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Contemporary Approach to
Social Science
Research
Aondover Eric Msughter
ii
© Aondover Eric Msughter, 2020
All Right Reserved
All rights reserved. No part of this book may be reprinted or
reproduced or utilized in any form or by any electronic,
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ISBN: 978-978-8543-96-1
Published and Printed by:
Ahmadu Bello University Press Limited, Zaria,
Kaduna State, Nigeria. Tel.: 08065949711
E-mail: [email protected]
Website: www.abupress.com.ng
iii
Dedication
his book is dedicated to my mother, Mnguungwan
Aondover, who brought me up with love and care and
who created in me a sense of self-confidence as a writer.
T
iv
Foreword
he book Contemporary Approach to Social Science
Research appeals to the new essentiality and systematic
approach to research in social science disciplines. The
book with 287 pages and 11 Chapters focuses on the basic tools
of scientific methods and the applicability to contemporary
trends and dynamics in research methods, theories and
application are dedicated to touch all aspects of the book. In a
simple and discernable approach, the book provides an up to
date framework that is significant to students, teachers and
researchers to the basic concepts and techniques of conducting
research. The author has substantially carried out a
comprehensive and in-depth analysis and articulated properly
on the subject matter.
The author of this book, Aondover Eric Msughter
advances a framework, a process and composition approaches
for designing a research project for qualitative, quantitative and
mixed methods research in the social sciences. This ascendency
of qualitative research, the emergence of mixed methods
approaches and the growth of quantitative designs have created
a need for this book’s unique comparison to the three
approaches to inquiry.
In addition, the book addresses the key elements in the
process of designing and conducting a research project: writing
an introduction, stating a purpose or research aim, identifying
research questions and hypotheses and advancing methods and
procedures for data collection, analysis and interpretation. The
credibility of the book is apt, as it touches on rarely explored
research methods, such as semiotics, pragmatics and discourse
analysis, among others.
In my judgment, the book is a credit and intended for
students and faculty who seek assistance in preparing a plan or
proposal or research project for a scholarly journal article, a
dissertation or a thesis. At a broader perspective, the book is
T
v
useful as both a reference book and a textbook for courses in
social science research procedures.
It is against this foregoing that I commend the scholarly
effort of Aondover Eric Msughter (a Doctoral student at BUK),
a good associate of mine over last one decade, for adding to the
growing body of the literature into less academically addressed
subject of research in social science scholarship. It is a source of
joy to me that he has expanded enough literature in the area of
research to contribute to the strengthening of theory and new
methodological approaches to social science inquiry.
I am impressed with the quality and wide scope of the
Chapters as well as the bibliographic diversity of the ideas in
the various Chapters. In my judgment, I am of the view that this
book has added value to the pedagogical purity in our
discipline. I congratulate Eric and wish him greater energy to
do more. It is with great enthusiasm that I recommend this book
to all Mass Communication students and scholars and any other
person that has interest in social science research. Happy
reading.
Ralph A. Akinfeleye, PhD, fnipr, fnge, fcids
Professor of Journalism and Mass Communication
Chair, Centre of Excellence in Multimedia and Cinematography
Communication Specialist and Consultant to Radio Unilag
103.1FM and Unilag Television (Channel 184-Startimes)
Dept. of Mass Communication
University of Lagos, Lagos, Nigeria
vi
Preface
he book in your hand endeavours to present the modern
approaches to research for the benefit of students and
scholars. To facilitate easy comprehension, complex
concepts have been presented in tabulated or diagrammatical
forms. The author adopted a scientific approach in the treatment
of the subject and arranged the subject matter systematically.
The most striking point in this book is that examples are
taken from the surroundings in which the learner is brought up.
This makes the subject easier to understand for the learner. This
is why while writing this book, the author made sure that the
examples reflected Nigerian society, culture and environment.
The book, as a matter of fact, is a product of the author’s
experience in research. All the findings of the author’s research
have been incorporated in the book. It consists of 11 Chapters in
three parts. Each chapter contains a detailed explanation of the
research item followed by diagrams and numerous examples.
In Part One, the author presented research in the realm
of scholarship, the qualitative approach to social science
inquiry, the quantitative approach to social science inquiry and
the mixed methods approach (chapter one to four). Part Two
focused on understanding sampling and statistical procedure in
social science research, as well as perspectives on validity,
reliability, variables, scales and measurement and discussion on
pilot study were examined in four chapters (chapter five to
eight), while Part Three presented research proposal writing, the
format of the research project and guidelines for citation and
reference formation in three chapters (chapter nine to eleven).
Sincerely speaking, the book is a boon to students,
scholars and researchers in Nigeria and abroad and caters to
their needs, as it has been specifically designed. Its broad and
large format has been especially designed to make it more
attractive and readable. The author is confident that the present
book with its special features will find favour with students as
well as scholars and researchers.
T
vii
At this point, the author wishes to use the opportunity to
thank the publishers for their keen interest, co-operation and
encouragement in the publication of the book. Finally, any
suggestions from the reading public for further improvement of
the book may kindly be sent to the author’s email:
Author
Aondover Eric Msughter
21st July 2020
Kano, Nigeria
viii
Acknowledgements
give God, Who gave the idea of writing this book, all the
glory. I adore Him for inspiring and motivating me
throughout the writing stage. May His Name forever be
glorified in Jesus name, amen.
I would equally like to express my acknowledgements
and thanks to all the authors and writers whose books I have
consulted in the preparation of this excellent and competent
text.
I am deficient for the appropriate adjective to express
my gratitude to Prof. Ralph A. Akinfeleye, the father of Mass
Communication in Nigeria for taking time to write the
foreword. He is a great scholar that has served the discipline
well.
I also acknowledge Prof. Umaru A. Pate, the Dean,
School of Postgraduate Studies, Bayero University, Kano; Prof.
Abdalla Uba Adamu, the Vice Chancellor, National Open
University of Nigeria; Prof. Nosa Owens-Ibie, the Vice
Chancellor, Caleb University, Imota and Prof. Lai Oso, the
immediate past Dean of Communication in LASU, for
critiquing, applauding and approving the need to strengthen new
approaches in social science research.
I will forever be grateful to all the lecturers in the
Department of Mass Communication, Bayero University, Kano,
for their interest in my academic progress and professional
career. They taught me in the classroom, monitored and guided
my footsteps in journalism. I am equally grateful to Mustafa
Ibrahim (Ph.D student) for his suggestions, proofreading and
encouragement in favour and completion of this book.
I
ix
Contents
Dedication - - - - - - iii
Foreword - - - - - - iv
Preface- - - - - - - vi
Acknowledgements - - - - - viii
PART ONE
Chapter One
Understanding Research in the Realm of Scholarship- 3
The Typologies of Scholarship - - - 5
Framework for Research - - - - 8
Philosophical Worldviews - - - - 9
Perspectives on the Four Worldviews- - - 10
The Positivist Worldview - - - - 11
The Constructivist Worldview - - - 12
The Transformative Worldview - - - 14
The Pragmatic Worldview - - - - 15
Chapter Summary - - - - - 17
Chapter Two
Qualitative Approach to Social Science Inquiry - 19
Critical Discourse Analysis (CDA)- - - - 21
What is Critical in Discourse Analysis? - - 26
Intertexuality and (Inter) Disciplinarity - - 29
Transdisciplinarity - - - - - - 29
The Critique of CDA - - - - - 35
Issues to Analyse in CDA - - - - 37
Semiotic Analysis (SA) - - - - 37
Semiotics and Semiotic Analysis - - - 38
Steps in Semiotic Analysis - - - - 41
Types of Sign - - - - - - 41
Approaches to Semiotic Analysis - - - 41
Qualitative Content Analysis (QCA)- - - - 42
x
The Process of Qualitative Content Analysis - - 42
Objective of Qualitative Content Analysis - - 47
Procedures in Qualitative Content Analysis - - 47
Approaches to Qualitative Content Analysis - - 48
Text and Textual Analysis (TTA) - - - 48
Textual Analysis in Cultural and Media Studies - 49
Difference between Textual Analysis and Content Analysis 49
Methods and Techniques - - - - 50
Questions about Text and Textual Analysis - - 51
Ideological Codes in Media Content - - - 51
In-depth Interview (IDI) - - - - 52
The typologies of In-depth Interview - - - 53
Interview Guides - - - - - 53
The Basic Approach of Conducting In-depth Interview 54
Features of the In-depth Interview - - - 55
Steps or Process in Conducting In-depth Interview - 56
Advantages of In-depth Interviews - - - 58
Disadvantages of In-depth Interviews - - 58
Focus Group Discussion (FGD) - - - 58
Process in Focus Group Discussion - - - 59
Application of Focus Group Discussion - - 60
Characteristics of Focus Group Discussion - - 61
Advantages of Focus Group Discussion - - 61
Disadvantages of Focus Group Discussion - - 62
Instruments for Focus Group Discussion - - 62
Participant Observation (PO) - - - - 62
Methods in Conducting Observation - - - 63
Simple Observation - - - - - 63
Participant Observation - - - - 64
Requirements for Participant Observation - - 65
Approaches or Instruments use in Participant Observation 66
Nonparticipant Observation - - - - 67
Advantages of Nonparticipant Observation - - 68
Disadvantages of Nonparticipant Observation - 68
Systematic Observation - - - - 68
Mass Observation - - - - - 69
Steps in Observation Research - - - 69
xi
Case Study Method (CSM) - - - - 71
Types of Case Study - - - - - 72
The Purpose of Case Study - - - - 73
Case Study Design - - - - - - 74
Conducting a Case Study - - - - 74
Advantages of Case Studies - - - - 77
Disadvantages of Case Studies - - - 77
Chapter Summary - - - - - 77
Chapter Three
Quantitative Approach to Social Science Inquiry - 79
Survey Method - - - - - 80
The Purpose - - - - - - 82
The Characteristics of Survey - - - - 84
Forms of Administrating Survey - - - 84
Advantages of Telephone Survey - - - 84
Disadvantages of Telephone Survey - - - 84
Stages of a Mail Survey - - - - - 86
Advantages of Postal or Mail Survey - - - 86
Disadvantages of Postal or Mail Survey - - 86
How to Improved Return Rate - - - 86
Procedures in Conducting Personal Survey - - - 87
Advantages of Personal Survey - - - - 87
Disadvantages of Personal Survey - - - - 88
Advantages of Group Administration - - - 88
Disadvantages of Group Administration - - 88
Time Span - - - - - - 90
Survey Instruments - - - - - - 91
Guideline for Administering Questionnaires - - 92
How to Design or Construct a Questionnaire? - 92
Problem with Questionnaires - - - - 93
Types of Interview - - - - - - 94
Content Analysis - - - - - 94
Uses of Content Analysis - - - - 97
Advantages of Content Analysis - - - 98
Disadvantages of Content Analysis - - - 98
Manifest Coding - - - - - 98
xii
Latent or Systematic Analysis - - - - 99
Intercoder Reliability - - - - - 99
Unit of Analysis - - - - - - 100
Measurement in Content Analysis - - - - 101
Design in Content Analysis - - - - - 102
Experimental Research Method - - - 105
Types of Experimentation - - - - - 106
Advantages of Laboratory Experiment - - - 107
Disadvantages of Laboratory Experiment - - - 107
Field Experimentation - - - - - 107
Advantages of Field Experimentation - - 108
Disadvantages of Field Experimentation - - - 108
Guideline for Conducting Experimental Research - 109
Experimental Research Designs - - - - 111
Chapter Summary - - - - - 111
Chapter Four
Mixed Methods Research - - - - 113
Mixed Methods Designs - - - - 114
Chapter Summary - - - - - - 117
PART TWO Chapter Five
Understanding Sampling in Research - - - 121
The Population - - - - - - 121
Why Sampling? - - - - - - 123
Determining Sample Size - - - - - 124
Formulas for Sample Size Determination - - 126
Sampling Error - - - - - - 131
Sampling Procedures - - - - - 132
Probability Sampling - - - - - 132
Non-Probability Sampling - - - - 135
When to Use Non-Probability Sampling Techniques - 137
Sampling Terminologies or Concepts - - 138
Chapter Summary - - - - - - 140
xiii
Chapter Six
Statistical procedure in Social Science Research - 141
Why Students or Researchers Need the Knowledge
of Statistics? - - - - - - 142
Frequency Distribution Tables - - - 142
Ungrouped Data - - - - - 142
Group Data - - - - - - 143
Measurement of Association or Correlation - - 145
Characteristics of Correlation Procedure - - 145
Steps to Follow - - - - - 146
Bar Chart - - - - - - 147
Construction of Bar Graphs - - - - 147
Histogram - - - - - - 149
Parts of a Histogram - - - - - 149
Pie Chart - - - - - - 150
Ogive or Cumulative Frequency Distribution- - 151
Frequency Polygon - - - - - 152
Statistical Package for Social Science (SPSS)- - 155
How SPSS Helps in Research and Data Analysis Programs 156
Layout of SPSS - - - - - 157
SPSS Menus and Icons - - - - 157
Steps for Data Analysis Using SPSS - - - 159
Atlas.ti - - - - - - - 159
Analytical Strategies in Qualitative Data Analysis - 159
NVivo - - - - - - - 160
Why Use Nvivo? - - - - - 162
Mendeley - - - - - - 162
How do I Use It? - - - - - 164
Layout - - - - - - - 164
Features - - - - - - 166
How Mendeley Help to Your Research Work? - 167
Chapter Summary - - - - - 168
Chapter Seven
Perspectives on Validity, Reliability, Variables,
Scales and Measurement - - - - 171
Causes of Extraneous Variables - - - 171
xiv
Methods of Measuring Validity - - - 173
Reliability - - - - - - - 175
Method of Measuring Reliability - - - 176
Variables - - - - - - 177
Types of Variables - - - - - - 178
Scales - - - - - - - 179
Types of Scales - - - - - 180
Things to Consider When Using the Likert Scale - 181
Measurement - - - - - - 183
What Communication Researchers Measured? - 184
Levels of Measurement - - - - 184
Error in Measurement - - - - - 186
Chapter Summary - - - - - 186
Chapter Eight
The Pilot Study - - - - - 187
Rationale for Conducting Pilot Studies - - 187
Problems of Pilot Studies - - - - 188
Piloting Questionnaire - - - - - 191
How to Write and Analyse a Questionnaire - - 191
Chapter Summary - - - - - 194
PART THREE Chapter Nine
Research Proposal Writing - - - - 197
What Does Proposal Do? - - - - 198
Common Mistakes in Proposal Writing - - 198
Proposal Format - - - - - 199
Elements of Research Proposal - - - 200
The Topic or the Title - - - - - 200
Determination of the Topic Relevance - - 203
Background to the Study - - - - 206
Problem Statement - - - - - 207
Aim or Purpose of the Study - - - - 208
Objectives of the Study - - - - 209
Research Questions or Hypothesis - - - 210
Significance of the Study - - - - 210
xv
Scope of the Study - - - - - 211
Limitations to the Study - - - - 212
Organisation of the Study - - - - 212
Operational Definition of Terms or Concepts- - 213
Literature Review - - - - - 214
Theoretical Framework - - - - 215
Research Method - - - - - 217
Research Design - - - - - 217
Population Description - - - - - 218
Sample Size - - - - - - 218
Sampling Technique - - - - - 219
Data Gathering Instruments - - - - 219
Method of Data Presentation and Analysis - - 219
Chapter Summary - - - - - - 220
Chapter Ten
Format of Research Report - - - - 221
Preliminary Pages - - - - - 221
Flyleaf - - - - - - - 221
Title - - - - - - - 221
Declaration - - - - - - 222
Certification - - - - - - 222
Approval - - - - - - 222
Dedication - - - - - - 222
Acknowledgments - - - - - 222
Table of Content - - - - - 223
Abstract - - - - - - 223
Qualities of a Good Abstract - - - - 223
Four Steps to Writing Abstract - - - 224
Sample of Abstract - - - - - 225
List of Tables - - - - - - 225
The Main Body - - - - - 225
Chapter One - - - - - - 225
Chapter Two - - - - - - 226
Chapter Three - - - - - - 226
Chapter Four - - - - - - 226
Chapter Five - - - - - - - 226
xvi
Appendix - - - - - - 227
References or Bibliography - - - - 227
Chapter Summary - - - - - 227
Chapter Eleven
Guidelines for Citations and Reference Formations - 229
In-Text References (APA 7th Edition) - - 231
Reference List - - - - - - 232
Notable Changes in Citing Sources in the 7th Edition
of APA - - - - - - 233
Book or Book Chapters - - - - 234
Dictionary or Encyclopedia - - - - 240
Journal, Newspaper and Newsletter Articles - - 241
Conference or Seminar Papers - - - - 245
Government Publications - - - - 246
Images, Music and Audiovisual Media - - 248
Thesis or Dissertation - - - - 252
University Provided Study Materials - - - 253
Social Media - - - - - - 253
Personal Communication and Email - - - 255
Web Resources - - - - - 255
Chapter Summary - - - - - 257
References - - - - - - - 258
Index - - - - - - - 267
Part One
2
3
Chapter One
Understanding Research in the Realm of
Scholarship
Introduction
The completion of any academic course requires a
student to undertake a research project, for undergraduate
students; dissertation, for M.Sc students and thesis, for Ph.D
candidates. The ability to successfully obtain any of these
certificates will definitely compel, such a student to have the
basic knowledge of research regarding disciplines like Public
Relations, Advertising, Print Media, Broadcast Media, Theatre
Art, Political Science, Sociology, Economics, International
Relations, Business Administration, Accounting, History,
English and Literary Studies, Law, Agricultural Science to
mention but a few. The desire of every student or researcher is
to easily understand and identify the step-by-step approach that
will aid them successfully complete the research and obtain a
certificate in any of the preceding disciplines enumerated. The
task may be challenging especially for research beginners who
are not conversant with some of the technicalities or the step-
by-step approach that are involved.
Clearly, excellent skills are highly demanded for
students or researchers who want to excel in research. This is
because any scientific inquiry or solution is a product of
research. It is through research that societal problems are
identified, which eventually leads to a solution of the identified
problem. This could be the reason why Msughter and Ya’u
(2018) articulated that, the advancement of modern societies is
proportional to the growth and application of scientific inquiry.
Scientific inquiry or research has greatly enhanced socio-
political and economic development and expansion of
knowledge in the society (Neumann, 2000 and Gunter, 2000).
Without research, human societies would have remained
primitive, backward and stationary. It is as a result of social and
scientific inquiry that human societies recorded appreciable
4
progress in the areas of science, technology, medicine,
economics, politics, journalism and other areas of human
endeavour (Maikaba, 2011). Maikaba added that for any society
to achieve reasonable development, it must be research driven
and oriented. This was observed earlier by Olofin (2006) who
argued that without thorough research, no discovery can be
made and nothing old can be modified, refuted or confirmed.
Research process is just like a child who started
schooling, it is expected that such a child will start from the
play group classes, moving up to pre-nursery, nursery to
primary, secondary to higher institutions depending on the
child’s ability to cope in this graduated process. Research has
become a compulsory aspect of the society with mass media
inclusive as there is virtually no activity in the society and the
media that do not require one form of research or the other.
Research is needed in all aspect of life and that is why this book
is imperative as far as social science research is concerned.
Research is an aspect that is woven in the fabric of society that a
scholar needs to demonstrate competence in. This is because,
virtually every area of social science requires research. This is
why the need to understand the rules and the “games” of
research, in order to effectively put them into use, is apparent. It
is only when this is done that one will be able to advance one’s
understanding of research in the realm of scholarship. Research
determines the outcome of a particular problem and how that
problem can be solved.
A starting point for the understanding of research in the
realm of scholarship is a basic process of inquiry itself. Inquiry
connotes the systematic approach to study and the experience
that leads to knowledge, method and theory. According to
LittleJohn and Foss (2008) people engage in inquiry when they
attempt to find out about something in an orderly way. To them,
this process involves three stages. The first stage is asking
questions. They believe that inquiry is nothing more than the
process of asking interesting, significant questions and
providing disciplined, systematic answers to them. Questions
can be of various types in this perspective. Questions of
5
definition call for concepts as answers seeking to clarify what is
observed; what is it? What will we call it? Questions of fact ask
about properties and relationships in the object and subject
observed; what does it consist of? How does it relate to other
things? Questions of value probe aesthetic, pragmatic and
ethical qualities of the observed.
Another stage of inquiry is observation. Under this
stage, scholars look for answers by observing the phenomenon
under investigation. The method of observation varies from one
tradition to another. Scholars like LittleJohn and Foss (2008)
established that, some scholars observed by examining records
and artifacts, others by personal involvement, others by using
instruments and controlled experimentation while others do so
by interviewing people. However, whatever method that is used,
the investigator develops some planned method for answering
the questions posed by social science.
Constructing answers is in the third stage of the inquiry,
scholars attempt to define, describe and explain, including
making judgment and interpretations about what was observed.
Stage three is usually termed as the theoretical approach. People
often recognize these stages of inquiry as linear, occurring one
step at a time, first questions, then observations and finally
answers. However, inquiry does not proceed in this fashion. At
each point in time, each stage is affected by the others. For
instance, observations often stimulate new questions and
theories are challenged by both observations and questions.
Theories lead to new questions while observations are
determined in part by theories. Thus, inquiry is more like a
circular loop, with feedback resulting in a back and forth
movement in different points rather than a linear process.
The Typologies of Scholarship
The vital point to examine in this regard is on the basic
elements of inquiry because different types of inquiry ask
questions differently together with different methods of
observation, which lead to different kinds of theoretical
perspectives. Methods of inquiry can be categorized into three
6
forms of scholarship. These include: scientific, humanistic and
social scientific. LittleJohn and Foss (2008) examined these
typologies of scholarship thus:
Scientific Scholarship: science is associated with
objectivity, standardization and generalizability. Scientist
attempts to look at the world in the same way as other observers
trained the same way and use the same methods. The
replications of a study should be able to yield an identical result.
Standardization alongside replication is important in science
because scientists presumed that the world has observable form
and they view their tasks to include discovering the world as it
is. The argument put forward by the identified authors regarding
scientific scholarship is that the world sits in wait of discovery
and the essence of science is to observe and explain the world
as accurately as possible.
It is clear in the literature that there is no absolute way to
know how accurate observations are; the scientist must rely on
agreement among observers. The reason is that if all trained
observers using the same method report on the same results, the
object is presumed to have been accurately observed. The
emphasis here is on discovering knowable world because
scientific methods are suited to problems of nature.
Humanistic Scholarship: as science is associated with
objectivity, the humanities are subjective in nature. This is
because science aims to standardize observation while
humanities aim at interpretation. The essence of science is to
reduce human differences in what is observed while humanities
often understand individual in terms of subjective response.
Similarly, humanists are interested in individual cases than the
generalized theory. However, science focuses on the discovered
world and the humanities focus on the discovered person.
Consensus is associated with science while alternative
interpretation has to do with the humanists. In the humanists
tradition, there are suspicious claim that there is an immutable
world to be discovered which tend not to separate the knower
from the known. The position of the classical humanists is that,
what one sees is determined by whom one is and because of
7
this, subjective response and humanistic scholarship is suited to
problems of personal experience, values and art.
Therefore, science and humanities are not totally apart
because any programme of research and theory building
includes some aspects of both scientific and humanistic
scholarship. This is apparent because at times, the scientist is a
humanist that uses intuition, creativity, interpretation and
insight to understand the data collected or a research that is
taken in a new angle. Some of the scientific discoveries were as
a result of the creative insight. Archimedes for example
discovered how to measure the volume of liquid using
displacement when he stepped into his bathtub while Fleming
used and threw away the mold in the petri dish that produced
penicillin. Newton was inspired by a fallen apple.
Consequently, scientist must be subjective in creating the
methods that will lead to objective observation thereby making
research design a creative one. Also, the humanist can be
scientific in seeking facts that will enable experience to be
understood better.
