four to six cases for a serious project

while Miles and Huberman (1994) suggest two to four cases as

the minimum and fifteen as the maximum.

Ritchie, Lewis and Elam (2003) state that qualitative samples

often lie under 50 respondents while Bertaux (1981) asserts that

fifteen is the smallest acceptable sample for all qualitative

research.

Perry (1998) recommends 30-50 interviews for any qualitative

studies at PhD level.

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Sampling Strategy

Non-probability sampling technique was adopted instead of

probability sampling technique as there is no way to estimate the

probability of any one person being included in the sample in a

large population, and no assurance is given that each person has

a chance of being included (Maxfield & Babbie, 2011).

It is also inappropriate to assume that human behaviours such as

beliefs, attitudes and intentions are normally distributed within

the population (Jackson, 1970).

Sampling strategies include purposive, quota, theoretical and

convenience sampling techniques.

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Research Methods

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Research Methods (cont.)

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Interview

Interview is one of the most useful tools of collecting data in

qualitative research (DeVillis, 1991; Zikmund et al., 2010) and

the most common type of research instrument employed in

mixed-method marketing studies (Hanson & Grimmer, 2007).

It is known to be able to offer great insight into consumer

behaviour (Kahan, 1990; Roller, 1987).

It is the recommendable qualitative means for studies related to

generation (Fountain & Lamb, 2011; Pennington-Gray et al.,

2010).

The purpose is to allow probes and obtain unrestricted

responses so as to identify important subjects and common

themes for subsequent analysis (Burns & Bush, 2005).

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Interview

Rubin and Rubin (2005, p. 13) elaborate that, “the depth,

details, and richness sought in interviews, what Clifford Geertz

(1973) called „thick description‟, are rooted in the interviewers‟

first-hand experiences and form the material that researchers

gather and synthesize. To get to this level of detail, depth, and

focus, researchers work out main questions, probes, and follow-

ups.”

The emphasis is to draw as much information as possible from

the respondents, listen patiently, and encourage them to speak

(Dicicco-Bloom & Crabtree, 2006).

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Types of Interview

Structured interviews

The use of pre-formulated questions, strictly regulated with

regard to the order of the questions, and sometimes regulated

with regard to the time available.

Semi-structured interviews

The use of some pre-formulated questions, but no strict

adherence to them. New questions might emerge during the

conversation.

Unstructured interviews

Few if any pre-formulated questions. In effect the interviewee

has free rein to say what they want. Often no set time limit.

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Focus Group

Most qualitative interviews are one-on-one, but group interviews

can be used as well.

The purpose of a focus group interview is to get collective views

on a certain defined topic of interest from a group of people

(normally 6-10) who are known to have had certain experiences.

Focus groups enable a researcher to elicit opinions, attitudes and

beliefs held by members of a group.

Moderator is key to focus group discussions.

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Case Study

Research cases can be used:

In exploratory research – to discover

In explanatory research – to test, to explain, or to compare

The purpose of case study research in business and management

is to use empirical evidence from real people in real

organizations to make an original contribution to knowledge.

Yin defines a case study as an empirical inquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident" (Yin, 1994, p. 13).

37


Ethnographic Research

The main purpose of ethnography is to obtain a deep

understanding of people and their culture.

One distinguishing feature is fieldwork.

Ethnographers immerse themselves in the life of people they

study (Lewis, 1985) and seek to place the phenomena studied in

their social and cultural context.

In ethnographic research, the context is what defines the

situation and makes it what it is.

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Ethnographic research Case study research

Time commitment – significant

length of time required in the field

(months/ year)

Time commitment – less time

required in the field (weeks / few

months at most)

Orientation of researcher – learns

from people

Orientation of researcher – studies

people

Type of data collected – interviews,

documents, notes from fieldwork

and participant observation

Type of data collected – mostly

interviews and documents

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Observation

Observation is when you are watching other people from the

outside as an observer.

Participant observation is when you not only observe people

doing things, but you participate to some extent in these activities

as well.

The main idea of participant observation is that you are talking

with people and interacting with them in an attempt to gain an

understanding of their beliefs and activities from the inside.

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Data Processing

Transcription

Good audio recording is crucial for the quality of the transcript,

and likewise the quality of the transcript itself is crucial for the

reliability of the analysis (Moerman, 2010; Potter & Hepburn,

2005).

Interviews are transcribed verbatim (Burns & Bush, 2005). It is

known to be time-consuming. Data sampling can be used where

only relevant sections are transcribed (Sauders et al., 2009)

In the process, an independent assistant can do a thorough

review of each completed transcript, matching it against the

recorded interview (Kurasaki, 2000).

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Data Processing (cont.)

Translation

Translation of questions into mother languages is encouraged in

order to draw reliable and valid information from respondents

who preferred using these languages (Malhorta & Birks, 2003).

Past studies emphasize the importance of establishing

appropriate translation procedure (Brislin, 1970; Rustogi,

Hensel & Burgers, 1996; Werner & Campbell, 1970).