Social-Scientific Scholarship: this kind of research is
often seen as an extension of the natural science, which uses
methods that are borrowed from the natural sciences. Social
science is actually a different kind of inquiry. It includes
elements of both science and that of humanities but is different
from both (LittleJohn and Foss, 2008). In the process of
observing and interpreting patterns of human behaviour, social-
science scholars make human beings as the object of the study.
The social scientist, like the natural scientist, must put into
consideration consensus on the basis of what is observed. This
is because once the behavioural phenomena are accurately
observed, they must be explained or interpreted and this is
where the humanistic aspect comes into play. Considering the
fact that human subject is active, knowing being, unlike objects
in the natural world, interpreting becomes so difficult.
The big question is can scientific explanations of human
behaviour take place without taking into cognizance humanistic
knowledge of the observed person? This question is indeed a
8
philosophical issue of social science and has generated so many
debates among scholars in different disciplines. Before now,
social scientists believed that scientific methods would suffice
to uncover the mysteries of human experience but today, people
realised that humanistic element is needed.
Framework for Research
Framework for research is inclined to worldviews,
design and research method. The two important components in
each definition are that the approach to research involves
philosophical assumptions as well as distinct methods or
procedures. The broad research approach is the plan or proposal
to conduct research, involves the intersection of philosophy,
research designs and specific methods. To reiterate, in planning
a study, researchers need to think through the philosophical
worldview assumptions that they bring to the study, the research
design that is related to this worldview and the specific methods
or procedures of research that translate the approach into
practice. A framework that explains the interaction of these
three components is demonstrated in the diagram below:
9
Source: (Creswell and Creswell, 2018)
Philosophical Worldviews
Philosophical ideas remain largely hidden in research;
they still influence the practice of research and need to be
identified (Creswell and Creswell, 2018). This book suggests
that individuals preparing a research proposal or plan make
explicit the larger philosophical ideas they espouse. This
information will help explain why they chose qualitative,
quantitative or mixed methods approaches for their research. In
writing about worldviews, a proposal might include a section
that addresses the following:
a. The philosophical worldview proposed in the study.
b. A definition of the basic ideas of that worldview.
c. How the worldview shaped their approach to research.
The term worldview in this perspective connotes “a
basic set of beliefs that guide action” (Creswell and Creswell,
Philosophical
Worldviews
Design
Research
Approaches
Quantitative
Qualitative
Mixed Method
Positivist
Constructivist
Transformative
Pragmatic
Quantitative
(e.g.,
Experimentals)
Qualitative
(e.g.,
Ethnographies)
Mixed Methods
(e.g., Explanatory
– Sequential)
Research
Methods
Data Collection
Data Analysis
Interpretation
Validation
10
2018). Other scholars referred to it as “paradigms”. Therefore,
worldview is seen as a general philosophical orientation about
the world and the nature of research that a researcher brings to a
study. Individuals develop worldviews based on their discipline
orientations and research communities, advisors and mentors as
well as past research experiences. The types of beliefs held by
individual researchers based on these factors will often lead to
embracing a strong qualitative, quantitative or mixed methods
approach in their research. However, there is an ongoing debate
about what worldviews or beliefs researchers bring to inquiry.
This book highlights the four typologies that are widely
discussed in the literature: positivist, constructivism,
transformative and pragmatism. The major elements of each
position are presented thus:
Perspective on the Four Worldviews
Source: (Creswell and Creswell, 2018)
Positivism
Determination
Reductionism
Empirical
observation and
measurement
Theory verification
Constructivism
Understanding
Multiply
participant
meanings
Social and
historical
construction
Theory generation
Transformative
Political
Power and
justice oriented
Collaborative
Change-oriented
Pragmatism
Consequences of
actions
Problem-centered
Pluralistic
Real-world practice
oriented
11
The Positivist Worldview
The positivist or post-positivist assumptions have
represented the traditional form of research and these
assumptions dwell more on quantitative research than
qualitative research. This worldview is sometimes called the
“scientific method” or “doing science research”. It is also called
“empirical science” and “post-positivism”. This last term is
called post-positivism because it represents the thinking after
positivism, challenging the traditional notion of the absolute
truth of knowledge and recognizing that people cannot be
absolutely positive about their claims of knowledge when
studying the behaviour and actions of humans (Phillips and
Burbules, 2000).
Positivists or Post-positivists hold a deterministic
philosophy in which causes (probably) determine the effects or
the outcomes. The problems studied by positivists reflect the
need to identify and assess the causes that influence outcomes,
such as those found in experiments. It is also reductionist, in
that the intent is to reduce the ideas into a small, discrete set to
test, such as the variables that comprise hypotheses and research
questions. The knowledge that develops through a post-
positivist lens is based on careful observation and measurement
of the objective reality that exists “out there” in the world. Thus,
developing numeric measures of observations and studying the
behaviour of individuals becomes apparent for a post-positivist.
Finally, there are laws or theories that govern the world and
these need to be tested or verified and refined so that one can
understand the world (Creswell and Creswell, 2018). Therefore,
the scientific method in this context begins with a theory,
collects data that either supports or refutes the theory and then
makes necessary revisions and conducts additional tests.
The key tenets or assumptions of the positivist as
outlined by Phillips and Burbules (2000) include the following:
a. Knowledge is conjectural and anti-foundational,
absolute truth can never be found. Thus, evidence
established in research is always imperfect and fallible.
12
It is for this reason that researchers state that they do not
prove a hypothesis; instead, they indicate a failure to
reject the hypothesis.
b. Research is the process of making claims and then
refining or abandoning some of them for other claims
more strongly warranted. Most quantitative research, for
example, starts with the test of a theory.
c. Data, evidence and rational considerations shape
knowledge. In practice, the researcher collects
information on instruments, based on measures,
completed by the participants or by observations
recorded by the researcher.
d. Research seeks to develop relevant, true statements,
ones that can serve to explain the situation of concern or
that describe the causal relationships of interest. In
quantitative studies, researchers advance the relationship
among variables and pose this in terms of questions or
hypotheses.
e. Being objective is an essential aspect of competent
inquiry; researchers must examine methods and
conclusions for bias. For example, standard of validity
and reliability are important in quantitative research.
The Constructivist Worldview
Constructivism or social constructivism is often
combined with interpretivism and it is typically seen as an
approach to qualitative research. Social constructivists believe
that individuals seek understanding of the world in which they
live and work. Individuals develop subjective meanings of their
experiences, meanings directed toward certain objects or things.
These meanings are varied and multiplied, leading the
researcher to look for the complexity of views rather than
narrowing meanings into a few categories or ideas. The goal of
the research is to rely as much as possible on the participants’
views of the situation being studied. The questions become
broad and general so that the participants can construct the
meaning of a situation, typically forged in discussions or
13
interactions with other persons. The more open-ended the
questioning, the better, as the researcher listens carefully to
what people say or do in their life settings. Often these
subjective meanings are negotiated socially and historically.
They are not simply imprinted on individuals but are
formed through interaction with others (hence social
constructivism) and through historical and cultural norms that
operate in individuals’ lives. Constructivist researchers often
address the processes of interaction among individuals. They
also focus on the specific contexts in which people live and
work in order to understand the historical and cultural settings
of the participants. Researchers recognize that their own
backgrounds shape their interpretation and they position
themselves in the research to acknowledge how their
interpretation flows from their personal, cultural and historical
experiences. The researcher’s intent is to make sense of (or
interpret) the meanings others have about the world. Rather than
starting with a theory (as in post-positivism), inquirers generate
or inductively develop a theory or pattern of meaning. For
example, in discussing constructivism, Crotty in Creswell and
Creswell (2018) identified several assumptions:
1. Human beings construct meanings as they engage with
the world they are interpreting. Qualitative researchers
tend to use open-ended questions so that the participants
can share their views.
2. Humans engage with their world and make sense of it
based on their historical and social perspectives; people
are all born into a world of meaning bestowed upon
them by culture. Thus, qualitative researchers seek to
understand the context or setting of the participants
through visiting this context and gathering information
personally. They also interpret what they find, an
interpretation shaped by the researcher’s own
experiences and background.
3. The basic generation of meaning is always social,
arising in and out of interaction with a human
community. The process of qualitative research is
14
largely inductive; the inquirer generates meaning from
the data collected in the field.
The Transformative Worldview
Some scholars hold to the philosophical assumptions of
the transformative approach. This position arose during the
1980s and 1990s from individuals who felt that the post-
positivist assumptions imposed structural laws and theories that
did not fit marginalized individuals in the society or issues of
power and social justice, discrimination and oppression that
needed to be addressed. There is no uniform body of literature
characterizing this worldview, but it includes groups of
researchers that are critical theorists, participatory action
researchers, Marxists, feminists, racial and ethnic minorities,
persons with disabilities, indigenous and postcolonial peoples
and members of the lesbian, gay, bisexual, transsexual and
queer communities. Historically, the transformative writers
have drawn on the works of Marx, Adorno, Marcuse, Habermas
and Freire among others.
These inquirers felt that the constructivist stance did not
go far enough in advocating for an action agenda to help
marginalized peoples. A transformative worldview holds that
research inquiry needs to be intertwined with politics and a
political change agenda to confront social oppression at
whatever levels it occurs (Mertens, 2010). As such, the research
contains an action agenda for reform that may change lives of
the participants, the institutions in which individuals work or
live and the researcher’s life. Moreover, specific issues need to
be addressed that speak to important social issues of the day,
issues such as empowerment, inequality, oppression,
domination, suppression and alienation. The researcher often
begins with one of these issues as the focal point of the study.
The research also assumes that the inquirer will proceed
collaboratively so as not to further marginalize the participants
as a result of the inquiry. In this sense, the participants may help
design questions, collect data, analyze information or reap the
rewards of the research. Transformative research provides a
15
voice for these participants, raising their consciousness or
advancing an agenda for change to improve their lives. It
becomes a united voice for reform and change.
Philosophical worldview focuses on the needs of groups
and individuals in the society that may be marginalized or
disenfranchised. Therefore, theoretical perspectives may be
integrated with the philosophical assumptions that construct a
picture of the issues being examined, the people to be studied
and the changes that are needed, such as feminist perspectives,
racialized discourses, critical theory, queer theory and disability
theory. Although these are diverse groups and the explanations
here are generalizations, it is helpful to view the summary by
Mertens (2010) of key features of the transformative worldview
or paradigm:
a. It places central importance on the study of lives and
experiences of diverse groups that have traditionally
been marginalized. Of special interest for these diverse
groups is how their lives have been constrained by
oppressors and the strategies that they use to resist,
challenge and subvert these constraints.
b. In studying these diverse groups, the research focuses on
inequities based on gender, race, ethnicity, disability,
sexual orientation and socioeconomic class that result in
asymmetric power relationships.
c. The research in the transformative worldview links
political and social action to these inequities.
d. Transformative research uses a program theory of
beliefs about how a program works and why the
problems of oppression, domination and power
relationships exist.
The Pragmatic Worldview
This worldviews comes from the pragmatists. There are
many forms of this philosophy but for many, pragmatism as a
worldview arises out of actions, situations and consequences
rather than antecedent conditions (as in postpositivism). There
is a concern with applications, what works and solutions to
16
problems (Patton, 1990). Instead of focusing on methods,
researchers emphasize the research problem and question and
use all the approaches available to understand the problem. As a
philosophical underpinning for mixed methods studies,
Tashakkori and Teddlie (2010) convey its importance for
focusing attention on the research problem in social science
research and then using pluralistic approaches to derive
knowledge about the problem. Using the summary provided by
Cresewll and Creswell (2018) we can understand how
pragmatism provides a philosophical basis for research:
a. Pragmatism is not committed to any one system of
philosophy and reality. This applies to mixed methods
research, which inquirers draw liberally from both
quantitative and qualitative assumptions when they
engage in their research.
b. Individual researchers have a freedom of choice. In this
way, researchers are free to choose the methods,
techniques and procedures of research that best meet
their needs and purposes.
c. Pragmatists do not see the world as an absolute unity. In
a similar way, mixed methods researchers look to many
approaches for collecting and analyzing data rather than
subscribing to only one way (e.g., quantitative or
qualitative).
d. Truth is what works and it is not based on duality,
between reality independent of the mind or within the
mind. Thus, in mixed methods research, investigators
use both quantitative and qualitative data because they
work to provide the best understanding of a research
problem.
e. The pragmatist researchers look into what and how to
research based on the intended consequences, where
they want to go with it. Mixed methods researchers need
to establish a purpose for their mixing, a rationale for the
reasons why quantitative and qualitative data need to be
mixed in the first place.
17
f. Pragmatists agree that research always occur in social,
historical, political and other contexts. In this way,
mixed methods studies may include a postmodern turn,
a theoretical lens that is reflective of social justice and
political aims.
g. Pragmatists have believed in an external world,
independent of the mind as well as what lodged in the
mind. But they believe that we need to stop asking
questions about reality and the laws of nature. “They
would simply like to change the subject”.
h. Thus, for the mixed methods researcher, pragmatism
opens the door to multiple methods, different
worldviews and different assumptions, as well as
different forms of data collection and analysis.
Chapter Summary
Chapter One examines the imperativeness of social
science research. The need to be familiar with the rules and the
game of research was highlighted, considering the fact that
research is an integrated part of human existence and no part of
the society can exist without it. The need for students to
understand research in the realm of scholarship was stressed in
Chapter One. Arguments regarding the typologies of
scholarship were discussed extensively. It captures and
highlights the significance of social science inquiry drawing
from the scientific, humanistic and social-scientific scholarship.
It is argued in this perspective that research framework is
predetermined from the philosophical worldviews of positivist,
constructivist, transformative and pragmatic worldviews. Thus,
a proper design for any scientific inquiry is normally taken from
these worldviews so as to have a substantial backup regarding
the choice of any design undertaken by the researcher.
18
19
Chapter Two
Qualitative Approach to Social Science Inquiry
Introduction
In qualitative studies, authors report original, empirical,
qualitative research. Qualitative research refers to scientific
practices that are used to generate knowledge about human
experience or action, including social processes. Quantitative
research on the other hand is an approach for testing objective
theories by examining the relationship among variables. These
variables, in turn, can be measured, typically on instruments, so
that numbered data can be analyzed using statistical procedures.
The final written report has a set structure consisting of
introduction, literature and theory, methods, results and
discussion. Like qualitative researchers, those who engage in
this form of inquiry have assumptions about testing theories
deductively, building in protections against bias, controlling for
alternative or counterfactual explanations and being able to
generalize and replicate the findings (American Psychological
Association, 2020).
Qualitative research is a scientific practice that is used to
generate knowledge about human experience or action,
including social processes. Qualitative approaches tend to share
four sets of characteristics: Researchers analyze data consisting
of natural language (i.e., words), researcher observations (e.g.,
social interactions) or participants’ expressions (e.g., artistic
presentations) rather than collecting numerical data and
conducting mathematical analyses. Reports tend to show the
development of qualitative findings using natural language
(although numbers may be used adjunctively in describing or
exploring these findings).
Researchers often use an iterative process of analysis,
which they re-examine developing findings in light of continued
data analysis and refine the initial findings. In this way, the
process of analysis is self correcting and can produce original
knowledge. Researchers’ recursively combine inquiry with
20
methods that require researchers’ reflexivity about how their
own perspectives might support or impair the research process
and thus how their methods should best be enacted. Researchers
tend to study experiences and actions whose meaning may shift
and evolve; therefore, they tend to view their findings as being
situated within place and time rather than seeking to develop
laws that are expected to remain stable regardless of context.
Qualitative approach is about human behaviour, opinion,
perceptions in order to understand patterns and trends (Kurfi,
2019). This method is interested in investigating “why”, “how”
and “what”. Qualitative research is inductive in nature and the
researcher generally explores meanings and insights in a given
situation. It refers to a range of data collection and analysis
techniques that use purposive sampling and semi-structured
open-ended interviews (Gopaldas, 2016). It is described as an
effective model that occurs in a natural setting and enables the
researcher to develop a level of details from high involvement
in the actual experiences (Creswell, 2009). It consists of a set of
interpretive material practices that makes the world visible. It is
multi-method in focus, involving an interpretive, naturalistic
approach to its subject matter (Denzin and Lincoln, 2005).
It is a type of social science research that collects and
works with non-numerical data that seeks to interpret meaning
from data that help people to understand social life through the
study of targeted populations or places (Punch, 2013). It is the
observations and interpretations of people’s perception of
different events and it takes the snapshot of the people’s
perception in a natural setting. It investigates local knowledge
and understanding of a given programme, people’s experiences,
meanings and relationships, social processes and contextual
factors that marginalize a group of people. It is less structured in
description, because it formulates and builds new theories
(Haradhan, 2018). It focuses on words rather than numbers, this
type of research observes the world in natural setting,
interpreting situations to understand the meanings that people
make from day-to-day life. The basis of it lies in the interpretive
approach to social reality and in the description of the lived
21
experience of human beings. The qualitative methods in social
science inquiry include:
1. Critical Discourse Analysis (CDA)
2. Semiotic Analysis (SA)
3. Qualitative Content Analysis (QCA)
4. Text and Textual Analysis (TTA)
5. In-depth Interview (IDI)
6. Focus Group Discussion (FGD)
7. Participant Observation (PO)
8. Case Study Method (CSM)
(1) Critical Discourse Analysis (CDA)
Critical Discourse Analysis (CDA) is a method that is
interested in investigating the relationship between dominance,
discrimination, power and control as manifested in the language
(Kurfi, 2019). The aim is to study how linguistics forms are
used in various expression and manipulation of power.
Although it is not attached to any special theory and
philosophy, it is a method of analyzing text (Jahedi et al.,
2014). Discourse analysis approach is an empirical examination
of the text that are produced (created) and consumed (received
and interpreted) and viewed as an important form of social
practice which contributes to the constitution of the social world
including social identities and social relations (Jorgensen and
Phillips, 2002). Consequently, critical discourse analysis as an
explanatory critique that draws attention to the existence of
stereotyped categorizations in daily talk, elite talk and texts.
CDA involves language use in speech and in writing as
a form of social common practice. In CDA, language is not
powerful on its own but it gains power in the way powerful
people use it in the text. The language itself is not what really
matter but the people that have been featured in the text. The
ideology, the power, the hierarchy and the sociological
variables are relevant for the interpretation of the text.
CDA is defined as a branch of discourse analysis, which
is concerned with analyzing opaque as well as transparent
structural relationships of dominance, discrimination, power and
22
control as manifested in the language (El-Sharkawy, 2018). Van
Dijk (1998) argued that CDA is a field that is concerned with
studying and analyzing written and spoken texts to reveal the
discursive sources of power, dominance, inequality and bias. It
examines how these discursive sources are maintained and
reproduced within the specific social, the political and the
historical contexts. In other words, CDA aims to investigate
critically social inequality as it is expressed, signaled,
constituted, legitimized and so on by language use (or in
discourse). CDA aims at making transparent the connections
between discourse practices, social practices and social
structures, connections that might be opaque to the layperson.
However, CDA isn’t based on a single theory or
method, which is uniform and consistent (Fairclough, 2003).
Instead, it involves the linguistic and social approaches, which
would endorse Habermas’s claim that language is a medium of
domination and social force in such a way that it serves to
legitimize relations of organized power. Weiss and Wodak
(2003, p. 6) suggest that “the whole theoretical framework of
CDA seems eclectic and unsystematic”. Whereas linguistics
traditionally focused on the micro analysis of texts and
interactions, social science was traditionally concerned with
social practice and social change. In CDA, the analysis of the
social life requires investigation and combination of the
interactional and the structural. Texts do not only provide facts
but they provide many instances of the facts because it does not
only concern with what a text says but also how that text
portrays facts in various ways in which each and every text
becomes a unique creation of a unique creator. Texts also do not
describe facts, but they propose problems that the analyst tries
to solve.
Unlike non-critical approaches (that is, linguistics,
sociolinguistics, pragmatics, etc.), which are satisfied with
recognizing what a text says and restating the key remarks of
the text, CDA goes two steps further. First, it recognizes what a
text says and it reflects on what the text does. Secondly, it gives
instances of interpretations to what the text, as a whole, means
23
from both what it says and what it does. Meyer (2001) argues
that CDA is differentiated from other sociolinguistic approaches
because it is concerned on different problems in nature and in
research questions, as well as advocates a role for groups who
suffer from social discrimination and inequality.
Many theorists in CDA present the general principles of
CDA in their own terms. Fairclough and Wodak (1997, 271-80)
summarize the main tenets of CDA as follows:
a) CDA addresses social problems.
b) Power relations are discursive.
c) Discourse constitutes society and culture.
d) Discourse does ideological work.
e) Discourse is historical.
f) The link between text and society is mediated.
g) Discourse analysis is interpretative and explanatory.
h) Discourse is a form of social action.
The first principle is that CDA addresses social
problems. CDA not only focuses on language and language use
but also on the linguistic characteristics of social and cultural
processes. CDA follows a critical approach to social problems
in its endeavors to make explicit power relationships, which are
frequently hidden. It aims to derive results, which are of
practical relevance to the social, the cultural and the political
and even the economic contexts. In CDA, social cognition is the
missing link between discourse and society.
The second principle of CDA is that power relations are
discursive. That is CDA explains how social relations of power
are exercised and negotiated through discourse. The third
principle is that discourse constitutes society and culture. This
means that every instance of language use makes its own
contribution to reproducing and transforming society and
culture, including relations of power. The fourth principle is that
discourse does the ideological work. In other words, ideologies
are often produced through discourse. To understand how
ideologies are produced, it is not enough to analyze texts; the
discursive practice (how the texts are interpreted and received
and what social effects they have) must also be considered. The
24
fifth principle is that discourse is historical. Thus, discourses
can only be understood with reference to their historical
context. In this perspective, CDA refers to extra linguistic
factors, such as culture, society and ideology in historical terms
(Wodak, 2001). The sixth principle is that discourse is mediated
between the text and the society. CDA is not a deterministic
approach but invokes an idea of mediation. Fairclough (2003)
studies this mediated relationship between the text and the
society by looking at ‘orders of discourse’.
Van Dijk (1998) introduces a ‘socio-cognitive level’ to
his analysis and Scollon studies mediation by looking at
‘mediated action’ and ‘meditational means’ (Scollon, 2001).
The seventh principle is that CDA is interpretative and
explanatory. CDA goes beyond textual analysis. It is not only
interpretative but also explanatory in intent. These
interpretations and explanations are dynamic, open and may be
affected by new readings and new contextual information. The
eighth principle is that discourse, from the point of view of
CDA, is a form of social action. The principal aim of CDA is to
uncover opaqueness and power relationships. CDA is a socially
committed scientific paradigm. It attempts to bring about
change in communicative and socio-political practices. Van
Dijk in El-Sharkawy (2018) adds the features and the criteria
that CDA generally characterizes:
a. It is problem or issue oriented, rather than paradigm-
oriented.
b. It does not characterize a school, a field or a sub-
discipline of discourse analysis but rather an explicitly
critical approach, position or stance of studying text and
talk.
c. It is multidisciplinary approach, focusing on the
relations between discourse and society.
d. It may pay attention to all levels and dimensions of
discourse (that is, those of grammar, phonology, syntax,
semantics, etc.), style, rhetoric, schematic organization,
speech acts, pragmatic strategies and those of
interaction, among others.
25
e. Many studies in CDA are however not limited to these
purely “verbal” approaches to discourse but also pay
attention to other semiotic dimensions (pictures, film,
sound, music, gestures, etc.) of communicative events.
f. When studying the role of discourse in the society, CDA
especially focuses on (group) relations of power,
dominance and inequality and the ways these are
reproduced or resisted by social group members through
text and talk.
g. Much work in CDA deals with the discursively enacted
or legitimated structures and strategies of dominance
and resistance in social relationships of class, gender,
ethnicity, race, sexual orientation, language, religion,
age, nationality or world-region.
h. Much work in CDA is about the underlying ideologies
that play a role in the reproduction of or resistance
against dominance or inequality.
i. Among the descriptive, explanatory and practical aims
of CDA studies is the attempt to uncover, reveal or
disclose what is implicit, hidden or otherwise not
immediately obvious in relations of discursively enacted
dominance or their underlying ideologies. That is, CDA
specifically focuses on the strategies of manipulation,
legitimation, the manufacture of consent and other
discursive ways to influence the minds (and indirectly
the actions) of people in the interest of the powerful.
Van Dijk shows that CDA pays more attention to issues
and problems, particularly concerned with top down relations of
dominance than to bottom-up relations of resistance,
compliance and acceptance. Van Dijk (2009) claimed that CDA
is concerned with social problems, representing it as discourse
analysis with an attitude, a critical perspective, position or
attitude. In this view CDA emphatically opposes those who
abuse text and talk in order to establish, confirm or legitimate
their abuse of power: CDA does not deny but explicitly defines
and defends its own sociopolitical position. This does not mean
that power and dominance are not merely seen as unilaterally
26
imposed on others but they may seem jointly produced, e.g.
when dominated groups are persuaded, by whatever means, that
dominance is natural or otherwise legitimate. To Van Dijk,
although an analysis of strategies of resistance and challenge is
crucial for understanding of actual power and dominance
relations in the society, such an analysis needs to be included in
a broader theory of power, counter-power and discourse, critical
approach prefers to focus on the elites and their discursive
strategies for the maintenance of inequality.
In doing so, the relations between discourse structures
and power structures should be studied, for instance the usage
of directive speech acts, such as commands or orders may help
understand how power is enacted and how dominance is
reproduced. Moreover, the style and the rhetoric of the text that
create different strategies that aim at the concealment of social
power relations and how, such strategies are represented are
crucial to CDA. To Van Dijk, CDA is a complex,
multidisciplinary domain of study, is concerned with the
relations between discourse, power, dominance and social
inequality. It concerns the role of discourse in the (re)
production and challenge of dominance, the exercise of social
power by elites, institutions or groups, that results in social
inequality, including political, cultural, class, ethnic, racial and
gender inequality. It reveals and analyzes how power relations
are presented, legitimized, denied, concealed among
participants. The position of the discourse analyst in such social
relationships is to investigate and show what structures,
strategies or other properties of text, talk, verbal interaction or
communicative events that play a role in achieving power and
dominance (El-Sharkawy, 2018).
What is Critical in Discourse Analysis?
The term ‘critical’ may relate in the work of some
‘critical linguists’ and could be traced to the influence of the
Frankfurt School. In language studies, the term ‘critical’ was
first used to characterize an approach that was called Critical
Linguistics. Among other ideas, those scholars held that the use
27
of language could lead to a mystification of social events, which
systematic analysis could elucidate (Wodak, 2001).
In CDA, Lodges and Nilep (2007) explained what they
mean by ‘critical’ in their type of discourse analysis is in
relation to the analyst:
By “critical”, we mean to imply a broad understanding of
critical scholarship. On a general level, such scholarship is
characterized by careful analysis of empirical data. Moreover,
it entails a certain amount of distance from the data in order
to examine the issues from a wide, considered perspective (p.
4).
Lodges and Nilep (2007) established that the position of
the analyst as a scholar should be taken into account in such a
way that it makes critical scholarship to be motivated not only
to study the society for what it is but for what it might become.
In this way, critical scholarship desires to expose existing
wrongs in the society in an effort to shape a better world.
Critical approaches, therefore, take a keen interest in
understanding the workings of power in an effort to counter
abuses of power. Fairclough (2003) argued that the present form
of CDA implies showing connections and causes that are hidden
in its critical approach in such a way that the operations of
discursive patterns of ideology that can conceal features of the
social world can be decoded and uncovered.
To Fairclough (2003) critical means unsystematic in
approach and to be critical means to make opaque ideologies
and interconnectedness of things visible through analysis and to
criticize connections between properties of texts and social
processes and power relations, which are not obvious to people
who produce and interpret texts. CDA is critical because it
doesn’t only describe but it also interprets and explains the
relationship between the form (that is, grammar, morphology,
semantics, syntax and pragmatics) and the function (how people
use language in different situations to achieve an aim) of the
language. In doing so, the critical discourse analyst is not
neutral but explores hidden power in discourse and in relation to
wider, social and cultural formations.
28
In the same vein, Wodak (2001) distinguished critical
science from non-critical sciences as the former asks further
questions than the latter, such as those of responsibility,
interests and ideology. Instead of focusing on purely academic
or theoretical problems, CDA starts from prevailing social
problems and chooses the perspectives of those who suffer most
and critically analyzes those in power, those who are
responsible and those who have the means and the opportunity
to solve, such problems. According to Wodak (2001) to be
critical is to have a distance to the data, embedding the data in
the social, taking a political stance explicitly and a focus on
self-reflection as scholars doing research. This means
researchers should be objective in their analysis and subjective
to their results and findings that should be put in practical
seminars for teachers, doctors and civil servants or in writing
expert opinions or in devising school books. Wodak (2001) is of
the view that, critical theory should be directed at the totality of
society in its historical specificity (that is, discourse-historical
approach) and it should improve the understanding of the
society by integrating all the major social sciences, including
economics, sociology, history, political science, anthropology
and psychology.
Jorgensen and Phillips (2002) also argued that critical
approaches have in common the aim of carrying out critical
research, that is, to investigate and analyze power relations in
the society and to formulate normative perspectives, which a
critique of such relations can be made with an eye on the
possibilities for social change, though each perspective has a
range of distinctive philosophical and theoretical premises,
including particular understandings of discourse, social practice
and critique, which lead to particular aims, methods and
empirical focal points. The critical part in CDA seeks to create
awareness in agents of their own needs and interests. One of the
aims of CDA is to demystify discourses by deciphering
ideologies. Gee (2005) states that approaches to discourse
analysis that avoid combining a model of grammatical and
textual analysis (of whatever sort) with sociopolitical and
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critical theories of society and its institutions are not forms of
critical discourse analysis.
Hence ‘critique’ is essential in CDA approach since it
makes visible the interconnectedness of things. Fairclough
(2003) argued that the importance of critical language study
arises from the answers it introduces to questions of how and
why rather than just to answer what questions that focuses on
description and statement of facts. It also shows that CDA is
critical because it is used in special sense of aiming to show up
connections, which may be hidden from people, such as the
connection between the language, the power and the ideology
and it analyses social interactions focusing upon their linguistic
elements.
Intertextuality and (Inter) Disciplinarity
Whereas intertextuality is the communication between
different texts and resources and interdiscursivity is the
communication between different discourses, interdisciplinarity
is the communication between different disciplines, branches of
different or same science or methodologies. These three
processes are features of CDA and are used to help the analyst
understand, explain and analyze the complexity of intertextual
and interdiscursive texts. They are also interconnected and
dependent on each other and the following section explores
their meanings as used and referred in CDA.
Intertextuality
According to Fairclough (2003) intertextuality shows
how texts can transform prior texts and restructure existing
conventions (genres, discourses) to generate new ones. He
developed a three-dimensional framework for analyzing
intertextuality: the analysis of ‘discourse representation’,
generic analysis of discourse types and analysis of discourses in
the texts (El-Sharkawy, 2018). Discourse representation is a
form of intertextuality, which parts of previously encountered
texts are incorporated into a new text and are usually but not
always, explicitly marked with devices, such as quotation marks
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and reporting clauses. He argues that linguistic, such as
quotation and verbs of reporting are on a continuum with
presupposition, hedging, metaphor and perhaps an ultimately
infinite number of ways of representing discourses with
discourse. All of this representation of previously encountered
discourse is called discourse representation. In media discourse,
discourse representation accounts for a major part of what news
is: representations of what newsworthy people have said.
The intertextual analysis examines how writers draw on
other sources for the writing of their texts. It explores how the
writers include other sources in their texts, what types of
sources the writers used, how the writers used these sources and
how the writers positioned themselves in relation to other
sources to make their own statements. Bazerman (2004)
proposes the following procedures for analysing intertextuality.
a) Underline or highlight each reference in the text and
then create a list of all instances.
b) List how, such reference is expressed whether through a
direct quotation, indirect quotation or just paraphrase or
description.
c) Make comments on how or for what purpose the
intertextual element is being used in the new text.
d) Make observations and interpretations by considering
the reference in relation to the context of what the author
is saying.
e) Look for a pattern from which you start developing
conclusions, which again would depend on the purpose
of your examination.
In the same vein, Wang (2007) introduced a framework
for linguistically analyzing intertextuality in terms of the
writer’s ‘engagement’, which is divided into intra-vocalization
and extra-vocalization. ‘Intra-vocalisation’ is concerned with
the internal voice of the writer or speaker, which proclaims or
disclaims, while ‘extra-vocalisation’ is concerned with the
resources, which involve the inclusion in the text of some
explicitly external voice. Intra-vocalisation is considered under
the resources of ‘modality, proclaims and disclaims’, whereas
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extra-vocalisation is considered under the resources of
‘attribution’ (quoting or referencing the statements or points of
view of the external text).
Wang (2007, p.135) also developed the following
analytical framework of intertextuality to examine how writers
draw on the outside sources for the writing of their own texts:
1. Intertextual representation (How writers include the outside
sources in a text):
a. Direct quotation Inserted
b. Indirect quotation
c. Paraphrasing
d. Description Assimilated
2. Source type (What types of sources writers use):
a) Attributed
b) Personal or impersonal
c) Identified or unidentified
d) Specific or generic
e) Singular or plural
f) Status neutral or high or low status
g) Unattributed
h) Mentioning of a person, document, or statements
i) Comment or evaluation on a statement, text, or
otherwise invoked voice
j) Implicitly recognizable language and forms
3. Source function (What writers use outside sources for):
a. Background information
b. Evidence
c. Beliefs, ideas, issue circulated
d. Others
4. Endorsement (How the writers position themselves as writers
in relation to outside sources):
a) Non-endorsement(neutral) (responsibility delegated)
b) Endorsement (positive) (responsibility reclaimed or
shared)
c) Disendorsement(negative) (responsibility delegated)
To examine attribution, an analyst should
simultaneously consider the outside source in terms of textual
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integration, source type and endorsement. This framework
covers the explicit intertextual presentation (direct and indirect
quotation, paraphrasing and description) in a hierarchy from
inserted into assimilated materials. ‘Textual integration’
indicates the degree of integrating the material by the use of
paraphrase or by direct quoting. ‘Source type’ refers to the
source in more or less personalized, named, specific or
authoritative ways and ‘endorsement’ indicates various degrees
of support for the material.
Interdisciplinarity
Historically, Van-Leeuwen (2005) sketched three
approaches of interdisciplinarity: the centralist, the pluralist and
the integrationist. He pointed out that a centralist model of
interdisciplinarity is essentially a model of the relation between
different autonomous disciplines, each of which sees itself as
the center of the universe of knowledge and charts its relations
to other disciplines. The core of each discipline is formed by its
theories, methods and central subject matters. Relations to other
disciplines primarily concern overlapping subject matter,
specialist theoretical frameworks and methodologies.
The pluralist model brings all the disciplines together as
equal partners and as autonomous and self-sufficient in the way
they operate without affecting their identities or their values.
Like the pluralist model, the integrationist model focuses on
problems rather than methods and brings together researchers
from different disciplines. In this perspective, no single
discipline can satisfactorily address any given problem on its
own. As a result, disciplines are seen as interdependent and
research projects involve team work with specific divisions of
labour and specific integrative principles. Disciplines can no
longer function as traditional professions, with the autonomy to
define what will count as a research problem and how it will be
addressed, with their own professional associations and
boundary maintenance mechanisms (e.g. through specialist
terminologies) and with distinct perspectives and professional
identities.
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The idea of “discipline” is in effect narrowed down to
“skill” that can contribute in specific ways to integrated
projects. In such a context the linguist, for example, is not just a
linguist but one who is skillful in linguistics and knows how to
do certain types of linguistic research and can therefore, make a
specific and useful contribution to interdisciplinary research
projects in such a way that brings together the perspectives of
different disciplines on a given research problem and such
projects are interdisciplinary as a whole, but without affecting
other contributing disciplines or their status and identity as
autonomous research professionals.
Interdisciplinarity is different from intertextuality,
interdiscursivity and recontextualization. Interdisciplinarity
concerns with the communication of different disciplines
(sociology and linguistics) and intertextuality concerns with the
relations between one text and other texts on one hand and to
other social practices and activities on the other.
Interdiscursivity of a text refers to the presence of other genres
and styles of other texts. A single text may incorporate more
than one genre or style and may refer to and adopt genres and
styles, which relate to other texts. The concept of
recontextualisation is particularly useful as it allows analysis of
the shift of meanings either within a single genre or across
genres. In the process of recontextualisation meanings are
transformed, as discourse is reshaped and repeated in modified
form in different contexts. Blackledge (2005, p. 6) summarized
that CDA is fundamentally “political in orientation,
interdisciplinary in scholarship and diverse in focus”.
Transdisciplinarity
An important perspective in CDA is that it is very rare
for a text to be the work of any one person. In this way, texts
are sites of struggles as they involve traces of differing
discourses and ideologies. Moreover, CDA approach mediates
between social theories and linguistic theories. Therefore, the
CDA proponents believe that the complex interrelations
between discourse and society cannot be analyzed adequately
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unless linguistic and sociological approaches are combined.
Such communication with other disciplines of discourse
analysis makes CDA transdisciplinary (as opposed to merely
interdisciplinary), so the term transdisciplinary has recently
been preferred to interdisciplinary or multidisciplinary
(Blackledge, 2005).
Therefore, CDA emphasizes the need for
transdisciplinary work in order to gain a proper understanding
of how language functions in constituting and transmitting
knowledge, in organizing social institutions or in exercising
power. For this reason, CDA involves a theoretical synthesis of
conceptual tools developed in different theoretical schools, for
example, Foucault’s discursive formations, Bourdieu’s habitus
or register and code as defined by Halliday and Bernstein were
borrowed into CDA.
This heterogeneity of methodological and theoretical
approaches that can be found in this field of linguistics would
tend to confirm Van Dijk’s point that CDA and Critical
Linguistics (CL) are at most a shared perspective on doing
linguistic, semiotic or discourse analysis. CDA sees ‘language
as social practice’ and considers the context of language use to
be crucial. This form of cooperation is used to treat different
subjects within a framework of a transdisciplinary design. This
means that, discourse analysis in this view involves working in
dialogue with particular bodies of social theory and approaches
to social research, identifying specific research questions for
discourse analysis within the object of research, seeking to
ensure that relations between discourse and other social
elements are properly addressed.
However, transdisciplinarity is not opposite to
specialization but disciplines complement each other and they
coexist in a form of cooperation, which helps to treat a subject
from differing disciplinary perspectives. Such cooperation leads
to a bundling or clustering of problem-solving approaches
rooted in different disciplines and drawing on a pool of theories.
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The Critique of CDA
CDA is often critiqued from its most controversial
paradigm of Conversational Analysis (CA) in the following
points (El-Sharkawy, 2018). First, political and social
ideologies are projected onto the data rather than being revealed
through the data. This means that the critic analyst enters his or
her analysis with predefined criteria or patterns to apply to
chosen parts of the text (i.e., the target data of analysis).
Second, there is no balance between social theory and linguistic
method. Third, many discourse analyses are extracted from
social contexts. This implies that what Schegloff (1999) pointed
out, that many linguists working in CDA invoke many concepts
from social theory, such as ‘power differences or hegemony’,
when it is not always so clear how the participants are
linguistically indexing something like what ‘power’ or even
what power means. Fourth, there is no consistent or rigorous
methodology of CDA application and analysis. Schegloff
(1999) asks proponents of CDA what standards are being used
to ground interpretation.
For the first point, Fairclough and Wodak (1997) argue
that CDA is not seen as holistic or a closed paradigm of specific
set of principles but an approach or a point of view that may
change over the years. Similarly, Van Dijk (1993) pointed out
that CDA does not primarily aim to contribute to a specific
discipline, paradigm, school, or discourse theory. Rather, it is
interested and motivated by pressing social issues, which it
hopes to better understand through discourse analysis. For the
second, Van Dijk (1993) shows that theories, descriptions,
methods and empirical work are chosen or elaborated as a
function of their relevance for the realization of the relative
sociopolitical goal because it is impossible to analyze the whole
data in details. For the third, CDA is a transdisciplinary
approach due to the difficulty and complexity of its task of
uncovering social inequality and power abuse. Discourse
analysis here involves a political critique of those responsible
for its perversion in the reproduction of dominance and
inequality. In doing so, critical discourse analyst should be
36
aware of social and political issues. This means that CDA is
ideological since ‘any critique by definition presupposes an
applied ethics’.
Billig (2002) argues that analysts should not have to
wait until “power” or “abuse” are actually brought up or
attended to before the analyst can invoke them. Invoking them
need not be an imperialistic move but rather an informed and
cautionary attempt to fill-out the social and cultural forces
which have come to make possible the encounter in the first
place. Billig (2002) basically argues that Conversational
Analysis (CA) should become more ideological in its fine-
grained efforts and less neutral. Because Billig believes that a
non-ideological analysis is impossible, he wants to argue that
CA should aim less for pure empiricism and more for an open
and reflexive ideological presentation of its assumptions and
motives.
Silverman (2001) concluded that both CDA and CA
have different analytic agendas and starting points and each
orientation is operating at a different level of analysis. CA, for
example, is simply designed to reveal how things like
pronomial self-repair strategies are accomplished during
question-and-answer exchanges while CDA is designed to
uncover something like the ideological workings of hegemonic
language practices. The debate isn’t that CA is completely
lacking of the larger socio-political contexts or that CDA is
altogether ignorant of detailed linguistic patterns and micro-
discursive constructions. The debate is really about when and
how things like “context” and “participant orientation” are
brought into the analytic discussion and how they ground
claims-making.
Fairclough and Wodack (1997) suggest that such
critiques exist because of the absence of references of
researchers, that is any criticism of CDA should specify, which
research or researcher they relate to because CDA cannot be
viewed as a holistic or closed paradigm and, such program or
set of principles has changed over the years.
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Philo (2012, p. 17) argued that “critical discourse
analysis would be more powerful if it routinely included a
developed account of alternatives”, claiming that CDA which
remains text-based analysis encounters a series of problems
specifically in its inability to show the relationships between a
text and social interests; the existence of the diversity of social
accounts compared to what is present (and absent) in a specific
text and the impact of external factors, such as professional
ideologies on the manner, which the discourses are represented
as well as the fact that the text actually has different meanings
to different types of receivers. He also claimed that such
analysis, in certain cases, may affect the accuracy of
representation of texts as well as some participants (i.e.,
politician speakers) may exaggerate what they are saying or
may speak of things they want to happen as if they are already
happening and this may create misinterpretation of discourse.
To handle such problems, Philo suggests that CDA-analysts
must fill the gap between text and reality or between what is in
the text and what is outside the text.
Issues to Analyse in CDA
1. Gender issues.
2. Issues of racism.
3. Media content.
4. Political communication.
5. Identity research, etc.
Therefore, CDA is the way and manner language is used
in the text. It involves the use of power to command the
language.
(2) Semiotic Analysis (SA)
This method is interested in examining how signs,
natural or artificial, function in the text. The aim of symiotic
analysis is to understand, analyse and interpret signs as text.
Semiotic analysis of media texts is an analysis of the language
of signs and symbols in the media texts. This analysis is closely
linked to the iconographic analysis. Semiotics is a discipline, in
38
which culture, society and natural phenomena are explored as
signs. The fundamental question in semiotics is how meanings
are formed. Semiotic research approaches signs as existing in
various forms: pictures, words, letters, objects, natural objects,
gestures, phenomena and actions. Semiotics explores the
content of signs, their use and the formation of meanings of
signs at both the level of a single sign and the broader systems
and structures formed by signs.
If you use semiotic analysis (involving semiotic
concepts and models) your aims are to analyze, understand and
interpret signs, the meanings of signs and the interaction of
signs and sign systems. Semiotic analysis views the sign and
use of signs as a part of a sign system. A sign system directs the
use of the sign and thus, the system always has an effect on the
contents of individual signs. A sign is never independent of the
meanings and the use of other signs. Semiotic analysis uses
both qualitative and interpretative content analysis involving
semiotic concepts and terms. As Rose (2001, p. 69) explained,
semiotics “offers a very full box of analytical tools for taking an
image apart and tracing how it works in relation to broader
systems of meaning”. The major strength of semiotics is that it
is a sophisticated analytical tool for explaining how signs make
sense.
Semiotics and Semiotic Analysis
Within semiotics, there are two major models of how a
sign is structured: the Saussurian model and the Peircean model
(Chandler, 2001). According to the Saussurian model, a sign
consists of the signifier and the signified and signification is the
relationship between the two (Chandler, 2001). In Saussure’s
model, both the signifier and the signified are abstract rather
than material. The signifier in Saussure’s model is “the form,
which the sign takes” and a signified is “the concept it
represents”. A signified is not to be recognized as a referent;
rather, it is a concept in the mind. In other words, rather than an
actual object, it is the notion of an object. However, people who
have adopted Saussure’s model now take the signifier as the
39
material form of the sign, which can be seen, heard, touched,
smelled or tasted. The signified, on the other hand, is still
treated as a mental concept but it is pointed out that it might as
well refer to material things in the world (Chang, 2008).
Pierce’s model consists of the representamen, the
interpretant and the object. The representamen is the mode,
which a sign adopts, which is similar to Sausurre’s signifier.
The interpretant is how one makes sense of the sign, which is
like Saussure’s signified but it is itself a sign in the mind of the
interpreter. The object is the thing that the sign stands for within
objective reality. According to Pierce, there were three kinds of
signs: the icon, the index and the symbol (Rose, 2001). When
the signs are at the iconic stage, the photographic images look
just like the thing or person that are being represented and the
signifier and the signified at this stage are similar to each other.
An example of an iconic sign is a portrait of a person
representing the person portrayed. Other signs go further than
the simple portrayal of a person or a thing. The signs at the
indexical stage are used to denote an extra meaning to the one
that is obviously represented. The connection is made between
the sign and what it is signifying through causation or analogy;
thus, the relationship between the signifier and signified are not
arbitrary.
A postcard of the Eiffel tower that makes people think
about Paris is an illustration of indexical signs (Rose, 2001).
Signs at the symbolic stage have a conventionalized and clearly
arbitrary relation between signifier and signified. In this stage,
the signifier is neither a copy nor bears resemblance to the
signified; people think of the signified when they see the
signifier because they have learned that connection. A rose
symbolizing love or passion is an example of a symbolic sign.
Although Saussure and Pierce are considered the fathers of
semiotics, Roland Barthes’ writings led to the widespread use of
semiotics in the cultural studies area (Chang, 2008). From
Barthes’ perspective, signs could be denotative or connotative
(Rose, 2001). Signs at the denotative level are easy to interpret
but signs at the connotative level are subtle and more difficult to
40
decode because they have a higher-level meaning. More
specifically, denotation refers to the literal, obvious, superficial
meaning of a sign (Chandler, 2001).
Connotation, on the other hand, refers to the ideological
and individual affiliation of the sign. These associations are in
relation with the interpreter’s background, such as class, age
and gender. Therefore, signs in their connotations allow more
room for interpretation than they can in their denotations. In
relation to the denotation and connotation is the notion of myth.
Myth is a form of ideology. It converts things that happened
into natural phenomenon; it makes natural the way things are. In
other words, myths are the dominant ideologies that people
don’t question.
Barthes in Chang (2008, p. 9) declared that: Semiology
therefore aims to take in any system of signs, whatever their
substance and limits; images, gestures, musical sounds, objects
and the complex associations of all of these, which form the
content of ritual, convention or public entertainment: these
constitute, if not languages, at least systems of signification.