Competent translators who are familiar with the content involved

in the source language materials are essential.

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Data Processing (cont.)

Back-translation

Back-translation is known to be one of the most widely used

translation techniques adopted in cross-cultural research

(Cateora, 1990; Usunier, 2000).

When translating the transcripts from English back to the source

language, different translators must be called upon to back-

translate the transcripts (Werner & Campbell, 1970).

Reliability or usability of English transcripts is determined by

looking at the agreement between the script with source language

and back-translated script.

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Data Analysis

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Narrative analysis

Semiotics

Content analysis

Conversation analysis

Discourse analysis

Grounded theory

Hermeneutics

Phenomenology

Literary criticism

Deconstruction

Coding

Series of events

Critical incidents

Decision-modelling

Cognitive maps

Analytic induction

Within case analysis

Cross case analysis

Pattern matching

Explanation building

Time series analysis

Data Analysis (cont.)

Responses to open-ended and probing questions were found in

free-flowing texts. One solution to annotating the main points for

coding purpose was to identify “idea units” based on where an

idea started and ended (Carey, Morgan, & Oxtoby, 1996).

Coding is the process by which themes are attached to segments

of data that depict what each segment is about (Charmaz, 2006).

“Codes are tags or labels for assigning units of meaning to the

descriptive or inferential information compiled during a study.

Codes are attached to “chunks” of varying size – words, phrases,

sentences, or whole paragraphs, connected or unconnected to a

specific setting” (Miles and Huberman, 1994).

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Analytic Induction

Analytic induction is a way to develop causal explanations of a

phenomenon from one or more cases.

First, define a phenomenon that requires explanation and

propose an explanation. Next, examine a case to see if the

explanation fits. If it does, then examine another case. An

explanation is accepted until a new case falsifies it.

When a case is found that doesn‟t fit, change the explanation (so

that you can include the new case) or redefine the phenomenon

(so that you can exclude the nuisance case).

Ideally the process continues until a universal explanation for all

known cases of a phenomenon is attained (Ryan & Bernard,

2000, p. 787).

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Grounded Theory

In the grounded theory of Strauss and Corbin (2008) the

disaggregation of data into units is called open coding, the

process of recognizing relationships between categories is

referred to as axial coding, and the integration of categories to

produce a theory is labeled selective coding.

The use of a grounded theory strategy will be time consuming,

intensive and reflective. Before you commit yourself to this

strategy, you will need to consider the time that you have to

conduct your research, the level of competence you will need,

your access to data, and the logistical implications of immersing

yourself in such an intensive approach to research.

Watch Grounded Theory by Graham R. Gibbs on Youtube.

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Hermeneutics

Hermeneutics suggests a way of understanding textual data.

Hermeneutics is primarily concerned with the meaning of a text

or text-analogue (an example of a text-analogue is an

organization, which the researcher comes to understand through

text or pictures).

The basic question in hermeneutics is: what is the meaning of

this text? (Radnitzky, 1970, p. 20)

If hermeneutic analysis were to be used in business and

management, the object of the interpretive effort could become

one of attempting to make sense of a company as a text-

analogue.

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Semiotics

Semiotics is primarily concerned with

the analysis of signs and symbols and

their meaning.

A sign or symbol is something that can

stand for something else.

The greatest use of semiotics has been

in marketing, consumer research and

information systems. This is because of

the pervasiveness of signs in marketing

communications (e.g. brand names,

logos, and advertising) and the

importance of “information” in

information systems

49


Content Analysis

Content analysis has long been used in qualitative marketing

studies (Wright & Barbour, 1975; Resnik & Stern, 1977;

Kassarjian, 1977).

It is particularly useful when data are collected through personal

or in-depth interview (Kassarjian, 1977), and for evaluating

various communication forms on human behaviours (Yale &

Gilly, 1988).

It includes frequency counts (Wilkinson, 2000), but at the same

time allows for exploratory analysis of qualitative data (Ryan &

Bernard, 2000).

50


Conversation Analysis

Conversation analysis looks at at the use of language by people

as a type of action, or as a skilled accomplishment by competent

actors

A key concept within conversation analysis is the idea of the

speaking turn. The principle of turn-taking in speech is claimed

to be a universal feature of all conversations

It does not presume the existence of fixed meanings in words

and idioms

Meanings are shaped in the context of the exchange

51


Discourse Analysis

Discourse analysis looks at the way texts are constructed and is

concerned with the social contexts within which the text is

embedded.

The word discourse refers to communication that goes back and

forth, like an argument or debate. All language can be treated as

a social interaction (there is always a speaker/writer and listener/

reader), but discourse analysis focuses mostly on language in use

- the use of naturally occurring language in speech and/or written

text.

Discourse analysis is concerned with actual instances of language

as used in communication.

52


Narrative Analysis

Narrative is defined by the Concise Oxford English Dictionary as

a “a spoken or written account of connected events; a story”

(Soanes & Stevenson, 2004)

Traditionally, a narrative requires a plot, as well as some

coherence. It has a linear structure, with a beginning, middle,

and end.