The approach of semiotics analysis entails a critical change
from “the simple interpretation of objects and forms of
communication to investigations of the organization and
structure artifacts and, in particular, to enquiry into how they
produce meaning” (Dyer, 1982, p. 115). In other words,
semiotic analysis focuses on interpreting an image by looking at
the signs within it. It allows researchers to make overt what is
usually hidden (Chandler, 2001).
Conducting a semiotics approach helps a researcher to
decode the signs and read the latent messages in an image.
Semiotics, like case studies, deal with a comparatively small
amount of images. The result of the analysis only represents the
data rather than a wider range of material. Its results are not
generalisable; thus, the results “stand or fall on its analytical
integrity” (Rose, 2001).
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Steps in Semiotic Analysis
Rose (2001) proposed steps for analyzing the signs in an
image. First, identify the signs in the image. Then determine
what these signs are in themselves. Find out how the signs
relate to each other and then find out the relations to broader
meaning systems. Finally, go back to the signs through their
codes to discover the specific enunciation of ideology and
mythology. Semiotics analysis is an efficient tool for analyzing
the visual meaning in photos; it is a method to deduce emotions
and associations from signs in images. It takes into account the
effects of the images through its construction and its social
conditions.
On the other hand, semiotics analysis has some
drawbacks. First, its results are not generalizable (Chang, 2008).
Second, it contains elaborate terminology that can be confusing.
While some terms are useful and are clearly defined, some are
unnecessary and can create confusion. Lastly, while images are
polysemic and open for different interpretation, semiotics
analysis often provides a single interpretation for one image.
Types of Sign
Kurfi (2019) identified the following:
1. Symptoms: they are normally warning signals and they
could be artificial or natural.
2. Signals: this perhaps explains things that can respond to
stimulus.
3. Icons: they are representation of resemblance that are
often meaningful.
4. Indexes: this is a representation of things in relation to
existence or space.
5. Symbols: these are signs that stand for reference in an
arbitrary or conventional way.
6. Names: this is an identifier assigned to an object, but act
or living thing.
Approaches to Semiotic Analysis
a. Examine the message.
42
b. Examine the signs.
c. Identify the different signs.
d. Correlate signs and reality to see the extent they
represent reality, how close they portray reality.
(3) Qualitative Content Analysis (QCA)
Unlike quantitative content analysis, which is primarily
concerned with measurement and quantification of variables,
qualitative content analysis method is interested in interpreting
meaning from the context of text data in a systematic and
context procedure (Kurfi, 2019). The idea is to build or support
an argument. Qualitative content analysis is a research method
for the subjective interpretation of the content of text data
through the systematic classification process of coding and
identifying themes or patterns. It is an approach of empirical,
methodological controlled analysis of texts within their context
of communication, following content analytic rules and step by
step models, without rash quantification. Therefore, any
qualitative data reduction and sense-making effort that takes a
volume of qualitative material and attempts to identify core
consistencies and meanings can be said to be qualitative content
analysis. For instance, one can interpret text data to build or
support a document. The interpretation of text data can be in
two ways:
a) Manifest interpretation: this connotes what has been said
by the author, producer, originator, organisation, etc.
b) Latent meaning interpretation: this entails what is
intended to be said. Here, you may not see them in
documents. It is meaning implied in text, signified by
the context and adjoining texts.
Therefore, content that can be analyse include: text
materials of any type, book, magazine, etc. or any visual text.
One can also study audio and visual materials, field notes, etc.
The Process of Qualitative Content Analysis
The process of qualitative content analysis often begins
during the early stages of data collection. This early
43
involvement in the analysis phase will help you move back and
forth between concept development and data collection and may
help direct your subsequent data collection toward sources that
are more useful for addressing the research questions (Miles and
Huberman, 1994). To support valid and reliable inferences,
qualitative content analysis involves a set of systematic and
transparent procedures for processing data. Some of the steps
overlap with the traditional quantitative content analysis
procedures, while others are unique to this method. Depending
on the goals of your study, your content analysis may be more
flexible or more standardized but generally it can be divided
into the following steps, beginning with preparing the data and
proceeding through writing up the findings in a report.
Step 1: Prepare the Data
Qualitative content analysis can be used to analyze
various types of data but generally the data needs to be
transformed into written text before analysis can start. If the
data come from existing texts, the choice of the content must be
justified by what you want to know (Patton, 2002). Qualitative
content analysis is most often used to analyze interview
transcripts in order to reveal or model people’s information
related behaviours and thoughts. When transcribing interviews,
the following questions arise: (1) should all the questions of the
interviewer or only the main questions from the interview guide
be transcribed; (2) should the verbalizations be transcribed
literally or only in a summary and (3) should observations
during the interview (e.g., sounds, pauses and other audible
behaviours) be transcribed or not?. Your answers to these
questions should be based on your research questions. While a
complete transcript may be the most useful, the additional value
it provides may not justify the additional time required to create
it.
Step 2: Define the Unit of Analysis
The unit of analysis refers to the basic unit of text to be
classified during content analysis. Messages have to be unitized
44
before they can be coded and differences in the unit definition
can affect coding decisions as well as the comparability of
outcomes with other similar studies. Therefore, defining the
coding unit is one of your most fundamental and important
decisions (Weber, 1990). Qualitative content analysis usually
uses individual themes as the unit for analysis, rather than the
physical linguistic units (e.g., word, sentence or paragraph)
most often used in quantitative content analysis. An instance of
a theme might be expressed in a single word, a phrase, a
sentence, a paragraph or an entire document. When using theme
as the coding unit, you are primarily looking for the expressions
of an idea (Minichiello, Aroni, Timewell and Alexander, 1990).
Thus, you might assign a code to a text chunk of any size, as
long as that chunk represents a single theme or issue of
relevance to your research question(s).
Step 3: Develop Categories and a Coding Scheme
Categories and a coding scheme can be derived from
three sources: the data, previous related studies and theories.
Coding schemes can be developed both inductively and
deductively. In studies where no theories are available, you
must generate categories inductively from the data. Inductive
content analysis is particularly appropriate for studies that
intend to develop theory, rather than those that intend to
describe a particular phenomenon or verify an existing theory.
When developing categories inductively from raw data, you are
encouraged to use the constant comparative method. Since it is
not only able to stimulate original insights but is also able to
make differences between categories apparent. The essence of
the constant comparative method is (1) the systematic
comparison of each text assigned to a category with each of
those already assigned to that category, in order to fully
understand the theoretical properties of the category and (2)
integrating categories and their properties through the
development of interpretive memos. For some studies, you will
have a preliminary model or theory to base your inquiry. You
can generate an initial list of coding categories from the model
45
or theory and you may modify the model or theory in the course
of the analysis as new categories emerge inductively (Miles and
Huberman, 1994).
The adoption of coding schemes developed in previous
studies has the advantage of supporting the accumulation and
comparison of research findings across multiple studies. In
quantitative content analysis, categories need to be mutually
exclusive because confounded variables would violate the
assumptions of some statistical procedures (Weber, 1990).
However, in reality, assigning a particular text to a single
category can be very difficult. Qualitative content analysis
allows you to assign a unit of text to more than one category
simultaneously. Even so, the categories in your coding scheme
should be defined in a way that they are internally as
homogeneous as possible and externally as heterogeneous as
possible. To ensure the consistency of coding, especially when
multiple coders are involved, you should develop a coding
manual, which usually consists of category names, definitions
or rules for assigning codes and examples (Weber, 1990). Some
coding manuals have an additional field for taking notes as
coding proceeds. Using the constant comparative method, your
coding manual will evolve throughout the process of data
analysis and will be augmented with interpretive memos.
Step 4: Test Your Coding Scheme on a Sample of Text
If you are using a fairly standardized process in your
analysis, you’ll want to develop and validate your coding
scheme early in the process. The best test of the clarity and
consistency of your category definitions is to code a sample of
your data. After the sample is coded, the coding consistency
needs to be checked, in most cases through an assessment of
inter-coder agreement. If the level of consistency is low, the
coding rules must be revised. Doubts and problems concerning
the definitions of categories, coding rules or categorization of
specific cases need to be discussed and resolved within your
research team (Schilling, 2006). Coding sample text, checking
coding consistency and revising coding rules is an iterative
46
process and should continue until sufficient coding consistency
is achieved.
Step 5: Code All the Text
When sufficient consistency has been achieved, the
coding rules can be applied to the entire corpus of text. During
the coding process, you will need to check the coding
repeatedly, to prevent “drifting into an idiosyncratic sense of
what the codes mean” (Schilling, 2006). Because coding will
proceed while new data continue to be collected, it’s possible
(even quite likely) that new themes and concepts will emerge
and will need to be added to the coding manual.
Step 6: Assess Your Coding Consistency
After coding the entire data set, you need to recheck the
consistency of your coding. It is not safe to assume that if a
sample was coded in a consistent and reliable manner, the
coding of the whole corpus of text is also consistent. Human
coders are subject to fatigue and are likely to make more
mistakes as the coding proceeds. New codes may have been
added since the original consistency check. Also, the coders’
understanding of the categories and coding rules may change
subtly over the time, which may lead to greater inconsistency.
For all these reasons, you need to recheck your coding
consistency.
Step 7: Draw Conclusions from the Coded Data
This step involves making sense of the themes or
categories identified and their properties. At this stage, you will
make inferences and present your reconstructions of meanings
derived from the data. Your activities may involve exploring the
properties and dimensions of categories, identifying
relationships between categories, uncovering patterns and
testing categories against the full range of data. This is a critical
step in the analysis process and its success will rely almost
wholly on your reasoning abilities.
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Step 8: Report Your Methods and Findings
For the study to be replicable, you need to monitor and
report your analytical procedures and processes as completely
and truthfully as possible (Patton, 2002). In the case of
qualitative content analysis, you need to report your decisions
and practices concerning the coding process, as well as the
methods you used to establish the trustworthiness of your study.
The qualitative content analysis does not produce counts
and statistical significance; instead, it uncovers patterns, themes
and categories important to a social reality. Presenting research
findings from qualitative content analysis is challenging.
Although it is a common practice to use typical quotations to
justify conclusions, you also may want to incorporate other
options for data display, including matrices, graphs, charts and
conceptual networks. The form and extent of reporting will
finally depend on the specific research goals.
When presenting qualitative content analysis results, you
should strive for a balance between description and
interpretation. Description gives your readers background and
context and thus needs to be rich and thick. Qualitative research
is fundamentally interpretive and interpretation represents your
personal and theoretical understanding of the phenomenon
under study. An interesting and readable report “provides
sufficient description to allow the reader to understand the basis
for an interpretation and sufficient interpretation to allow the
reader to understand the description” (Patton, 2002, p.503-504).
Objective of Qualitative Content Analysis
a) To create evidence for the content.
b) To build or support an argument.
c) To persuade an intelligent reader.
Procedures in Qualitative Content Analysis
a. Situate the content within the context of the study.
b. Follow the rules of analysis.
c. Identify the content. That is, create content categories
and unit of analysis.
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d. Develop criteria for reliability and validity.
Approaches to Qualitative Content Analysis
(a) Conventional qualitative content analysis: here, coding
categories are derived within the content of the text.
(b) Directed qualitative content analysis: here, analysis
begins with a theory or research findings.
(c) Summative qualitative content analysis: this involves
counting and comparism of keywords. That is, idioms,
figures of speech, etc.
(4) Text and Textual Analysis (TTA)
The main focus is on media content as far as text and
textual analysis is concern. TTA involves applying a form of
textual analysis to a series of printed, visual or audio text. In
text and textual analysis method, researchers tend to highlight
the common codes, terms, ideologies and individual that
dominates the media content. Textual analysis is a qualitative
method for gathering, processing and interpreting text data. This
methodology is mainly used in academic research to analyze
content related to the media and communication studies,
popular culture, sociology and philosophy. In this case, the
purpose of textual analysis is to understand the cultural and
ideological aspects that underlie a text and how they are
connected with the particular context, which the text has been
produced. In short, textual analysis consists of describing the
characteristics of a text and making interpretations to answer
specific questions.
Textual analysis is a broad term for various research
methods used to describe, interpret and understand texts. All
kinds of information can be gleaned from a text from its literal
meaning to the subtext, symbolism, assumptions and values it
reveals. The methods used to conduct textual analysis depend
on the field and the aims of the research. It often aims to
connect the text to a broader social, political, cultural or artistic
context.
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Textual analysis is a method that involves understanding
language, symbols or pictures present in texts to gain
information regarding how people make sense and
communicate life and life experiences. Visual, written or
spoken messages provide clues to ways through which
communication may be understood. Often the messages are
understood as influenced by and reflective of larger social
structures. For example, such messages may reflect or may
challenge historical, cultural, political, ethnical contexts for
which they exist. Therefore, the analyst must understand the
broader social structures that influence the messages present in
the text under investigation.
Textual Analysis in Cultural and Media Studies
In the fields of cultural studies and media studies,
textual analysis is a key component of research. Researchers in
these fields take media and cultural objects, for example, music
videos, social media content, billboard advertising and treat
them as text to be analyzed.
Usually, working within a particular theoretical
framework (for example, using postcolonial theory, media
theory or semiotics), researchers seek to connect elements of
their texts with issues in contemporary politics and culture.
They might analyze many different aspects of the text:
a) World choice.
b) Design elements.
c) Location of the text.
d) Target audience.
e) Relationship with other texts.
Textual analysis in this context is usually creative and
qualitative in its approach. Researchers seek to illuminate
something about the underlying politics or social context of the
cultural objective they are investigating.
Difference between Textual Analysis and Content Analysis
When one talks about textual analysis, one is referring to
a process of data gathering and analyzing of text data. This
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qualitative method examines the structure, content and meaning
of a text and how it relates to the historical and cultural context
in which it was produced. To do so, textual analysis combines
knowledge from different disciplines, like linguistics and
semiotics.
Content analysis on the other hand can be considered as
a subcategory of textual analysis, which intends to
systematically analyse text, by coding the elements of the text to
get quantitative insights. By coding text (that is, establishing
different categories for the analysis), content analysis makes it
possible to examine large sets of data and make replicable and
valid inferences. Sitting at the intersection between qualitative
and quantitative approaches, content analysis has proved to be
very useful to study a wide array of text data from newspaper
articles to social media messages within many different fields
that range from academic research to organisational or business
studies.
Methods and Techniques
Here, the book lays out some of the most frequent
methods and techniques for automated textual analysis. The
basic methods include:
i. World Frequency: it helps you to find the most recurrent
terms or expression within a set of data. Counting the
times a word is mentioned in a group of texts can lead
you to interesting insight, for example, when analysing
customer feedback responses. If the terms ‘hard to use’
or ‘complex’ often appear in comments about your
product, it may indicate you need to make adjustments.
ii. Collocation: by ‘collocation’ it means a sequence of
words that frequently occur together. Collocations are
usually bigrams (a pair of words) and trigrams (a
combination of three words). ‘Average salary’, ‘global
market’, ‘close a deal’, make an appointment’, ‘attend a
meeting’ are examples of collocations related to
business.
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In textual analysis, identifying collocation is useful to
understand the semantic structure of a text. Counting
bigrams and trigrams as one word improves the
accuracy of the analysis.
iii. Concordance: human language is ambiguous;
depending on the context, the same word can mean
different things. Concordance is used to identify
instances in which a word or a series of words appear, to
understand its exact meaning. For example, here are a
few sentences from product reviews containing the word
‘time’:
Preceding Context
Target
Following Context
I can advertise on
different platforms at
the same
time
without having to
register
I have saved a lot of
time
and the results were
very good
It is difficult for first
time
users or people who
don’t know how to
customize a form
It offers segmentation
time
zone and other
integration tools
Questions about Text and Textual Analysis
Kurfi (2019) outlined questions about text and textual
analysis as follows:
a. What can be said about the individual feature in the
text?
b. Who are the contributors of the text?
c. How are the text formed and presented?
d. What are the terms and phrases and what are their
meanings?
e. What are the assumptions imbedded in the text?
Ideological Codes in Media Content
a) One can identify this at the editorial, news writing and
features.
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b) Interpretation of language.
c) Symbolism (the representation of visual text).
d) Social and cultural values (cultural representation)
e) Analysis of advertising text and its impact on
consumers.
Therefore, text for analysis could be film, music, songs,
political speeches, posters, cartoons, pictures, radio
programmes, etc. all these are viewed as text.
(5) In-depth Interview (IDI)
This is a method that involves conducting an intensive
individual face-to-face interaction with respondents to explore
their perspective on a particular issue. In-depth interview is
useful when you want details or first-hand information about
person’s thoughts and behaviour. According to Berry (1999) In-
depth interviewing is widely used in educational research and is
generally regarded as a powerful tool in extracting data, in
particular qualitative in nature. In-depth interviewing has the
distinct features of being an open situation, allowing new
research direction to emerge through using techniques, such as
probing.
In-depth interview is an open-ended, discovery-oriented
method to obtain detailed information about a topic from a
stakeholder. In-depth interview is a qualitative research method;
its goal is to explore in-depth a respondent’s point of view,
experiences, feelings and perspectives. In other words, an in-
depth interview is a qualitative research technique that allows
person to person discussion. It can lead to increased insight into
people’s thoughts, feelings and behaviour on important issues.
This type of interview is often unstructured and therefore
permits the interviewer to encourage an informant (respondent)
to talk at length about the topic of interest.
One essential element of all interviews is the verbal
interaction between the interviewer and the interviewee(s).
Hitchcock in Berry (1999) stresses that central to the interview
is the issue of asking questions and this is often achieved in
qualitative research through conversational encounters.
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According to Boyce and Neale (2006) in-depth interviews are
useful when you want detailed information about a person’s
thoughts and behaviours or want to explore new issues in depth.
Interviews are often used to provide context to other data (such
as outcome data), offering a more complete picture of what
happened in the programme and why.
In-depth interviews should be used in place of focus
groups if the potential participants may not be included or
comfortable talking openly in a group or when you want to
distinguish individual (as opposed to group) opinions about the
programme. The process for conducting in-depth interviews
follows the same general process as is followed for other
research: plan, develop instruments, collect data, analyze data
and disseminate findings.
The Typologies of In-depth Interview
a) Information, conversational interview: this is the type of
interview whereby questions are not predetermined.
b) General interview guide approach: here, the aim is to
collect general information and not within a particular
context. You can also give the questions to the
respondents before the actual time for the interview.
c) Standardize or open ended interview: this is when you
have same questions. All the questions are open ended.
d) Close fixed responses interview: same questions but
such question are closed ended which are often asked to
the interviewee.
Interview Guides
Kurfi (2019) outlined the following as interview guides:
a. Introduce yourself and explain the purpose of your
interview.
b. Ensure that the respondents are fully aware of the
essence of the study.
c. You should develop relevant questions that will answer
your research questions.
d. Grouping the questions into themes.
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e. Seek for additional questions where necessary. This
means asking follow-up questions.
f. Make questions very easy to understand.
g. Avoid leading questions (questions that will predict your
outcome or predetermined expectations).
h. Allow the respondents to explain himself for herself
freely.
The Basic Approaches of Conducting In-depth Interview
As in-depth interviewing often involves qualitative data,
it is also called qualitative interviewing. In view of this, Patton
in Berry (1999) suggests three basic approaches to conducting
qualitative interviewing of which the researcher selected the
second approach as the most tenable. These approaches are:
i. The informal conversational interview: this type of
interview resembles a chat, during which the
informants may sometime forget that they are being
interviewed. Most of the questions asked will flow
from the immediate context. Informal conversational
interviews are useful for exploring interesting
topic(s) for investigation.
ii. The general interview guide approach (commonly
called guided interview): when employing this
approach for interviewing, a basic checklist is
prepared to make sure that all relevant topics are
covered. The interviewer is still free to explore,
probe and ask questions deemed interesting to the
researcher. This type of interview approach is useful
for eliciting information about specific topics. The
general interview guide approach is useful as it
allows for in-depth probing while permitting the
interviewer to keep the interview within the
parametres traced out by the aim of the study.
iii. The standardized open-ended interview: researchers
using this approach prepare a set of open-ended
questions which are carefully worded and arranged
for the purpose of minimising variation in the
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questions posed to the interviewees. This method is
often preferred for collecting data when two or more
researchers are involved in the data collection
process. Although this method provides less
flexibility for questions that the other two mentioned
previously, probing is still possible, depending on
the nature of the interview and the skills of the
interviewers.
Features of the In-depth Interview
According to Legard, Keegan and Ward (2014) the
following are the key features of the in-depth interview method:
Combined Approach: the first feature of the In-depth
Interview is that it is intended to combine structure with
flexibility. Even in the most unstructured interviews, the
researcher will have some sense of the themes he wishes to
explore and interviews will generally be based on some form of
topic guide (or interview guide) setting out the key topics and
issues to be covered during the interview. However, the
structure is sufficiently flexible to permit topics to be covered in
the order most suited to the interviewee, to allow responses to
be fully probed and explored, and to allow the researcher to be
responsive to relevant issues raised spontaneously by the
interviewee.
Interactivity: the second feature is that the interview is
interactive in nature. The material is generated by the
interaction between the researcher and the interviewee. The
researcher will ask an initial question in such a way to
encourage the interviewee to talk freely when answering the
question.
Probe: thirdly, the researcher uses a range of probes and
other techniques to achieve depth of answers in terms of
penetration, exploration and explanation. An initial response is
often at a fairly ‘surface’ level: the interviewer will use follow-
up questions to obtain deeper and fuller understanding of the
participant’s meaning. The in-depth format also permits the
researcher to explore fully all the factors that underpin
56
participants’ answers: reasons, feelings, opinions and beliefs.
This furnishes the explanatory evidence that is an important
element of qualitative research.
Generative: fourthly, the interview is generative in the
sense that new knowledge or thoughts are likely at some stage,
to be created. The extent to, which this is so may vary
depending on the research questions but it is likely that the
participant will at some point direct themselves or be directed
by the researcher down avenues of thought they have not
explored before. Participants may also be invited to put forward
ideas and suggestions on a particular topic and to propose
solutions for problems raised during the interview.
Finally, these key features together mean that qualitative
interviews are mostly conducted face-to-face. The interview is
an intense experience for both parties involved and a physical
encounter is an essential context for an interview which is
flexible, interactive and generative, which meaning and
language is explored in depth.
Steps or Process in Conducting In-depth Interview
Kvale (1996) established seven stages of conducting in-
depth interviews: thematizing, designing, interviewing,
transcribing, analyzing, verifying and reporting.
Stage 1: thematizing: at this stage, the researcher
clarifies the purpose of the interviews. And having ascertained
the purpose of the interview to be information gathering in
order to answer the research questions of the study, the
researcher pinpoints the key information he wants to gather
through the in-depth interview process.
Stage 2: designing: immediately after the researcher had
determined what he wants to know, the researcher designs a
way to elicit this information through the interview process. An
interview guide that includes the key topics and questions will
be designed as the formal plan for collecting information. The
interview guide helps the interviewer to focus on topics that are
important to explore, maintain consistency across interviews
57
with different respondents and stay on track during the
interview process.
Stage 3: interviewing: at the beginning of the interview,
the researcher makes introductions, explains the purpose of the
study and tells the respondents to be at ease that information
from them will be confidential. The researcher tries to obtain
permission from the respondents to audio record the session.
Some of the respondents may decline this request and the
researcher may settle for note-taking only. But for those
respondents that grant the researcher’s request to record the
interview session, the researcher records the interview while
also taking notes. At this stage, the researcher makes listening
and observing his primary responsibility in order to guide the
respondents through conversations that exhaustively explored
the important issues in the interview guide.
Stage 4: transcribing: after the interview sessions are
concluded, the next thing is the transcribing stage where the
researcher creates a verbatim text of each interview by writing
out each question and response using the audio recording and
the notes taken during the interview.
Stage 5: analyzing: after transcribing the interview, the
researcher re-reads the interview transcripts to identify themes
that emerge from the respondents’ answers. The researcher does
this to enable him organise his analysis, in essence synthesizing
the answers to each research question.