Narrative analysis is a qualitative approach to the interpretation

and analysis of qualitative data.

There are many different kinds of narrative analysis.

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Choosing a qualitative data analysis approach

Do you find the approach interesting?

Is the approach reasonably consistent with your own

philosophical assumptions about knowledge and reality?

Is the approach reasonably consistent with the research method

you employed?

Have you gathered the right quantity and quality of data for the

particular qualitative data analysis method?

Do you have a supervisor or some other faculty member who

can provide advice and guidance on the use of your preferred

approach?

54


Intercoder Agreement

Researchers have suggested using multiple coders to establish

high inter-coder reliability in content analysis of open-ended

interview data (Bernard, 1995, Kurasaki, 2000).

It is a measure of agreement between multiple coders about how

they code the themes and apply them to the data (Kurasaki,

2000).

Such joint agreement is used not only to measure the reliability

of the coders in identifying themes in the transcripts, it also

serves as a proxy for the validity of themes emerged from the

data (Ryan, 1999).

This prevents the coded themes to be anything but the subjective

imagination or predetermination of the researcher.

55

CAQDAS

Use of QDA Software

Weitzman and Miles (1995) say that Qualitative Data Analysis (QDA) software can help the qualitative researcher in:

Making notes in the field, writing up or transcribing field notes

Editing: correcting, extending, or revising field notes

Memoing: writing reflective commentaries on some aspect of the data

Coding: attaching keywords or tags to segments of text to permit later retrieval

Storage: keeping text in an organized database

Search and retrieval: locating relevant segments of texts

Data "linking": forming categories, clusters, or networks of information

Content analysis: counting frequencies, sequence, or locations of words and phrases

Data display: placing selected or reduced data in a condensed organized format,

Conclusion-drawing and verification: helping interpretation of data and testing findings

Theory-building: developing systematic explanations of findings; testing hypotheses

Graphic mapping: creating diagrams that depict findings or theories

Preparing interim and final reports (Weitzman and Miles, 1995) 56

CAQDAS

Should you use QDA software?

If you are using grounded theory or similar – YES.

The QDA software might be too mechanistic for some

qualitative data analysis approaches.

QDA software is only a tool.

It can be a temptation to become too detailed and not see the

big picture.

As long as you are able to use the software appropriately, most

qualitative researchers should consider using QDA software.

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Findings and Discussion

Findings are the presentation of results after analysis.

Despite the use of frequency count, the percentage of each count

is not required in findings.

Quotes of interviews are presented as findings so as to provide

evidence to later discussion.

Researchers need to discuss the findings with reference to past

literature. Stating what the findings are is not discussion.

Discussion must be relevant, insightful and rigorous with sound

justification based on the literature.

Sample qualitative paper:

http://dx.doi.org/10.1080/00220670903382921

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Potential Errors/Bias

Error (statistical error) describes the difference between a value

obtained from a data collection process and the 'true' value for

the population. The greater the error, the less representative the

data are of the population.

Sampling error occurs solely as a result of using a sample from a

population, rather than conducting a census (complete

enumeration) of the population. It refers to the difference

between an estimate for a population based on data from a

sample and the 'true' value for that population which would

result if a census were taken.

Non-sampling error is caused by factors other than those related

to sample selection. It refers to the presence of any factor,

whether systemic or random, that results in the data values not

accurately reflecting the 'true' value for the population.

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Potential Errors/Bias (cont.)

Coverage error: this occurs when a unit in the sample is

incorrectly excluded or included, or is duplicated in the sample

(e.g. a field interviewer fails to interview a selected household or

some people in a household).

Non-response error: this refers to the failure to obtain a response

from some unit because of absence, non-contact, refusal, or

some other reason. Non-response can be complete non-

response (i.e. no data has been obtained at all from a selected

unit) or partial non-response (i.e. the answers to some questions

have not been provided by a selected unit).

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Potential Errors/Bias (cont.)

Response error: this refers to a type of error caused

by respondents intentionally or accidentally providing inaccurate

responses. This occurs when concepts, questions or instructions

are not clearly understood by the respondent; when there are

high levels of respondent burden and memory recall required;

and because some questions can result in a tendency to answer

in a socially desirable way (giving a response which they feel is

more acceptable rather than being an accurate response).

Interviewer error: this occurs when interviewers incorrectly

record information; are not neutral or objective; influence the

respondent to answer in a particular way; or assume responses

based on appearance or other characteristics.

Processing error: this refers to errors that occur in the process of

data collection, data entry, coding, editing and output.

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THANK YOU

Hiram Ting

Email: [email protected]

Research Officer at Universiti Malaysia Sarawak

MBA PT Lecturer at SEGi College Sarawak

in collaboration with University of Sunderland, UK

PT Lecturer at Open University Malaysia and

Swinburne University of Technology Sarawak, Malaysia

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In house training 151114 qualitative research

Education

Transcript of In house training 151114 qualitative research