Stage 6: verifying: the researcher at this point uses
constant comparism of data to check the credibility of the
information gathered. Through this method, the researcher will
use multiple perspectives to interpret a single set of information.
When the researcher discovers that each participant said the
same thing (although from different point of view) in the
interviews, then the information is considered to be valid.
Stage 7: reporting: the researcher at this point is
expected to follow Kvale’s stages of conducting an in-depth
interview. In between Kvale’s thematizing and designing, a
researcher should include “planning” and this include making
contact and getting agreement to undertake interviews.
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Advantages of In-depth Interviews
a) Yields a high percentage of returns, since most people
can be reached and are willing to respond to questions
asked.
b) Information obtained is likely to be richer than that
collected through questionnaires.
c) Information about the personal characteristics and
environment of the respondents can be obtained.
d) Accurate records of the subjects’ responses can be kept,
particularly, if scoring and test devices are employed.
e) Visual materials to which the respondent is to react can
be presented, etc.
Disadvantages of In-depth Interviews
a. Too much time is required to conduct interviews.
b. The interviewer may ask questions, which provide
answers that accord with his views or ask questions
from only people who share common beliefs with him.
c. Lack of training or experience in the use of the interview
may cause the interviewer to record data in a manner
that makes the returns incomplete and inaccurate.
d. Interviews are difficult to conduct in situations where
respondents are workers, especially if such interviews
must be conducted in the homes. If a large number of
respondents are involved only few people can be
reached by a single interviewer each evening, etc.
(6) Focus Group Discussion (FGD)
The first requirement is that when the population is very
small, this method is suitable. As long as the population is large,
one cannot go for FGD. Focus Group Discussion is an interview
conducted with six to 12 people as a group simultaneously,
witha moderator leading the discussion about a specific topic.
Its identified characteristic is that it is a controlled group
discussion. It is used to understand the reason behind a
phenomenon, to see how a group of people interpret a certain
59
phenomenon or test preliminary ideas or plans. When properly
conducted, it is a natural method for eliciting group opinion on
specific issues in a social setting. It has an advantage over the
individualistic respondent interview when natural responses are
expected. FGD serves as an influential forum whereby
individuals within the group have their personal views
moderated by the responses of other members of the group.
Therefore, the application of FGD should be able to
satisfy the following criteria:
a. Small population.
b. It involves attitudes, opinion, views or perceptions.
c. The minimum is from six to 12. (A section of scholars
say should be minimum of six and maximum of 12).
d. Gather the respondents in one place (After gathering, tell
them the rules and regulations and allow them to select
the moderator themselves).
This qualitative method has a long history. Although,
they are most commonly associated with market research and
product testing, the method developed out of research
commissioned in the 1930s by the United State War Department
to investigate the loyalty and moral of American Soldiers,
leading up to World War II. Focus group discussion can be of
benefit to other research methods and endeavour. They are used
to gather preliminary information for research projects to help:
i. Develop items for survey research.
ii. Understand the reasons behind a particular phenomenon.
iii. See a group of people interpret a certain phenomenon,
and
iv. Test preliminary ideas or plans.
Procedures in Focus Group Discussion
Wimmer and Dominck (2000, p. 120) outline seven
basic steps in focus group research:
i. Define the Problem: at this first stage, you have to
define the problem you want your research to tackle.
For example, you could decide to look at product
outlet for Benue Television advertisers. In this
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situation, you could decide to conduct a focus group
interview with advertisers in Benue State.
ii. Select a Sample: here you must bring together a
subset of your target interviewees. Based on our
initial example, sample of your interviewees can be
drawn from among Lagos advertisers.
iii. Determine the Number of Groups Necessary: to help
eliminate part of the problem of selecting a
representative group, you should conduct two or
more focus group on the same topic.
iv. Prepare the Study Mechanics: this step involves
arranging for the recruitment of respondents,
reserving facilities at which the group discussions
will be conducted and deciding what type of
recording will be used (audio, video or both).
v. Prepare the Focus Group Materials: the materials to
be used for the focus group are prepared at this
stage. The questionnaire is developed to recruit the
desired respondents; recorders and other materials
are prepared and questionnaires are produced.
vi. Conduct the Session: here, the actual study is carried
out. Also at this stage, the moderator must be
selected and briefed about the purpose of the group.
The session may be conducted in a variety of
settings, from professional conference rooms to hotel
rooms rented for the occasion. In most cases, a
professional conference room is used.
vii. Analyse the Data and Prepare Report: this can be
done in two ways: (a) a brief synopsis of what was
said with an interpretation of the subject’s responses.
(b) The comments can be scanned and coded into
categories for detailed analysis and interpretation.
Like what obtains in other research methods, after
the report has been written, it has to be disseminated.
Application of Focus Group Discussion
Kurfi (2019) established the following applications thus:
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a. When there is a group interaction (note that, the group
should share certain characteristics).
b. When “how” and “why” questions are more important
than “what”, “where” and “when”.
c. When you want qualitative data than quantitative (Here,
one is not interested in quantification).
d. When working with a group that is not comfortable with
writing method.
e. When immediate feedback on questions are needed.
Characteristics of Focus Group Discussion
(a) It offers the opportunity of interacting with the group
(even though you are not participating).
(b) It provides opportunity for observation.
(c) It allows description of complex behaviour (i.e. action,
inaction, emotion, influence, etc).
(d) Provides comfortable environment for the respondents
to speak.
(e) It is bound with the issue of confidentiality (like
identifying them with given names, such as Participant
One, etc, while in the appendix, you identify them by
their surname).
Advantages of Focus Group Discussion
a. It provides wider range of information and responses.
b. It is a method that elicits information even from
uneducated people.
c. The discussion can challenge extreme or
unrepresentative views.
d. It allows researchers to collect preliminary information
about a topic.
e. It can be conducted quickly.
f. They are cost effective. In terms of money, focus groups
are cheap to conduct.
g. It is flexible in question design and follow-up.
h. Responses are often more complete and less inhibited
than those from individual interviews.
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Disadvantages of Focus Group Discussion
a. A self-appointed group leader may emerge and dominate
discussion.
b. A focus group is an inappropriate technique for
gathering quantitative data. In other words, focus groups
don’t answer the question “how many?” or “how
much?”
c. Focus groups samples are not representative.
d. Recording equipment and other materials on location
may inhibit respondents.
Instruments for Focus Group Discussion
a) Field notes.
b) Audio or video recording.
c) Transcription.
(7) Participant Observation (PO)
This is a method that is interested in describing and
explaining the measurement of quantification. It is a direct
observation method unlike Focus Group Discussion, which is
an indirect observation. It analyses actions, performances and
practices. Observation entails noting and recording the specific
engagements and interactions of a selected sample of a
population. Observation is an intentional or explicit
examination of a situation or a thing, in order to ascertain facts
about it. However, observation can also be unintentional or
inexplicit, known or unknown, direct or indirect, scheduled or
unscheduled. Researchers are usually interested in direct
scheduled observations. Communication researchers often
become active participants in the research setting. Observation
can fairly be referred to as the classic method of scientific
inquiry. The basic principle of an observational technique is
that, it is an attempt to summarise, systematize and simplify the
representation of an event rather than, provide an event of exact
representation of it. Much can be learned about human
communication behaviour by observing it. It concerns for
63
instance, the planned watching, recording and analysis of
observed behaviour, as it occurs in a natural setting (Asemah et
al., 2012).
Observation method is a standardised, planned and
systematic approach to objectively observe and record
behaviours. This of course, like other research methods, is to
generate all important data upon which to base many
conclusions. For example, a researcher may decide to
investigate the news processing behaviour of journalists by
observing them (journalists) right in the newsroom where they
operate. Observation as a research method has a long history in
psychology, anthropology and sociology. It was rarely used in
mass media research before 1980. It is important, however, to
state that scientific observation as a research technique is
different from everyday observation. The latter is random and
fugitive. That is, quickly moving on to other matters. The
former (scientific observation) focuses on what the observer
wants to find out and it is objective and systematic. The
techniques of making observation include:
a) Make a list of carefully defined and observable factors
that are relevant to the problem.
b) Group items related to a given factor into categories, and
c) Provide a space after each item where you will write
short descriptive statements or indicate the presence or
absence or frequency of occurrence of a phenomenon.
Methods in Conducting Observation
Basically, there are three ways of carrying out
observation; they are:
i. Simple observation.
ii. Systematic observation, and
iii. Mass observation.
(a) Simple Observation: most people rely on uncontrolled
observation for knowledge about social situations. It
consists of the simple forms of looking and listening,
which not only contribute to the basic and varied stock
of knowledge about social relations, but also affords the
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principal technique for gathering data in many modern
investigations. There are two ways to conduct simple
uncontrolled observation; namely: participant and non-
participant methods.
Participant Observation
The participant observation requires an outsider who
temporarily becomes an insider. He secures a better insight into
the situation he is investigating, as he is not personally involved
and can remain detached, while at the same time, taking part in
the group’s activities and sharing their feelings and prejudices.
He should have some preliminary knowledge of their attitudes,
habits and customs to obtain the best habits. He is not 100%
involved in the activities of the social institution, but takes part
in one way or the other to get information. The researcher seeks
deliberately to become a member of the social event or group
under study as a method of obtaining data. This usually
involves religious groups, social groups, community groups,
etc. The researcher integrates himself into a social institution,
understands their mindset and gets the people to participate in
the research process before finally getting his research done
(Asemah et al., 2012).
It is also called participatory research action (PRA) and
it has its roots from the participants’ observation method or
approach. It is usually useful when discussing groups not open.
For instance, when writing about masquerade, you cannot see
them; you have to behave like them. In practice the participant
observer may not or may reveal his research role; that is, his
purpose of being there. They will have implications. The
decision has methodical and ethical consideration. If he or she
admits to other participants that he or she is conducting a
research, his presence may affect the subject of study or
phenomenon of study. The presence of the researcher modifies
the research exercise. There is also an ethical question, “is it
appropriate to study people without their consent?”
The participant observation has three (3) main purposes;
namely:
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a. To answer questions in their natural setting and in
settings where the use of questionnaires and direct
reports will be impracticable or inappropriate. For
example, when conducting research exercise that has to
do with children, it will be appropriate to observe them
instead of using questionnaire.
b. It is also used when a researcher is dealing with a setting
that is new; that hypotheses are not yet developed. That
is, the setting has been so unexplored that formal
hypotheses may not have been developed. Thus, as the
researcher involves himself in the activities of the group
through participation, he will be able to acquire an
insight that cannot be gained through other approaches.
c. To develop grounded theories. A grounded theory,
according to Reinhard (n.d) is a set of explanations that
has immediate relevance to a specific field setting under
investigation. The participant observes through his
method, attempts to discover categories to describe his
observations. There is an alternative approach called
analytic induction which entails a researcher staring with
some tentative hypotheses that they apply in field work.
If the hypothesis is inadequate, it may be abandoned or
reformulated.
Requirements for Participant Observation
a) It serves a formulated research purpose (you need to
have a justification for using the method).
b) It relates to the existing literature or theory (one is trying
to validate literature or theory assumption).
c) It is systematically planned (you have to go into it with
the four quadrants in mind).
d) It is record systematically (for example, having a biro
that may have a camera).
e) It is refined into general hypothesis.
f) It is subject to check and control of some form of
reliability and validity.
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Approaches or Instruments use in Participant Observation
The instruments of participant observation are being
carried out in quadrant and they can either be overt or covert.
See the diagram below:
Overt Observation (Quadrant 1): in this situation, the
researcher is identified when the study begins and those under
observation are aware that they are being studied. Apparently,
the researcher’s role is only to observe, refraining from
participation in the process under observation.
Overt Participation (Quadrant 2): in this arrangement, those
being observed also know the researcher. The researcher goes
beyond the observer role and becomes a participant in the
situation. The researcher participates in all the entire process
and the respondents are aware that they are been studied or
observed.
Covert Observation (Quadrant 3): is the situation where the
researcher’s role is limited to that of observer but those under
observation are not aware that they are being studied. Here, the
Overt Observation
Overt Participation
Covert Observation
Quadrant 3
Quadrant 2
Quadrant 1
Covert Participation
Quadrant 4
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role of the researcher is limited to observation and the
respondents of the study are not aware that they are being
observed.
Covert Participation (Quadrant 4): it represents a study in
which the researcher participates in the process under
investigation but is not identified as a researcher. Here, the
researcher participates in what the respondents are doing but
they are not aware that they are being studied or observed.
Non Participant Observation
Non participant observation consists of examination of
specific social situations, but not taking part in them. This
entails looking at a social situation without being part of it,
thereby making a secrete observation of what they might be
doing without letting them know. It is sometimes called the
loafing method. This method can reveal what people do and
most possibly, why they do them. The presence of the non
participant observers should be made as inconspicuous, as
possible. The investigator just loafs around, follows the crowd
and observes carefully its behaviour. As the day or evening
wears on, the observer finds himself at places where people
gather. This method sometimes gives a better insight than all the
formal methods combined on how people live and why they act
as they do. Non participant observation helps to eliminate
fallacies in the question-answer approach. The question answer
approach seldom produces reliable information about the
influence of local leaders. Sobowale (1983) summaries the non-
participant observational method thus:
In nonparticipant observation, the researcher detaches himself
from the event he is watching. He makes his observation from
a distance. He is not involved or engaged in the activity as his
participant counterpart; the researcher observes a situation
from a detached position, which does not intrude or take over
any of the roles of the people interacting in that situation. For
instance, a researcher who wishes to study the behaviour of a
traffic policeman at a road block does not have to join the
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police force to do that. He may stand at a convenient distance
from the check point and watch the interactions of the
policeman with motorists and other road users. He is far less
inhabited to jot down his observations (p. 15).
Nonparticipant observation has the following advantages:
(a) There is no risk of observer effect. That is, the
researcher does not internalise the values of the group he
is observing.
(b) May result in detailed recording of information.
(c) Can provide the basis for theories and hypotheses
development, and
(d) Less risky than participant observation.
Its disadvantages are:
a. Since the observer is detached from the situation, he
relies on his perception, which may be inaccurate.
b. If the research subjects know that they are being
observed, the results obtained will be artificial, as they
will not reflect their actual behavioural pattern.
c. Problem of bias. The observer is bound to watch out the
details he records.
d. It is more prone to errors than participant observation.
(b) Systematic Observation: systematic observation is
controlled. It differs from simple observation in the sense that,
its observational techniques are standardised and both the
observer and the observed are under control. It entails
controlling the person doing the observation and the person
being observed. It is not everyone’s opinion you need in this
case. Simple observation is not useful in exploratory studies,
but has to be supplemented with schedules, questionnaires and
tests. The advantage it has is that, biases can be accurate. Also,
some people’s senses are not too sharp and the person collecting
the information should be built into the research. There has to
be objectivity. This is sometimes used for social research. It is
also used to verify existing hypothesis. It also helps to bring out
the meanings of social facts or situations and predictions. When
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this kind of research is used, it can be accurate. It must consist
of the following:
a) Limited area the individual must observe.
b) The information to be recorded.
c) Select the data you want to observe.
d) Standardise your observation (by time, place, person,
etc).
e) Particular people to be observed, and
f) The use of mechanical means to achieve accuracy.
(c) Mass Observation
It is the combination of the two (simple and systematic),
while the information is controlled. The number of people being
observed is not controlled. Here, you record only the
information needed. Even if you interview a large number, you
only put down the important information.
Steps in Observation Research
The procedure for observational research as identified
by (Wimmer and Dominick, 2000, p. 114) are:
(a) Choosing the research site: the nature of the research or
study usually suggests a behaviour or phenomenon of
interest. Once it is identified, the next step is to select a
setting, where the behaviour or phenomenon occurs with
sufficient frequency to make observation worthwhile.
The site must be stable and permanent to permit
observations over a period of time. For example, if you
are interested in studying journalists’ information
processing behaviour, the best site is a newspaper, radio
or television newsroom.
(b) Gaining Access: once you have selected the site, the
next step is to establish contact. In other words, you
have to gain access to the site. The easiest setting to
enter is the one that is open to the public and gives
people little reason to keep behaviour secret. For
example, a place in which people are watching
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television in public like airport, a bar, a hall, viewing
room, etc.
(c) Sampling: on gaining access to the site, you have to
determine a subset of the site’s subjects you are
interested in. If the topic is family viewing of television,
how many families should be included or samples for
the study? After answering this question, you now
sample behaviour episodes or segments. It is noteworthy
that you cannot be everywhere and see everything, so
what you have observed becomes de facto sample of
what you have not observed. For instance, if you view a
meeting in the newsroom, this meeting represents other
unobserved meetings. Most field observations use
purposive sampling, where observers draw on their
knowledge of subjects under study and sample only
from the relevant behaviours and events.
(d) Collecting Data: at this stage, the data for study are
collected. Data collection tools in observation research
include: (i) note book and pencil (ii) video recorder and
(iii) audio recorder. Even though, the advantages offered
by audio and video recording are tempting, there are five
draw backs on their use:
i. Recording devices take time away from research
process, because they need regular calibration and
adjustment to work properly.
ii. The frame of the recording is different from the
frame of the observer.
iii. Recording has to be cataloged, indexed and
transcribed, adding extra work to the project.
iv. Recording takes behaviour out of context.
v. Recording tends to fragment behaviours and distract
attention from the overall process.
(e) Analysing the Data: the overall goal of data analysis in
field observation is to arrive at general understanding of
the phenomenon under study. Here, data analysis
consists of primarily filing the information and
analysing its content. Constructing the filing system is
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an important step in observation. The purpose of the
filing system is to arrange raw field data in an orderly
format that is amenable to systematic retrieval later.
(f) Exiting: as a researcher, you must have a plan for
leaving the setting on the group under study. In some
instances, the group may have become dependent on you
in some way and the departure may have a negative
effect on the group as a whole. You have an ethical
obligation therefore, to do everything possible to prevent
psychological, emotional or physical injury to those
being studied.
(8) Case Study Method (CSM)
A case study method connotes a comprehensive
description and explanation of many components of a given
situation. The researcher seeks to examine and collect as many
data as possible, regarding the subject of study. Whereas most
studies are interested in generalised understanding, the case
study is initially directed at the comprehensive understanding of
a single idiosyncratic case. The researcher does not seek to limit
the number of variables to be considered, rather the case study
seeks to maximise the variables. Typically, case study seeks an
insight into the applicability of the validity beyond the single
case and the disadvantage is that the single case may not
guarantee this.
Case study, according to Wimmer and Dominick (2000,
p. 134) “is a research technique that uses as many data sources
as possible, to systematically investigate individuals, group,
organisations or events. Case studies are conducted when a
researcher needs to understand or explain a phenomenon.
Unlike a survey that examines one or a few characteristics of
many subjects or units, a case study is used to examine many
characteristic of a single subject (a communicator, newsroom,
newspaper, television station, etc). The case study usually tries
to learn all about the area. The investigator is interested in the
specific case, over a period of time.
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The major pitfall of case studies is that they usually,
cannot be generalised to other similar situations. Most often, the
results are based on a single example. Case studies are
conducted when a researcher needs to understand or explain a
phenomenon. It should be noted that case studies do not need to
have a number of cases or to randomly select cases. This
method employs the multi-perspective analysis as it considers
not just the voice and perspective of the actors, but also, of
relevant groups of actors and interaction between them. It gives
a voice to the powerless and voiceless. In a way, this definition
highlights how a case study differs from other research
methods.
Asemah et al., (2012) observed that case study typically
seeks insight that will have a more generalised applicability
beyond the sample case under study. However, a case study
itself cannot assure or guarantee this. For instance, a case study
of Black Axe cult to represent other cults on the campus, it can
be examines it in details such as:
a. Their activities.
b. Symbols.
c. Aims.
d. Structure.
e. Language.
f. Initiation method.
g. Modus operandi.
h. Admission requirement.
i. Place of meeting, and
j. Rules and regulations.
Types of Case Study
Osuala (2005, p. 187) established the types of case study
as follows:
(a) Historical Case Study: they are studies that trace the
development of an organisation or social system
overtime.
(b) Observational Case Study: these studies often focus on
a classroom, group, teachers and pupils, often using a
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variety of observation and interview method as their
major tools.
(c) Oral History: these are normally first person narratives
that the researcher collects, using extensive
interviewing of a single individual. For instance, retired
staff recounting how they were taught in the early part
of the century.
(d) Situation Analysis: particular events are studied in this
form of case study. For instance, an act of student
vandalism could be studied by interviewing the people
concerned, the parents, the teacher, the chairman or
witnesses.
(e) Clinical Case Study: this method aims to understand in-
depth, a particular individual, such as a child having
problem with reading, a newly transferred student in his
first term at school or a teacher with disciplinary
difficulties.
(f) Multi-Case Studies: a collection of case studies, that is,
the multi-case study, is based on the sampling logic of
multiple subjects in one experiment.
The Purpose of Case Study
Asemah et al., in Osuala (2005) highlights the purpose
of case study as follows:
a. It is valuable as preliminaries to major investigations.
Because they are so intensive and generate rich
subjective data, they may bring to light variable,
phenomena, processes and relationships that deserve
more intensive investigation. In this way, a case study
may be a source of hypothesis for future research. As a
pilot study, methods, approaches or policies are tried out
to see what the difficulties are, that need to be dealt with
before the main study is undertaken.
b. A case study fits many purposes, but most case studies
are based on the premise that a case can be located that
is typical of many other cases. Once such a case is
studied, it can provide insights into the class of events
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from which the case has been drawn. Of course, there is
no way of knowing how typical the selected case really
is and it is therefore, rather hazardous to draw any
general conclusion.
c. A case study may refute a universal generalisation. A
single case can represent a significant contribution to
theory building and assist in refocusing the direction of
future investigations in the area.
d. A case study is preferred when the relevant behaviour
cannot be manipulated.
e. A case study may be valuable in its own right as a
unique case.
Case Study Design
In case study, there are four (4) main components to the
research design thus:
1. Initiate Case Study Questions: these are who, what,
where, when and how and must be clarified and stated
succinctly before moving on. Without at least, one initial
question to which you wish to find answer, no start can
be made.
2. Study Propositions: there is a need to specify some
succinct propositions that will enable the questions to be
answered.
3. Unit of Analysis: this component is concerned with
defining what the ‘case’ really is. Without this the
investigator will have no bounded system and will be
tempted to collect everything that randomly may have a
bearing on the issue.
4. Linking Data: this is the means of linking data to
proposition, using it as a criterion for interpreting
findings.
Conducting a Case Study
Asemah et al., (2012) remark that case study research
procedure bears some semblance of the traditional methods of
survey and experiment but differs greatly in many respects.
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There are five distinct stages in carrying out a case study. These
are:
a. Design: the first concern in case study design is what to
ask. The case study is most appropriate for questions
that begin with “how” and “why”. A research question
that is clear and precise focuses the reminder on the
efforts on a case study. A second design concern is what
to analyse. What constitutes a case? In many instances, a
case is an individual, server individuals or an event or
events.
b. Pilot Study: a pilot study is used to refine both research
design and field procedures. Variables that were not
foreseen during the design phase can crop up during the
pilot study. The pilot study is to also observe different
activities from several trail perspectives. It is noteworthy
that before the pilot study is conducted, the case study
researcher must construct a study protocol. This
document describes the procedures to be used in the
study and also includes the data gathering instrument or
instruments. The results of the pilot study are used to
revise and polish the study protocol.
c. Data Collection: there are six sources of data in case
studies; namely: first, documents, which could be letters,
memoranda, agenda, administrative documents,
newspaper articles or any document that is germane to
the investigation. Second, archival records, which can be
service records, organisational records, lists of names,
survey data and other records. Third, interviews are also
important source of case study information. These could
take the form of open ended, focused and structured
survey. Fourth, direct observation occurs when a field
visit is conducted during the case study. Fifth,
participant observation makes the researchers become
active participant in the events being studied. Sixth,
physical artifacts can be tools, instruments or some other
physical evidence that may be collected during the study
as part of a field visit. Note that not all sources are
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relevant for all case studies. In spite of this fact, you
should be able to deal with all of the multiple uses of
data sources as recommended for two reasons. The first
reason is that it permits triangulation of the phenomenon
under study. The second is that it improves the
reliability of the study.
d. Data Analysis: there are no specific formulas for
analysing case study data. This is one of the aspects that
differentiates case study from more quantitative research
techniques like survey. Yin (1994) suggests three broad
analytic strategies: pattern matching strategy, an
explanation building and time series. In the pattern
matching, empirically base pattern is compared with one
or more predicted patterns. For instance, assuming a
Nigerian businessman wants to set up a newspaper for
rural audience, based on the gate keeping concept a
researcher might predict the structural makeup of the
newspaper management. If analysis of the case study
data indicates similar makeup, as predicted by the
researcher, then the case study interpretation is reliable,
otherwise the initial study propositions have to be
questioned.
In the analytic strategy of explanation building, the
researcher tries to construct an explanation about the
case, by making statements about the causes of the
phenomenon under study. In time series analysis, the
investigator tries to compare a series of data points to
some theoretical trends that were predicted before the
research or to some alternative trends. If, for example,
several Nigerian cities have experienced newspaper
strikes, a case study investigator might generate
predictions about the changes in information-seeking
behaviour of residents in these cities and conduct a case
study to seek whether these predictions are supported.
e. Report Writing: the case study report can take several
forms. The report can follow the traditional research
study format problem methods, findings and discussion
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or it can use a nontraditional technique. No matter what
form is chosen, the researcher must consider the
intended audience of the report.
Advantages of Case Studies
1. Case studies provide tremendous details.
2. The case study technique can suggest why something
has occurred.
3. The case study method affords the researcher the ability
to deal with a wide spectrum of evidence.
Disadvantages of Case Studies
1. There is general lack of scientific rigour in case studies.
2. Case study is not amenable to generalisation.
3. Case studies are time-consuming and may occasionally
produce massive quantities of data that are hard to
summaries.
Chapter Summary
The Chapter presents the qualitative research approach,
which is a scientific practice that is used to generate knowledge
about human experience or action, including social processes.
This type of social science research collects and works with
non-numerical data that seeks to interpret meaning from these
data that help people to understand social life through the study
of targeted populations or places. It investigates local
knowledge and understanding of a given programme, people’s
experiences, meanings and relationships and social processes
and contextual factors that marginalize a group of people. In
discussing the qualitative approach, Critical Discourse Analysis
(CDA), Semiotic Analysis (SA), Qualitative Content Analysis
(QCA), Text and Textual Analysis (TTA), In-depth Interview
(IDI), Focus Group Discussion (FGD), Participant Observation
(PO), Case Study Method (CSM) was extensively examined.
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Chapter Three
Quantitative Approach to Social Science Inquiry
Introduction
In quantitative studies, authors report original, empirical,
quantitative research. Quantitative research refers to a set of
approaches commonly used in the behavioural and social
sciences and related fields, which the observed outcomes are
numerically represented. The results of these studies are
typically analyzed using methods (statistics, data analyses and
modeling techniques) that rely on the numerical properties of
the measurement system. Quantitative research studies use a
variety of experimental designs and a range of analytic
techniques. Some quantitative studies present novel hypotheses
and data analyses not considered or addressed in the previous
reports of related data (American Psychological Association,
2020).
The results of these studies are typically analyzed using
methods (statistics, data analyses and modeling techniques) that
rely on the numerical properties of the measurement system.
Quantitative research studies use a variety of experimental
designs and a range of analytic techniques. Within the research,
authors should describe elements of their study in the first
person (American Psychological Association, 2020).
Quantitative research is an approach for testing objective
theories by examining the relationship among variables. These
variables, in turn, can be measured, typically on instruments, so
that numbered data can be analyzed using statistical procedures.
The final written report has a set structure consisting of
introduction, literature and theory, methods, results and
discussion. Like qualitative researchers, those who engage in
this form of inquiry have assumptions about testing theories
deductively, building in protections against bias, controlling for
alternative or counterfactual explanations and being able to
generalize and replicate the findings (Creswell and Creswell,
2018).
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Quantitative approach, according to Nwodu (2006) is
when a study takes account of numerical values or the
frequencies with which the various delineated items of the
content analysis occurred. While qualitative content analysis is
the process that explain (putting into words), the results
obtained from the quantitative research. In social science, the
methods that are frequently employed to obtained data under
quantitative method are:
a. Survey method.
b. Content Analysis.
c. Experimental Research Method.
(A) Survey Method
Scholars like Msughter (2018) and Maikaba (2019)
established that in most areas of Mass Communication, survey
is popularly used. Survey is a study that has to do with the
opinion of people. It is often done in the area where there is a
large population. In conducting a survey, it is apparent to have a
sampling frame. A sampling frame is a comprehensive list that
represents the entire population. In conducting survey also,
there is need for probability method in terms of sampling
because there must be randomization.
Historically, Karl Marx was the first user of the survey
method of research in 1880. He mailed 25, 000 questionnaires
to Protestants in trying to investigate their ethical inclination.
Unfortunately none of the questionnaires was returned. Some
scholars however, argued that survey is linked to the earliest
population census conducted in the early time (Maikaba, 2019).
Survey can be described as a descriptive form of
research; it is also ex-post-facto (looking at what already exist).
Ex-post-facto research is a research that is undertaken after the
event has taken place and the data is already in existence. It is
therefore, a systematic empirical study in which the researcher
does not in any way control or manipulates independent
variables because the situation for study already exists or has
already taken place.
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Survey implies a systematic process of examining
phenomenon in its entirety. A survey is an empirical study that
uses questionnaires or interviews to discover descriptive
characteristics of a phenomenon. Survey is used in
communication studies, where large groups of people are asked
about their views, opinion, perspectives and perception about
subject matter. It is aimed at developing generalized
propositions about human behaviours from what is observed in
a sampled population.
McCombs and George, in Stempel and Wesley (1981, p.
144) wrote that the use of survey method is very imperative in
observing the social and behavioural characteristics, attitudes,
values and beliefs of large population. This coincides with
Asemah et al., (2012) who observe that survey is the most
popular technique of data collection among communication
researchers and that it is an effective method of measuring or
collecting large data about people, their thoughts, preferences,
beliefs, attitudes or factual information.
Ogbuoshi (2006) states that in survey research, if the
population is small, there will be no need for sampling and the
researcher will therefore study the entire population. However,
if the population is too large, the researcher can therefore draw
a sample from the population under study. This means that
survey studies both small and large population.
The survey research method is perhaps the most popular
technique of data collection in social science research. Surveys
are now commonplace in all areas of life. Decision makers in
businesses, consumer and activist groups and the media, use
survey result as part of their daily routine. The survey research
technique is thus, a method of collecting and analysing social
data via highly structured and often very detailed interview or
questionnaire in order to obtain information from large number
of respondents, presumed to be representative of a specific
population.
The two things that can help in survey research are:
a. Levels of measurement, and
b. The concept of questionnaire.
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Berger (2000, p. 147) further adds that surveys are used to
determine the following:
i. What people know;
ii. What people think;
iii. What people own;
iv. What people do;
v. What people’s attitudes are;
vi. People’s beliefs; and
vii. What people value.
Survey can be located from three (3) different levels:
1. Base on purpose;
2. Form of administration; and
3. Time span.
1) The Purpose:
Purpose denotes an intended and carefully planned goal
or what the researcher hope to accomplish with the study. Based
on this, survey is classified into (3) type: (i) descriptive (ii)
explanatory and (iii) exploratory.
i. The descriptive survey: this is an attempt to describe and
document what exists in the population under study
interms of features and characteristics. The researcher
tries to record what is obtainable at the moment.
Wimmer and Dominick (2011) explained that the
descriptive survey research attempts to describe or
document current conditions or attitudes. This survey
seeks to obtain information about demographic factors,
such as: age, gender, marital status, occupation,
ethnicity, income, religion, etc and to relate this
information to opinions, beliefs, values and behaviours
of some groups of people or research population.
Broadcasters for instance, use survey research to find
out how popular their programmes are. The focus of
descriptive surveys is on present day behaviour of
people. Broadcast stations and print media constantly
survey their audiences to determine the programming
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tastes, changing values and lifestyle variations that
might affect programming. Public relations and
advertising people survey the audience to know how
they respond to their goods and services (Gunter, 2000).
The researcher is primarily concerned with what
distribution exists and not why, such distribution occurs.
E.g. we may need to describe the voting behaviour of
Bayero University students.
ii. Explanatory or analytical Survey: this type of survey is
also known as analytical survey. It seeks to find out why
people behave the way they do. Researchers often use
data from descriptive surveys to develop hypotheses and
use analytical surveys to test their hypotheses about
what causes certain kinds of behaviours. Analytical
survey attempts to determine whether there are causal
relationship between certain kinds of behaviour and
various social and demographic characteristics of
people.
The focus of analytical survey is to describe and explain
why certain situations exist. In this approach, two or
more variables are examined to test research questions
or hypotheses. The result allows a researcher to examine
the interrelationships among variables and to draw
explanatory inferences. For instance, one may be
interested to ascertain why voters prefer one candidate
over another.
iii. Exploratory Survey: this breaks new ground particularly
when looking into a particular topic. Exploratory studies
raise new possibilities which can be followed. A good
example is when a researcher intends to dis-virgin or
deflowers a particular area of interest, which has not
been researched before or over time.
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The Characteristics of Survey
1. Parsimonious: it means it is economical, we use sample
to serve as representation of the population and it also
uses a representative sample.
2. It collects a broad range of data: this means that it has
the ability of testing many more variables.
3. The unit of analysis is usually an individual person: this
also depends on the nature of the problem; sometimes
we interview family members together.
4. Survey research involves a selection of an unbiased
sample (random sampling).
5. Survey can be used to investigate a vast array of topics
in politics, consumers, behaviours, media users, social
behaviour, etc.
2) Forms of Administering Survey
Survey administration entails the pattern of engagement
or interaction between the researcher and the target population
or sample in the selective process of data generation. Survey
can be administered into the following ways:
i. Telephone Survey: this is a kind of survey that employ
trained members of a research team to ask questions
verbally and record the responses through the use of a
telephone line. Telephone survey seems to fill a middle
ground between mail survey and personal interviews.
They offer more control and higher response rates than
most mail surveys but are limited in the types of
questions that can be used. They are generally more
expensive than mail survey but less expensive than face-
to-face interviews. Because of these factors, telephone
survey seems to represent a compromise between the
other two techniques and this may account for their
growing popularity in mass media research.
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Advantages of Telephone Survey
1. The cost tends to be reasonable.
2. It contains more detailed questions and there is
clarification.
3. Non response is minimal or low.
4. Faster than mail survey
5. Very easy to be conducted
Disadvantages of Telephone Survey
1. In some cases, telephone is not research at all but an
attempt to sell people something. Unfortunately, many
companies disguise their sales pitch as a “survey” and
this has made respondents suspicious and even prompt
to terminate an interview before it is started.
2. Visual questions are prohibited. A researcher cannot, for
instance hold up picture of a product and ask if the
respondents remember seeing it advertized.
3. Sometime, sampling frame may not consist of all the
population under study. Not everyone has phone
numbers; also some members are listed incorrectly and
others are too new to be listed.
4. It is highly personal.
5. The researcher may not be able to ascertain that the
respondent is competent enough to answer the questions.
ii. Postal or Mail Survey: this involves mailing or posting
self-administrable questionnaire to a sample of
individuals through the postal service of a country.
Stamped reply envelopes are enclosed to encourage
respondents to mail completed questionnaire back to the
researcher. Mail surveys are popular because they can
secure a great deal of data with a minimum expenditure
of time and money. According to Asika (2009) mail
questionnaire is self administered from the stand point
of respondent. It is often called interviewing by mail
because it contains carefully worded questions and
instructions for the respondent who may not have the
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opportunity of seeing and asking in clarification from
the researcher.
Stages of a Mail Survey
i. Select a sample.
ii. Construct the questionnaire.
iii. Write a cover letter.
iv. Assemble the package.
v. Mail the survey.
vi. Closely monitor the return rate.
vii. Send follow-up mailings.
viii. Tabulate and analyse data.
Advantages of Postal or Mail Survey
1. It covers a wide geographical area with a reasonable
cost.
2. It also allow for selective sampling through the use of
specialised mailing lists.
3. It provides anonymity, so that subjects are likely to
answer sensitive questions candidly.
4. It eliminates interviewer bias since there is no personal
contact.
5. Low cost.
Disadvantages of Postal or Mail Survey
1. No place for clarification on questions. Therefore, mail
questionnaires must be self-explanatory.
2. It is the slowest means of data collection.
3. Researchers never know exactly who answered the
questions.
4. Low return. This low return casts doubt on the validity
of the findings.
5. It is impersonal.
How to Improve Return Rate
1. Keep questions to a minimum.
2. Use follow-ups.
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3. Use inducements. A small sum of money is the most
common form of inducement used in survey research.
4. Include a cover letter.
5. Using stamped envelopes rather than business reply
envelopes.
6. Asking for objective rather than subjective information.
7. Addressing cover letter by name rather than by “Dear
Sir”.
iii. Personal Survey: this method involves a person seeking
the information called the interviewer and another
giving the information called the respondent. The
interviewer armed with an interview schedule meet the
respondents, asks questions to the respondents and
completes the interview schedule himself. In effect,
personal survey uses questionnaire which is completed
by the interviewer himself. Unlike in mail questionnaire,
the interviewer often goes beyond what is contained in
the interview schedule to ask questions for clarification
in order to enrich response. The topics and pattern of
discussions are decided by the interviewer. There are
two basic types of interviews (a) structural and (b)
unstructured
Procedures in Constructing Personal Survey
1. Select sample.
2. Construct questionnaire.
3. Prepare an interview instruction manual.
4. Train the interviewer.
5. Collect the data.
6. Make necessary call back.
7. Verify result.
8. Tabulate the data.
Advantages of Personal Survey
1. It is the most flexible means of obtaining information.
2. Easier for clarification.
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3. The identity of the respondents is known or can be
controlled.
4. Minimising lost or questionnaire.
5. Quick turn over of questionnaires.
Disadvantages of Personal Survey
1. Too cost to operate.
2. Difficult to conduct.
3. The interviewer may insert his or her personal opinion.
4. Lack of cooperation and trust from the respondents can
reduce response rate.
iv. Group Administration: this is a survey method that is
conducted when a group of respondents are gathered
together and given individual copies or a questionnaire
for self administration or asked to participate in a group
interview. In the group interview technique, the
interviewer read the questions aloud and each
respondent records responses on an answer that was
supplied. This technique can be participatory, helpful
with respondents who have only minimal reading skills.
In administered situation, the questionnaires are simply
passed out and the respondents proceed at their own
pace, much as in a mail survey. The respondents, of
course have the opportunity to ask questions of the
research personnel in the room.
Advantages of Group Administration
1. The response rates are quite high.
2. Less costly than face-to-face or telephone interview.
3. Interviewer can clarify some complex questions.
4. Quick turn-over of information.
Disadvantages of Group Administration
1. It might be very difficult to control.
2. Mixing respondents together may bias the result.
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3. It might provide suspicion and biasness on the part of
respondents if it leads to perception that the study is
sectioned by some authorities.
v. Internet Survey: the number of surveys being conducted
over the internet has increased dramatically over the
years, driven by a dramatic rise in internet penetration
and the relatively low cost of conducting web surveys in
comparison with other methods. Web surveys have a
number of advantages over other modes of interview.
They are convenient for respondents to take on their
own time and at their own pace. The lack of an
interviewer means web surveys suffer from less social
desirability bias than interviewer-administered modes.
And Web surveys also allow researchers to use a host of
multimedia elements, such as having respondents view
videos or listen to audio clips, which are not available to
other survey modes.
Although more surveys are being conducted via
the Web, internet surveys are not without their
drawbacks. Surveys of the general population that rely
only on the internet can be subject to significant biases
resulting from under coverage and nonresponsive. Not
everyone has access to the internet and there are
significant demographic differences between those who
do have access and those who do not. People with lower
incomes, less education, living in rural areas or age 65
and older are underrepresented among internet users and
those with high-speed internet access (Pew Research
Center, 2016).
There is no systematic way to collect a
traditional probability sample of the general population
using the internet. There is no national list of email
addresses from which people could be sampled and
there is no standard convention for email addresses, as
there is for phone numbers that would allow random
sampling. Internet surveys of the general public must
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thus first contact people by another method, such as
through the mail or by phone and ask them to complete
the survey online.
Because of these limitations, researchers use two
main strategies for surveying the general population
using the internet. One strategy is to randomly sample
and contact people using another mode (mail, telephone
or face-to-face) and ask them to complete a survey on
the web. Some of the surveys may allow respondents to
complete the survey by a variety of modes and therefore
potentially avoid the under coverage problem created by
the fact that not everyone has access to the web. This
method is used for one-time surveys and for creating
survey panels where all or a portion of the panelists take
surveys via the web (Pew Research Center, 2016).
Another internet survey strategy relies on
convenience samples of internet users. Researchers use
one-time surveys that invite participation from whoever
sees the survey invitation online or rely on panels of
respondents who opt-in or volunteer to participate in the
panel. These surveys are subject to the same limitations
facing other surveys using non-probability-based
samples: the relationship between the sample and the
population is unknown so there is no theoretical basis
for computing or reporting a margin of sampling error
and thus for estimating how representative the sample is
of the population as a whole (American Association for
Public Opinion Research, 2015).
3) Time Span
The major distinguishing characteristic of survey is
whether they are conducted at one point in time or are repeated
over time or more occasions. Here, there are two variance of
survey. They include: Cross-sectional and Longitudinal study.
1- Cross-sectional Survey: this is where data are collected
at one point in time from a sampled population. This
type of design can be use for the purpose of description
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and also for the timing relationship between variables
and the time of the study.
2- Longitudinal Study: is where data are collected at
different point in time and changes into description and
explanatory reported. There are three types of
longitudinal study: trend study, cohort analysis and
panel studies.
Trend Studies: this is where the general population may
be sampled and studied at different point in time. Trend studies
are base on description of the general population. A good
example is Nigeria general election.
In trend studies, researchers can either generate their
own data or use data from secondary sources that may have
originally constructed for other purposes. In trend studies also,
different persons are studied in each survey but each sample
represent the same population. Trend often involves a rather
long period of data collection.
Cohort Analysis: this implies generation and analysis of
data from people who share certain life experiences. For
example, all students who attended Bayero University, Kano for
a first degree in 2018 or children who are born in the same year.
Cohort analysis is a flexible technique that can indicate whether
changes in attitudes or behaviours are affected by maturation or
other social and cultural factors.
Panel Studies: this involves the collection of data over
time from the same sample of respondents. Panel studies can
make use of postal questionnaires, telephone interviews or
personal interviews.
Survey Instruments
Instruments are the facilities used in collecting data. In
survey, we have two instruments. They are: (i) questionnaire
and (ii) interview.
Questionnaire simply means a set of questions written
and printed on a paper in order to be administered to the target
respondents. It can be entirely open ended or close ended format
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or the mixture of two. However, this depends on the study.
Questionnaires are used when you have a large population.
Guideline for Administering Questionnaires
1. We need to design questions that will provide answers
to what is real.
2. We need to consider the method or analysis to adopt.
3. Make your items in the questionnaire clear.
4. Use language that is very clear. That is, good command
of language.
5. Avoid a bias question. E.g. Do you agree that
Southerners are selfish?
6. Avoid ambiguous questions. That is, questions that
provides more than one answers. E.g. BBC Network has
a funny or sexual explicit. Do you agree or disagree?
7. Organise items in such a way that the respondents will
not feel laboured.
8. Avoid polar questions, unless it is absolutely necessary.
Yes or No questions do not help us to measure. When
you use yes or no questions, used follow-up questions.
9. Do not ask questions that demand highly detailed
information. E.g. In the past 40 days, how many hours
of television you have viewed with your family? This
question is unrealistic. In more realistic, how many
hours you spend in watching TV with your family
yesterday?
10. Avoid potentially embarrassing questions. E.g. Do you
belong to a terrorist group?
11. For your demographic data, make sure you give a range.
This is because no respondent may like to give you the
exact age. Also, ensure that information on demographic
data should be the last item on the questionnaire because
some people are not always comfortable with this aspect
of the questionnaire.
How to Design or Construct a Questionnaire?
a) Introduction.
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b) Instruction.
c) Question order.
d) Layout.
e) Question length.
Introduction: one way to increase the response in survey
is to prepare a persuasive introduction. Two researchers
Backstrom and Hursh-Cesa (1986) suggested six characteristics
viz:
1. The introduction should be short.
2. Realistically worded.
3. Non-threatening.
4. Serious.
5. Neutral.
6. Pleasant but firm.
Instrument: all the questionnaires must be clearly stated
to respondents. The questions vary depending on the type and
nature of the study. Mail and self administered questions
usually demand more specific instructions. Procedurally,
instructions are usually highlighted with specific.
Question order: survey flows better when the questions
are simple and easy to answer.
Layout: the physical design is another factor in survey
research. A badly typed and poorly reproduce questionnaire is
not likely to attract many responses.
Questionnaire length: the length of a questionnaire is
directly related to the completion rate, wrong questionnaire
cause fatigue and mortality rate. Shorter ones guarantee higher
completion rate. Unfortunately, there are no strict guidelines to
help in deciding how long a question should be. The length
depends on a variety of factors.
Problem with Questionnaires
1. Respondents sometimes keep what George Bishop
called “top-of-the head reaction question”. This simply
means the respondents are not thinking deeply. We can
overcome this by having lie detectors. Questions can ask
in three different ways.
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2. There is a problem of Hawthorne Effects (people give
you what you want because they are been observed).
3. Variation in meanings among respondents. This means
that respondents give different meaning to different
question. You can overcome this by using the pre-
testing. So, pre-testing is very vital in survey.
4. Unwillingness of the respondents. Some time, the
respondents may not like to take part in the study.
5. Human problem: this has to do with human angle.
Where people fail to response because they want
something from the interviewer.
On the other hand, interviews are used when you have a
small or scanty population. It involves asking people questions
about a particular issue under investigation. Interviews are very
essential because they help the researcher to obtain firsthand
information about a particular issue.
Types of Interview
There are two types of interviews, namely:
1. Structured and
2. Unstructured interview.
Structured Interview: this is an interview in which
standardised questions are asked in a predetermined order.
Here, you have a fixed number of questions. It is often
conducted when the interview has limited time to offer. It is
easier to cope and analysed issues in this type of interview.
Unstructured Interview: this allows for flexibility in
manner, order and language, which the interviewer asked the
questions. It is informal in terms of manner and language. This
interview is adopted when the interviewee has enough time to
offer. In this type of interview, you need to establish a rapport
with the respondents. Remember that we can only conduct
interview when we have a small number of people.
(B) Content Analysis
According to Maikaba (2019) Unobstrusive is an
attempt to create distinction between the several designs in
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communication and general social science research. It is
examined from this premise that “almost all social science
investigation involves the action participation of the study
agent”. The experimental method is impossible without the
active participation of the study agent. Thus, Unobstrusive
studies are the one that is not realistically included on by the
researcher. They involve the study of raw communication
matter. Principles among is the content analytical measure. It
also includes the existing statistics as well as historical analysis.
Content analysis, according McQuail cited in Msughter
(2018) it is a technique for systematic qualitative and objective
description of the media texts. It is useful for the purposes of
classifying output, looking for effects and making comparisons
between media content and ‘reality’. This method helps
researchers to arrive at some conclusion regarding the attitude
of writers and the written messages. Content analysis is an
analysis based on the manifest or latent content of information
or text rather than observing people’s behaviour directly or
asking them to respond to scales or interview. Content analysis
is a research technique for the objective, systematic and
qualitative description of the manifest and latent content of
communication. Wright (1986, p. 125), describes “content
analysis as a research technique for the systematic classification
and description of communication content according to certain,
usually predetermined categories”. Prasad in Kerlinger (2000)
observes that content analysis is also considered as an
unobtrusive or non-reactive method of social research, instead
of asking people to respond to questions, it takes the
communications that people have produced and asks questions
about. Broadly, content analysis may be seen as a method where
the content of the message forms the basis for drawing
inferences and conclusions about the content. Gunter (2000)
describes content analysis as any systematic procedure devised
to examine the content of recorded information. Kerlinger
(2000) describes content analysis as the method of studying and
analysing communication in a systematic, objective and
quantitative manner for the purpose of measuring variables.
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Kerlinger’s definition involves three concepts that
require elaboration as noted by (Wimmer and Dominick 2011).
First, content analysis is systematic. This means that the content
to be analyzed is selected, according to explicit and consistently
applied rules: Sample selection must follow proper procedures
and each item must have an equal chance of being included in
the analysis. Moreover, the evaluation process must be
systematic: All content under consideration is to be treated in
exactly the same manner. There must be uniformity in the
coding and analysis procedures and in the length of time coders
are exposed to the material. Systematic evaluation simply
means that one and only one set of guidelines is used for
evaluation throughout the study. Alternating procedures in an
analysis is a sure way to confound the results.
Second, content analysis is objective; that is, the
researcher’s personal idiosyncrasies and biases should not affect
or influence the findings. The analysis should yield the same
results, if another researcher replicates the study. Operational
definitions and rules for the classification of variables should be
explicit and comprehensive so that other researchers who repeat
the process will arrive at the same decisions. Unless a clear set
of criteria and procedures is established that fully explains the
sampling and categorization methods, the researcher does not
meet the requirement of objectivity and the reliability of the
results may be called into question. Perfect objectivity,
however, is seldom achieved in content analysis. The
specification of the unit of analysis and the precise makeup and
definition of relevant categories are areas in which individual
researchers must exercise subjective choice.
Third, content analysis is quantitative. The goal of
content analysis is an accurate representation of a body of
messages. Quantification is important in fulfilling that objective
because it aids researchers in the quest for precision. The
statement “seventy percent of all prime-time programmes
contain at least one act of violence” is more precise than “most
shows are violent.” Additionally, quantification allows
researchers to summarize results and to report them succinctly.
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If measurements are made over intervals of time, comparisons
of the numerical data from one time period to another can help
simplify and standardize the evaluation procedure.
Apparently, quantification gives researchers additional
statistical tools that can aid in interpretation and analysis.
However, quantification should not blind the researcher to other
ways of assessing the potential impact or effects of the content.
Uses of Content Analysis
Wimmer and Dominck (2011) also established five uses
of content analysis as follows:
1) Describing communication content and systematic
period: they examine what exist. For example the
character trend of comedian on the newspapers or the
focus or trends of coverage in the print media.
2) Testing hypothesis of message characteristics: this has
to do with measuring the hypothesis. For example, if a
source has characteristic A, then message containing
element X and Y would be produced. If a source has a
characteristic B, then message containing elements W
and Z would be produced.
3) Comparing media content to real world: some content
analytical studies reflect on the degree of agreement,
correlation or harmony between recorded matters and
plain reality. While the former is supposed to describe
the latter, the level of authenticity of the former is often
accessed by real world experience especially where no
major introduced correlation between situation A and
situation B.
4) Image assessment of social group: this is, if you want to
see how group is been portrayed in the media. Find-line
of investigation include; direction of coverage and scope
of coverage.
5) Establishing a starting point for studies of media effects:
the use of content analysis as a starting point for
subsequent studies is relatively new; the best example is
the cultivation analysis, what is the dominant messages
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and themes in the media which are documented by
systematic procedure and several areas of studies are
conducted to see whether the messages are fostering
similar attitude among heavy media users.
Advantages of Content Analysis
1. It is regarded as self design especially because of the
impersonality involved in content analysis. Here, clear
content categories are well defined.
2. Researcher is bound to work with all matters within his
research. He cannot discard anything even if he has
source.
3. The very idea of quantification to lend some credibility
of research process, etc.
Disadvantages of Content Analysis
1. It cannot be used as a sole design in effects studies.
Effects studies require some correlation between
equivalents to observe relation. The researcher set to
measure degree to which a certain phenomenon has been
affected.
2. Methodology in content analysis is often individualistic.
Different studies have different categories.
3. It requires money and time. Time is taken as well as
money is involved in content analysis.
Manifest Coding
Coding entails the act of placing a particular unit of
analysis into a content category. Coding is a visible surface in a
text, for example, the researcher counts a number of time or
phrase that appears in a written text or whether it is a street
action. Unfortunately, manifest coding does not take the
consideration of word into count. Coding sheet is a standardized
sheet which allows coder(s) to classify data by placing check
marks or slashes in predetermined spaces, Wimmer and
Dominick (2006, p.163). A coding sheet is important because it
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is used to record findings derived from the entire coding
exercise.
Latent or systematic Analysis: a researcher uses latent coding
to underline the simplicity meaning. His or her coding system
has general rules to guide his or her interpretation of the text in
determining whether a particular mood or theme is present;
latent coding turns to be unreliable because it has to depend on
the coder’s meaning.
Intercoder Reliability
An instrument is valid if it accurately achieves the
purposes for which it was designed. This is because objectivity
is very difficult to achieve in content analysis, thus, reliability
relates to the consistency of the data collected and to ensure the
reliability of the instrument. The reliability of the research
instrument, according to Wimmer and Dominick (2011, p.170)
noted that “a study is reliable when repeated measurement of
the same material results in similar decisions or conclusions”.
Therefore, research in mass communication use the instrument
of inter-coder reliability test. Thus, the formula for determining
the reliability test is examined thus:
Where Reliability will be =
Where 2M will be the number of coding decisions on
which two coders agree and N1 is the decision of the first coder
while N2 is the coding decision of the second coder (Wimmer
and Dominick, 2011, p.172). See the example below:
Coder 1 (Master coder)
Daily Trust
Guardian
Leadership
The Nation
Total
Variables
No
%
No
%
No
%
No
%
No
%
Positive
68
66.7
122
68.5
49
76.6
102
71.8
341
70.2
Negative
25
24.5
22
12.3
8
12.5
16
11.3
71
14.6
Neutral
9
8.8
34
19.1
7
10.9
24
16.9
74
15.2
Total
102
100
178
100
64
100
142
100
486
100
100
Coder 2 (Trained coder)
Daily Trust
Guardian
Leadership
The Nation
Total
Variables
No
%
No
%
No
%
No
%
No
%
Positive
68
66.7
122
68.5
49
76.6
102
71.8
341
70.2
Negative
25
24.5
22
12.3
8
12.5
16
11.3
71
14.6
Neutral
9
8.8
34
19.1
7
10.9
24
16.9
74
15.2
Total
102
100
178
100
64
100
142
100
486
100
(Source: Kuchi, 2018).
From the above tables (Master coder)and (Trained
coder), which analyzed the direction of the newspapers’
coverage of agricultural news in Nigeria, it was clear that 341
news stories amounting to (70.2%) of the total stories analyzed
were positively reported, while 71 (14.6%) news stories were
negative and 74 news stories neutral level representing 15.2%
within the period under investigation.
Therefore, there was no difference in the coded data
between the researcher and the trained coder. The trained coder
agreed with the researcher on all the coded items in the editions
selected for review. The inter-coder reliability is presented
below: Inter-coder reliability;
R = 2M
N1 + N2
R = 2(486)
486+486
R =
R = 1
Unit of Analysis
The unit of analysis is the entity that is counted in a
content analysis. It is the smallest element of such an analysis,
but it is also one of the most important. In written content, the
unit of analysis might be a single word or symbol, a theme or an
entire article or story. In television and film analysis, units of
analysis can be characters, behavioural actions or entire
programmes. Specific rules and definitions are required for
determining these units and to ensure agreement between coders
in their identification and cataloguing (Gunter, 2000, p. 64). A
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unit of analysis in newspaper could be news stories, feature
articles or editorial etc.
Measurement in Content Analysis
Measurement in content analysis uses structure
observation, columns, etc, the rules explain how to categorise
and classify observations. As it is other measurements, coding
system in content identify four characteristics of such content.
1. Frequency.
2. Direction.
3. Space.
4. Intensity or Magnitude.
Frequency: simply means counting whether or not
something occurs and if it occurs, how many time? E.g. how
many people appear on a programme within a given time?
Direction: is nothing but the tone of the messages
among the continuum, that is, it could be positive, negative or
neutral.
Space: this involves the allocation of portion in the
media to a particular story.
Intensity: it has to do with the depth or length of the
story as well as the power in the direction. We also have minor
and major intensity. E.g. the characteristic of forgetfulness can
be minor or major.
Apparently, there is a current trend in the process of
selecting content categorisation which is somewhat different
from crime, agriculture, corruption, entertainment, social news,
health, business, conflict among others. To determine a content
category, one is expected to look at issues that are related to that
particular study one is investigating. For instance, a researcher
conducting a study on “Content Analysis of the Coverage of
Arms Deal Scandal in the Daily Trust, The Nation and The
Guardian newspapers can develop his content analysis base on
the typology of corruption as follows: Political corruption,
economic corruption, administrative corruption, grand
corruption, petty corruption and systematic corruption.
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Design in Content Analysis
According to Maikaba (2019) a research design is a plan
for collecting and analysing data in order to answer
investigation questions. It clearly integrates the procedure for
selecting a sample of data for analysis, content categories and
units to place within such categories, comparism between
categories and the classes of influences that may be drawn from
the data.
Basically, the clarity of thought of the researcher is the
secret of an excellent design. From the unsaid, one proposes a
great measure of harmony among the elements of theories, data
gathering, analysis and interpretation of findings. Maikaba
(2019) maintains that several studies have failed because of
haphazard design often described as fishing expedition, where
there is a “random” search research matter with no clear court
definition of expectation and intention. This is equated with a
sampling building material and builders with no housing plan
and the effort is often useless. Such ex-post-factor studies make
the systematic study a useless venture.
Therefore, describing characteristic of communication,
most content analytical studies focus on message attributes
without reference to the intentions of the sender (encoder) or the
effect on the receiver (decoding).Hypothesis are tested in
relation to the purpose of attention, trends in communication
and comparism of media output. Thus, securing scientific
evidence in content analysis involves making at least one level
of comparism. In this perspective, meaningful and accurate
conclusion is reached when content data are compared with
other data. According to Holsti cited in Maikaba (2019) there
are three basic types of comparism in text description as
examine thus:
1. An analyst may compare a content matter from a single
source in several ways. This involves comparing
messages from a single source over time and drawing
carefully observed trends. For example, looking at the
programming format at NTA, Kano or ARTV, Kano or
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Freedom Radio over time or political reporting in the
Daily Trust.
Key:
ABCD - Source or recipient of messages
XY - Content variables
Z - Non-content variable
S1 S2 - Situation
T1 T2 - Time
An arrow with is representing
comparism between categories.
An arrow with represent
influence to be drawn from comparism.
E.g. AxB BxA
T1 T2
A = represent the sender
B = represent the receiver
X = content variable
T1 = time one
T2 = time two
Message produced Message produced
Content Variable
A A
X X
T1 T2
Trend in communication content
2. An analyst may also compare single source of messages
using different situations. Here, the aim is to examine
how changes in circumstance or context impact on a
specific communication matter. For instance, will
newspapers in competitive environment give better
coverage than monopoly newspapers? Or are there
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significant differences in novels with those written
immediately after the Civil War and those written in the
Second Republic?
Messages produced by A: situation Messages produced by A: situation
S1 S2
Content A A
Variables X X X
S1 S2
Effects of situation on communication content
3. An analyst may also study how the character of
audiences affects the content and style of
communication. Here, content matters examined are
those produced by a single across several audiences. For
instance, an author writing for children and also for
adult. Or a reporter reporting on conflicting society and
also reporting on a peaceful society.
Message produced by source A
Content variable A
X X
C (Relationship of content
variable to each other)
Content variable Y A
Y
D
Therefore, the AA represents different programmes on a
television situation. Content variable X (A) is tales by
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moonlight, while content variable CY (A) represent kiddies’
vision, C and D represent the various audiences of the
programme. A design therefore calls for comparism by
messages derived from the same source but spread or address to
several audiences. Example of this approach includes the
analysis of rhetorical style of late Chinua Achebe’s writing for
children and for adult.
The above descriptions examined the comparism of the
content of communication across TIME, SITUATION and
AUDIENCES. However, these all still fall within inter-message
study (relationship between messages). Some design also study
relationship between two or more variables within a single
document or a set of documents. Here, special attention is paid
to how the value or condition of a variable changes the position
of the other. Researchers also use these designs to study how
self-perceptions and feeling towards other relations are.
Example, using the quality on how person A sees others.
(C) Experimental Research Method
This involves a deliberate manipulation of related
variables and population samples to ascertain the relationship of
one to another. Experiments may be carried out in the
laboratory or in the field. They are however prone to distortion
because of the involvement of miscellaneous variables that
affect the subjects of an experiment. It is even more so in the
field where the researcher often finds it difficult to eliminate or
control stimuli. Experimental research is the type of research
that entails the researcher manipulating variables. It entails
manipulation and observation. In this case, the researcher
manipulates the different variables like dependent and the
independent variables. It simply follows the process of
experimentation. The essence of this manipulation and
observation is to find out the relationship that exists between the
variables in questions (Asemah et al., 2012). Experimental
research has to do with the study of the effects of variables
manipulated by the researcher in a situation in which all other
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variables are controlled and completed for the purpose of
establishing causal relationships.
Exercising control in experimental research is not easy
as a careless researcher might manipulate other variables by
accident when introducing variables. The researcher in the
process may manipulate the wrong variable and this is called
confounding. The controlled experiment, according to Wesley
cited in Stempel and Wesley (1981) is, when properly carried
out and most powerful method of seeking answers to research
questions available to the behavioural scientist. As explained by
Osuala (2005) experimentation serves the following purposes:
i. To derive verified functional relationship among
phenomena (events and occurrences) under controlled
conditions.
ii. To identify the conditions underlying the occurrence of
a given phenomenon.
iii. To enable the researcher improve the conditions under
which he observes and thus, to arrive at more precise
results.
Types of Experimentation
Basically, there are two techniques that can be used to
carry out experimental research; namely: laboratory and field
experiments.
Laboratory experimentation: a laboratory experiment is
usually carried out in a special place (building, room, studio,
etc), it is used for scientific research purposes otherwise,
referred to as a laboratory, where conditions which are likely to
affect the experiment can be varied or controlled as desired. The
control of these conditions or variables is necessary in order to
be able to measure or calculate as accurately as possible, how
one variable affects the other and the extent of influence it
exerts on it. This way, it is possible to establish causal
relationship among variables (Sobowale, 1983). In other words,
one is able to say with a considerable degree of certainty that
variable A causes variable B. Researchers using the laboratory
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method have control over areas of the study. The following uses
of laboratory approach are as follows:
a. To investigate hypotheses and research questions under
controlled conditions.
b. To develop theories that can be tested in the field.
c. To refine existing theories and research findings.
d. To investigate problems in small step.
e. To ease replication since condition of the study are
clearly specified.
Advantages of Laboratory Experiment
1. It allows in-depth isolation to desired research problems
and gives room for understanding the interactions that
occur between variables.
2. It enables the researcher to test hypotheses and to
establish the veracity of theories.
3. It has a high replicability: that is, the study of one
researcher can easily be verified and replicated by
another researcher.
Disadvantages of Laboratory Experiment
1. It is performed in controlled conditions that are artificial.
2. It is generally considered to lack external validity.
3. It usually necessitates subject.
Field Experimentation: unlike laboratory experiment,
field experimentation is carried out in the natural environment
of the experimental subject. That is, instead of taking the
experimental subject to the laboratory where the experiment is
to take place, the experiment is performed on the subject on the
field. Like laboratory experiments, field experiments have both
the experimental group (the group that receives the
experimental treatment) and the control group (the group that
receives no experimental treatment). However, the field
experimenter does not have as much control over the
environment in which he conducts his study as the laboratory
experimenter has. Wimmer and Dominick (2011) established
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some of the issues that can be investigated through field
experimentation as follows:
i. What people would do without television or
newspapers.
ii. The positive and negative impacts of television on
community.
iii. The effectiveness of an advertising campaign.
iv. The impact of PR campaign.
v. The impact of the mass media on politics.
Advantages of Field Experimentation
1. They are inexpensive when compared with the
laboratory experiment. This is because most field studies
do not require equipment.
2. They are a reliable means of studying complex social
processes and situations.
3. They have the advantage of non-reactive. This means
the influence that a subject’s awareness of being
measured or observed has on his behaviour.
4. The results of field experiments are usually more
reliable, because they often, will represent reality better
than the artificial laboratory situation.
5. Field experiments have external validity because study
conditions closely resemble natural setting, etc.
Disadvantages of Field Experimentation
1. Researchers cannot control all the intervening variables
in a field experiment and this may affect the precision of
the experiment and the confidence researchers may have
in the outcome of the research.
2. There could be bias among respondents as they may
want to please the researcher by giving him the type of
response he wants.
3. They often experience external hindrances that cannot
be anticipated, and
4. It is difficult for researchers to control the entire
intervening variable in a field experiment. The presence
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of extraneous variables affects the precision of the
experiment and the confidence of the researchers in its
outcome.
Guideline for Conducting Experimental Research
Wimmer and Dominick (2006) established eight
guidelines as follows:
(a) Selection of the Setting: the investigator has to select the
environment where the experiment will be conducted.
The setting may be a laboratory or field. That is, natural
or artificial setting. The researcher has direct control of
the experiment if it is in the laboratory but he has little
or no control if it is a natural setting.
(b) Selection of the Experimental Design: the research
design to be used depends on the research question or
the research hypothesis and the type of variables to be
manipulated or measured, the availability of subjects
and the amount of resources available. The experimental
design may be pretest posttest control group, posttest
only group design, factorial design, quasi experimental
design, interrupted times series designs among others.
(c) Operationising the Variables: the next phase in
conduction experimental research is to operationalise the
variables to be manipulated. In the experimental
approach, independent variables are usually
operationalised in terms of the manipulation done to
create the dependable variables and are operationalised
by constructing scales or rules for categorising
observation of behaviours.
(d) Deciding on How to Manipulate the Variables: a set of
specific instructions, events or stimuli are developed and
presented to the experimental subjects when
manipulating the independent variables. Wimmer and
Dominick (2006) established two basic ways of
manipulating variables. These include, straight forward
and staged. The straight forward manipulation is the
situation where written materials, verbal instructions and
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other stimuli are presented to the subjects. While the
stated manipulation is the situation where by researchers
construct events and circumstances that enable them to
manipulate the independent variables.
(e) Select and Assign Subjects to Experimental Conditions:
there is the need to randomly select subjects from the
population under study.
(f) Conducting a Pilot Study: the pilot text is a text to
ascertain whether or not the manipulation of the
independent variable actually has the intended effect.
These pilot texts or studies, usually involve small
samples of people, they may be as few as twenty or even
ten and who take part in an experiment. These people
are often interviewed to find out if they had difficulty
with experimental materials or responding to measures.
Although, not all the experiments are complicated
enough to require a pilot study in general, the more
experienced researchers are, the more likely they are to
complete one prior to full scale experimentation. Pilot
studies are so important to researchers because, through
such studies, the researcher will be able to discover
additional variables that if not controlled, may likely
endanger the quality of the conclusion of research
studies.
(g) Administer the Experiment: this is the stage of data
collection. It is at this stage that the researcher begins to
carry out the experimental manipulation. This
experimental manipulation can be carried out on either
individual or group level. Wimmer and Dominick (2006,
p. 235) note that “It is at this stage that the dependent
variable is measured and the subjects are debriefed.
They further explain that, the researcher needs to explain
the purpose and the implication of the research during
debriefing.
(h) Analyse and Interpret the Result: here, the researcher
begins to analyse the data and also, interpreting them.
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Experimental Research Designs
Experiments are not conducted haphazardly; they are
carefully designed to achieve expected or desired result.
Consequently, there are several experimental designs available
to the researcher to choose from. Osuala (2005, p. 221)
established that “experimental designs vary in complexity and
adequacy, depending on some factors. These include the nature
of the problem at hand, the nature of the data and the facilities
for carrying out the study. The following are the most widely
used experimental designs as examined thus:
1. Pre-test or Post-test Control Group: this is a fundamental
and widely used procedure in all research areas. In this
design, subjects are randomly selected and each group is
given a pre-test. However, only the first group receives
the experimental treatment.
2. Post-test Only Control Group: when researchers are
hesitant to use a pre-test because of the possibility of
subject sensitization to the post-test, the design is altered
to a post-test only control group. Neither group has a
pre-test but a group is exposed to the treatment or
experimental variable, followed by a post-test. The two
groups are compared to determine whether a statistical
significance is present.
3. Solomon Four Group Design: this design combines the
first two designs and is useful if pretesting is considered
to be a negative factor. Each alternative for pre-testing
and post-testing is accounted for in the design, which
makes it attractive to researchers.
Chapter Summary
Chapter Three discusses the quantitative approach to
social science inquiry. The quantitative methods of research
available in social science research like survey, content analysis
and experimental research method were discussed. One of the
striking points regarding survey research is that of the most
popular and widely used methods in social science research.
Perhaps, this is because it yields very vast information at a
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relatively low cost. This method enables the researcher to obtain
large sum of information. Similarly, content analysis was also
given due cognizance which entails the manifest content of
messages,which are normally examined by the researcher.
Apparently, experimentation also formed another part of
discussion on the account of manipulation of variables to bring
about the relationship that exists between them. Under this
method, the researcher manipulates the independent and
dependent variables to see what relationship exists between
them. It was argued in this regards that experimentation is not
only limited to the natural or physical sciences and psychology
but also useful in other disciplines like communication. Within
this context, it is apparent that quantitative method is
predominantly used in social science. The essentialities that
facilitate the use of quantitative methods were comprehensively
examined.
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Chapter Four
Mixed Methods Research
Introduction
In mixed methods, researchers combine qualitative and
quantitative empirical approaches. Mixed methods research
should not be confused with mixed models research, which is a
quantitative procedure or with multimethods research, which
entails using multiple methods from the same approach. Mixed
methods research involves the following: describing the
philosophical assumptions or theoretical models used to inform
the study design, describing the distinct methodologies, research
designs and procedures in relation to the study goals, collecting
and analyzing both the qualitative and the quantitative data in
response to research aims, questions or hypotheses and
integrating the findings from the two methodologies
intentionally to generate new insights (American Psychological
Association, 2020).
The basic assumption of a mixed method approach is
that the combined qualitative findings and quantitative results
lead to additional insights not gleaned from the qualitative or
quantitative findings alone (Creswell, 2015). Because there are
many ways to design a mixed methods study, the structure of
mixed methods varies depending on the specific nature of the
study and the balance between the two methodologies.
Researchers who used a mixed methods approach should follow
the mixed methods format to report their findings.
Mixed methods research is an approach to inquiry
involving collecting both quantitative and qualitative data,
integrating the two forms of data and using distinct designs that
may involve philosophical assumptions and theoretical
frameworks. The core assumption of this form of inquiry is that
the integration of qualitative and quantitative data yields
additional insight beyond the information provided by either the
quantitative or qualitative data alone.
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Mixed Methods Designs
Mixed methods involve combining or integration of the
qualitative and the quantitative research and data in a research
study. Qualitative data tends to be open-ended without
predetermined responses, while the quantitative data usually
includes closed-ended responses, found on questionnaires or
psychological instruments. The field of mixed methods research
began in the middle to late 1980s. Its origins, however, go back
further. In 1959, Campbell and Fisk used multiple methods to
study psychological traits, although their methods were only
quantitative measures. Their work prompted others to begin
collecting multiple forms of data, such as observations and
interviews (qualitative data) with traditional surveys (Sieber,
1973). Early thoughts about the value of multiple methods,
called mixed methods, resided in the idea that all methods had
bias and weaknesses and the collection of both the quantitative
and the qualitative data neutralized the weaknesses of each form
of data.
Within this context, triangulating data sources, which is
a means for seeking convergence across the qualitative and the
quantitative methods was born. By the early 1990s, mixed
methods turned toward the systematic integration of the
quantitative and the qualitative data and the idea to combine the
data through different types of research designs emerged. These
types of designs were extensively discussed in a major
handbook addressing the field in 2003 and reissued in 2010
Convergent
Exploratory Sequential
Explanatory Sequential
Mixed Methods
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(Tashakkori and Teddlie, 2010). Procedures for expanding
mixed methods developed such as follows:
a. Ways to integrate the quantitative and qualitative data,
such as one database, could be used to check the
accuracy (validity) of the other database.
b. One database could help explain the other database and
one database could explore different types of questions
than the other database.
c. One database could lead to better instruments when
instruments are not well-suited for a sample or
population.
d. One database could build on other databases and one
database could alternate with another database back and
forth during a longitudinal study.
Further, the designs were developed and notation was
added to help the reader understand the designs, challenges to
working with the designs emerged (Creswell, Plano and Clark,
2018). Practical issues are being widely discussed today in
terms of examples of “good” mixed methods studies and
evaluative criteria, the use of a team to conduct this model of
inquiry and the expansion of mixed methods to other countries
and disciplines. Although many designs exist in the mixed
methods field, this book will focus on the three primary designs
found in the social sciences today:
1) Convergent mixed methods is a form of mixed methods
design, which the researcher converges or merges the
quantitative and the qualitative data in order to provide a
comprehensive analysis of the research problem. In this
design, the investigator typically collects both forms of
data at roughly the same time and then integrates the
information in the interpretation of the overall results.
Contradictions or incongruent findings are explained or
further probed in this design.
2) Explanatory sequential mixed methods is the one, which
the researcher first conducts the quantitative research,
analyzes the results and then builds on the results to
explain them in more detail with the qualitative research.
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It is considered explanatory because the initial
quantitative data results are explained further with the
qualitative data. It is considered sequential because the
initial quantitative phase is followed by the qualitative
phase. This type of design is popular in fields with a
strong quantitative orientation (hence the project begins
with the quantitative research), but it presents challenges
of identifying the quantitative results to further explore
and the unequal sample sizes for each phase of the
study.
3) Exploratory sequential mixed method is the reverse
sequence from the explanatory sequential design. In the
exploratory sequential approach the researcher first
begins with a qualitative research phase and explores the
views of participants. The data are then analyzed and the
information used to build into a second, quantitative
phase. The qualitative phase may be used to build an
instrument that best fits the sample under study, to
identify appropriate instruments to use in the follow-up
quantitative phase, to develop an intervention for an
experiment, to design an app or website or to specify
variables that need to go into a follow-up quantitative
study. Particular challenges to this design reside in
focusing in on the appropriate qualitative findings to use
and the sample selection for both phases of research.
These basic or core designs then can be used in more
complex mixed methods strategies. The core designs can
augment an experiment by, for example, collecting qualitative
data after the experiment to help explain the quantitative
outcome results. The core designs can be used within a case
study framework to deductively document cases or to generate
cases for further analysis. These basic designs can inform a
theoretical study drawn from social justice or power as an
overarching perspective within a design that contains both the
quantitative and the qualitative data. The core designs can also
be used in the different phases of an evaluation procedure that
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spans from a needs assessment to a test of a program or
experimental intervention.
Chapter Summary
The Chapter discusses the mixed method approach. It
was articulated that mixed methods approach can be located
within the pragmatic worldview, which involves the collection
of both the quantitative and the qualitative data sequentially in
the design. The researcher bases the inquiry on the assumption
of collecting diverse types of data and provides a more
complete understanding of a research problem than the
quantitative or the qualitative data. The study begins with a
broad survey in order to generalize results to a population and
then, in a second phase, focuses on qualitative, open-ended
interviews to collect detailed views from participants to help
explain the initial quantitative survey. Therefore, mixed method
is a comprehensive approach that establishes a synergy of
database from the quantitative and the qualitative approach.
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Part Two
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Chapter Five
Understanding Sampling in Research
Introduction
Understanding sampling in research is very fundamental
and essential in all the aspects of research methods. Sampling as
a procedure involves a set of rules or convention that governs
the selection of a relatively adequate number of cases to
represent large number of cases. Sampling technique is very
imperative in research because it enables one to determine a
sample or the samples to be drawn from the entire population
under study. Generalizability of results is often made on the
bases of a representative sample of the population. When
correctly done our results might yield generalisations that
Yorubas are street smart but politically have herd mentality; the
Hausas are politically suave; the Igbos are business savvy and
politically naive, Nigeria is a festering nest of 419ners and other
criminals, etc. We arrive at such conclusions after we have
encountered, not a whole population but a representative
sample. There is always the risk that such few cases from the
population could represent aberrations, rather than the norm.
The Population
In scientific research, a specified boundary or the body
of contents to be considered, which requires an appropriate
operationalisation of the relevant geographical or socio-cultural
entity is what is termed as population. The population to be
studied should be defined narrowly enough to permit gathering
manageable size of information. Stempel, in Stempel and
Wesley (1981, p. 122) notes thus; what we are asking here is
simply, whether, we are going to consider words, statements,
sentences, paragraphs or an entire article. This implies that the
researcher has to describe the area of focus.
To draw samples from populations, communication
researchers must first define the population. This implies that
populations are defined by the researchers, according to the
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characteristics of the subjects or objects where the researcher
selects his samples from (Asemah et al., 2012). Population,
according to Asika (2009) is made up of all conceivable objects,
elements or observations relating to a particular phenomenon of
interest to the researcher. The population may be animal,
television viewers, students or any other quantifiable measure.
A population is the universe or events from which a sample is
drawn. The population ranges from abstract to non-abstract
things, that is, tangible and intangible things.
Population could be infinitely large (such as all the
children, past, present and future) or finite (such as primary six
children attending a particular school on a given day). Asika
(2009, p. 39) provided a similar view when he noted that, “a
population may be finite, in which case, its size or extent is
conceivable and estimable”. For instance, the subjects that make
up Nigerian population can be counted. Thus, the population of
Nigeria is finite and estimable. Population may also be infinite,
which means that it is impossible to count all the elements or
subjects that make up the population. For example, grains of
sand in the world cannot be counted. Asika further noted that a
population may be finite, yet not countable. All ants that inhabit
the world constitute a finite population, which cannot possibly
be counted.
Therefore, to draw samples from populations,
communication researchers must first define the population.
Assuming that as a communication researcher, you are
interested in studying the degree to which mass communication
students in Bayero University rely on news from radio in
preference to newspaper, all the mass communication students
in Bayero University will be your population and you will like
to make sure that samples are drawn to represent them. This
implies that populations are subjects or objects. Thus, the
researcher selects his samples from the population. In selecting
a target population, the following points must be noted:
1. It has at least, one characteristic that distinguishes it
from another.
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2. It may be of any size and may cover almost a given
geographical area.
3. It is not often possible to exhaust all its elements. That
is, it is finite. At times, we may target an infinite
population.
4. The whole group of study may be available. Only a
portion, the accessible population is sampled.
Therefore, for a study to be able to stand, a target
population must be established. This is very important because
it will enable the researcher to extract an appropriate sample
size for the study.
Why Sampling?
From the understanding of the concept, it becomes
evident that sampling is paramount in research. Sampling is
important in research for a number of reasons:
(a) It allows the researcher to gain sufficient knowledge of
what is obtainable in the entire population. This is so
because a small unit of the population once correctly
selected, is used to represent the entire population based
on similarities and the characteristics, which the entire
subject have in common. For instance, a researcher can
sample students of Bayero University, Kano to represent
university students in the Northern states of Nigeria
because, they think and behave alike.
(b) It is cheaper to study a sampled population than
studying the entire population. This is because, through
sampling, the researcher only deals with a unit of the
population, more realistic than attempting to reach the
entire population.
(c) Sampling is imperative because it enables researchers to
estimate the population characteristics. It is not possible
to study the entire population in most circumstances; the
only way to carry out such a study is to sample part of
the population of the study.
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(d) When we sample, our research work becomes more
thorough because, the researcher has more time to
supervise the work.
(e) The researcher achieves results quickly. Sampling
allows researchers to obtain quick result rather than
covering the entire population.
Determining Sample Size
Determining an adequate and representative sample size
is one of the most controversial aspects of sampling (Wimmer
and Dominick, 2011). This is compounded by the apparent
absence of a formula or method available for every research to
determine sample. Once the body of content to be considered
has been specified, the researcher has to determine the sample
size. In some instances, the universe may be small enough to be
analysed in its entirety. More often, researchers must sample a
subset of content from that total universe which is too large to
be analysed in full.
According to Asemah et al., (2012) sample size
determination is the act of choosing the number of observations
to include in a statistical sample. The sample size is an
important feature of any empirical study, which the goal is to
make inferences about a population from a sample. In practice,
the sample size used in a study is determined by the research
goal and the method available.
Therefore, using too few subjects results in wasted time,
effort and money and ultimately, inconclusive results.
Statistically inconclusive findings make it difficult to determine
whether a particular treatment or intervention was effective and
to identify directions for future studies. Studies with insufficient
subjects also may result in potentially important research
advances that go undetected. In statistical language, these
studies are referred to as “under-powered”. That is, the
probability that they will detect an existing treatment effects
lower than optimal. Using too many subjects may result in
statically significant conclusions and clear future study
directions. According to Chadwick (2001) inadequate and
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inappropriate sample size influences the accuracy and quality of
research.
In any population, there are numerous variables. The
researcher must make decisions as to which variable will be
incorporated into sample size. Wimmer and Dominick (2000, p.
92) established factors, which may determine the selection of a
sample size thus:
1. Type of project.
2. Purpose of project.
3. Complexity of project.
4. Amount of error that may be tolerated.
5. Time constraint.
6. Financial resources available or how much a funding
agency is prepared to spend.
7. Previous research in the area.
Wimmer and Dominick (2011) established some of the
principles, which may guide the researcher in determining an
appropriate sample size as follows:
a. A primary consideration in determining a sample size is
the research method. Focus group discussions use
sample of 6 to 12 people but the result are not intended
to be generalised to the population from which the
respondents are selected except, commonly used for
presetting, measuring instruments and pilot studies.
b. Researchers often use samples of 50, 75 or 100 subjects
per group (such as adult 18, 42 years old).
c. Cost and time consideration always control sample size.
Although, researchers may wish to use a sample of 1000
for a survey, the economies of such a sample are usually
prohibitive. A smaller sample may be forced on a
researcher by constraints.
d. Multivariate studies always require larger samples than
do univariate studies, because they involve analysing
multiple response data. One guideline recommended for
multivariate studies is as follows: 50 = very poor, 100 =
poor, 200 = fair, 300 = good, 500 = very good, 1000 =
excellent. Other researchers suggest using a sample of
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100 plus 1 subject for each dependent variable in the
analysis.
e. For panel studies, central location testing, focus groups
and other projects, researchers should always select in
larger sample than is actually required. The larger
sample compensates for those subjects who drop out of
research studies for one reason or another and
allowances must be made for this in planning the sample
selection.
f. Information about sample size is available in published
research. Consulting the works of other researchers
provide a starting point. If a survey is planned and
similar research indicates that a representative sample of
400 has been used regularly with reliable result, then a
sample larger than 400 may be unnecessary.
g. Generally, the larger the sample the better it is for the
researcher and the readers or other future researchers. A
large unrepresentative sample (Law of Large Numbers)
is as meaningless as a small unrepresentative sample, so
researchers should not consider number alone. Quality is
always more important in sample selection than mere
size.
h. Several sample size calculators are available on the
Internet.
Formulas for Sample Size Determination
Scholars have articulated various formulae for the
determination of sample size. However, sometimes researchers
apply the “law of large numbers” to overcome the problem of
sampling error. Some of these formulae are examined below:
1) Population Proportion Formula: this is a formula for
determining a sample size. It helps in solving the
maximum error of the estimate formula for the
population proportion for n. Some texts use p hat and q
hat but since the sample has not been taken, there is no
value for the sample proportion p and q are taken from a
previous study, if one is available. If there is no previous
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study or estimate available, then use 0.5 for p and q, as
these are the values, which will give the largest sample
size and it is better to have too large of a sample size and
come under the maximum error of the estimate than to
have too small of a sample size and exceed the
maximum error of the estimate. N =
2 p q
2) Population Mean Formula: this is a formula for the
sample size, which is obtained by solving the maximum
error of the estimated formula for the population mean
for ‘n’.
N =
2
3) Cochran’s Formula: the sample size determination
formula as stated by Cochran (1977) is as follows: N =
(T2 X S2) /D2
Where d2 = scale points multiplied by the acceptable
error, T is the T value and S is the estimated variance.
In the AIU data set, the values are as follows:
T = 2.3164, S = 1.166667, Scale points = 7, Acceptable
error = 3%
Therefore, the required sample size is:
N = ([2.3164]2 X [1.166667]2) / [7.3%]2
N = 340.9142
Therefore the required sample size is 341.
Population:
Assuming that the population is 1000, then the sample
size estimated above is greater than 5%. Cochran (1977)
stated that in such a case, the correct formula should be
used; this formula is stated as follows:
N’ = estimated sample / (1 + estimated sample or
population)
In our case therefore, the correctional formula should be
used:
N’ = estimated sample / (1 + estimated sample or
population)
N’ = 341/ (1+ (341/1000)
N’ = 254. 2878
Therefore, sample size should be 254
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Response rate:
When a researcher estimates that the response rate will
be certain percentage then the sample size should be
increased. For the appropriate sample size will be the N’
estimated above, divided by this percentage as follows:
N = 254 or 0.99 = 256.5657
Therefore the appropriate sample size will be 257.
4) Using the Retest Correlation Formula: the retest
correlation is for retests with the same time between the
tests as you intend to have in your experiment. For
instance, if you are doing an intervention that lasts for
two months, you need a two months retest correlation.
Do not used a one day retest correlation, unless you have
good grounds for believing that it will be the same as
two months retest correlation. Also, the spread between
the subjects in the reliability study. If the spread is
different, the value of the retest correlation coefficient
will be inappropriate. In that case you will need to
calculate the appropriate value by combining the within
(s) and between (S) standard deviations for your
subjects, using this formula: retest correlation r = (S2 –
s2)/S2.
Asemah et al., (2012) remarks that, the strategy for
working out the required sample size when you know
the retest correlation is as follows:
a. Work out the sample size of an equivalent cross-
sectional study, N, as shown above. It is 800 in the
traditional approach using statistical significance or
400, using new approach of adequate precision of
estimation for trivial effects.
b. Determine the reliability “r” of the outcome
measured by consulting the literature or doing a
separate study.
c. For a simple design consisting of a single pre and
post measurement on each subject and no control
group, the number of subject is: n = (1 – r)N/2
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This formula applies also to simple crossover
designs, which the subjects receive an experimental
treatment and a control treatment. (One half gets the
experimental treatment first; the other half gets the
control treatment first).
d. If there is a control group the total number of
subjects required is: n = 2(1 – r) N.
e. You need four times the number of subjects when
there is a control group, not twice the number.
f. To take into account the validity of the outcome
measured multiply the above formulae by 1/v2,
where v is the concurrent validity correlation (the
correlation between the observed value and the true
value of the variable). The simplest estimate of the
concurrent validity is the square root of the
concurrent reliability correlation for the outcome
measured, so you simply divide the above formulae
by the concurrent reliability correlation. In general,
the concurrent reliability will be greater than the
retest reliability.
5. Taro Yamane’s Sample Size Formula
Taro Yamane’s formula is as follows:
n = N/[1 + N(e)2] where: n = sample size
N= population size (the universe)
e = sampling error (usually. 10, .0.5 and .01 acceptable
error)
^ = raised to the power of.
6. The Central Limit Theorem: the central limit theorem
describes the characteristics of sample, means if a large
number of equal size sample (greater than 30 subjects) is
selected at random from an infinite population; it goes
thus:
i. The means of the samples will be normally distributed.
ii. The mean value of the sample mean will be the same as
the means of the population.
iii. The distribution of sample means will have its own
standard deviation. This is the distribution of the expected
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sampling error. It is known as the standard error of the
mean. The standard error of a mean is a standard deviation
of the distribution of sample means. It is different from the
dispersions of individual observations. It is computed from
the formula:
Where S =
S = The standard deviation of individual scores.
N = The size of the sample.
SX = The standard error of the mean.
It can be seen that as the size of the sample increases,
the standard error of the means decreases. Thus, as the
sample N approaches infinity, the mean approaches the
population means and the standard error of the means
approaches zero.
S =
=
= 0
As the sample is reduced in size and approaches one, the
standard error of the mean approaches the standard
deviation of the individual scores.
S =
=
= 0
As sample size increases, the magnitude of the error
decreases. Sample size and sampling error are negatively
correlated.
The relationship between sample size and the magnitude of
sampling error
It can be safely generalised that as the number of
independent observations increases, the error involved in
131
generalising from sample values to population values decreases
and accuracy of prediction increases. The formula for
calculating the standard deviation from a sample is given by:
S =
N - 1
Where = sum of squares of deviations in the sample
N = number of cases in the sample.
Sampling Error
Sampling error is the difference between a population
parameter and a sample statistic. Asemah et al., (2012)
established that it is the degree to which a sample differs from
the population characteristics on some measures. As the sample
size gets larger, the amount of sampling error is reduced. This
implies that the larger the population of the sample size, the
more likelihood of the sampling error reducing. If in your
research exercise, you sample the entire population, there may
likely not be any sampling error because, you considered all the
subjects in your population. But, it is always difficult to sample
the entire population in any research exercise. Thus, for a
researcher to reduce sampling error, it is advisable to collect a
very big sample. Sampling error is therefore seen as the
difference between the population parameter and a sample
statistic. Since researchers deal with samples, there must be
some way they compare the result of what was found in the
sample to what exists in the larger population. Such comparism
offers the researcher the opportunity to determine the accuracy
of the data and involves the computation of error.
Wimmer and Dominick (2011) have also noted that
computing standard error is a process of determining what a
certain amount of confidence, the difference between a sample
and the target population. Error can occur by chance or through
some fault of the researcher or flaw in the procedure. The
sampling error provides an indication of the degree of accuracy
of the research.
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Sampling Procedures
Broadly speaking, there are two types of sampling;
namely: probability and non-probability sampling.
(a) Probability Sampling: this uses mathematical guidelines
whereby each unit’s chances for selection into the
sample is known. Probability procedure involves a
random process that will lead to generalisation. In
probability sampling, each unit in the population has an
equal chance of being selected. The probability is the
type that presumes randomization. Randomization is the
process of allowing every subject in a population to have
an equal chance of being selected. Under the probability
sampling, the following types are considered:
1. Simple Random Techniques: here, each subject, element,
event or unit in the population has an equal chance of
being selected. If a subject or unit is drawn from the
population and removed from the subsequent selection,
the procedure is known as random sampling without
replacement. The simple random sampling is aimed at
eliminating bias or subjectivity. The sample is chosen in
such a way that every member of the population has an
equal chance to appear in the sample.
According to National Teacher’s Institute Module,
Kaduna (2008) random does not connote haphazard,
accidental or without aim or direction. It is the process
of selecting a sample in such a way that all individuals
in the defined population have an equal and independent
chance of being selected for the sample. A random
sample does not necessarily represent the characteristics
of the population but when the choice of subjects is left
to chance, the possibility of bias entering selection of the
sample is reduced.
2. Systematic Random Sampling Techniques: this involves
sampling a list by fixed portion or interval. Systematic
sampling entails the selection of respondents according
to a predetermined schedule other than a random
sequence. Systematic sampling involves the selection of
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the ‘nth’ subject or item from serially listed subjects or
units: where ‘n’ is any number usually determined by
dividing the population by the required sample size. In
systematic sampling, the first random selection must fall
between one and the ‘nth’ number.
Thus, Asika notes that the systematic sampling method
involves the selection of ‘nth’ subject or item from
serially listed population subjects or units. ‘N’ is used to
represent any number that is determined by dividing the
population by the required sample size. The population
is given by ‘N’. For instance, in a population where you
have 7000 items or subjects, to select 1000 items or
subjects, using systematic sampling procedure, you
follow the process:
Step I: Number the items or subjects up to 7000;
Step II: Divide 7000 by 1000, i.e. N/n = 7000/1000 = 7;
Step III: Randomly select a starting point, say a number
7 on the population list;
Step IV: Then select every 7th unit after the first. This
list would include the following: 7th, 14th, 21st, 28th, 35th,
42nd, 49th, 56th, 63rd, 70th, etc, on the population list.
3. Stratified Random Sampling: stratified sampling ensures
that a sample is drawn from a homogeneous sub-set of
the population- that is, from a population that has similar
characteristic. Homogeneity helps researchers to reduce
sampling error. In other words, Stratified random
sampling involves dividing your population into
homogenous sub-groups and further taking a simple
random sampling in each sub-group. The sub-group may
be considered based on gender, age, religion, etc.
Kombo and Tromp (2009) explain that the sample is
selected in such a way as to ensure that certain sub-
group in the population is represented in the sampled
population of their member. This sampling technique
simply entails the researcher dividing his population into
sub-unit that is, strata. The researcher groups his
population into certain characteristics and the groups are
134
called strata. Thus, after the population has been divided
into strata, samples will be selected randomly, but
independently from each stratum and an estimate of the
parameter is computed overall strata.
Babbie (2005) observes that a stratified sample is likely
to be more representative on a number of variables than
simple random sampling. Stratified sampling can be
applied in two ways; proportionate stratified sampling
and disproportionate stratified sampling. Proportionate
stratified sampling includes strata with size based on
their proportion in the population. If 10% of the
population is made up of adults between 60-75, the 10%
of the total sample should be subjects in this age
category. After this categorization, the simple random
sampling procedure is used to determine those who
make the selected sample. Disproportionate stratified
sampling, on the other hand, is used to over-sample or
over-represent a particular stratum because of the critical
importance attached to that stratum.
Stratified sampling is used to obtain a greater degree of
representatives. It ensures that different groups in the
population are adequately represented. The researcher
already has an existing idea or knowledge of the
population. With this knowledge, the population is
divided into groups, such a way that when the samples
are combined, it gives a sample of a more heterogeneous
population. For example, a researcher is aware that
students’ population of Bayero University, Kano (BUK),
is made up of 500 Hausas, 300 Tivs and 200 Igbos and
he wishes to draw a sample of 1000 from this. The
researcher would probably not get 500 Hausas, 300 Tivs
and 200 Igbos if he uses the simple random sampling.
Since one group may be over-represented and the other
under-represented. To ensure that all the three groups
are equally represented, the researcher can use stratified
design, since he has knowledge of the proportion of each
group in the population vis-à-vis the entire population.
135
Therefore, a stratified sample of 500 Hausas, 300 Tivs
and 200 Igbos would assume better representation.
4. Cluster Sampling: this method of sampling, according to
Asika (2009) is mainly used when dealing with a
geographically distributed population. If for example, a
researcher in Kano is interested in studying the ethnic
representation in Kano, he will have to use cluster or
area sampling. This is because in Kano, the Igbos live in
Sabon Gari, the Tivs live in Rijiyar Zaki, while the
Hausas who are the indigenes live mainly in the ancient
city. The researcher can use the clusters in Kano as a
basis for his sample selection. Area or cluster sampling
involves sampling areas or clusters first and then
sampling individuals or elements within the clusters.
The decision to use cluster sampling or any other type of
sampling is determined, both by cost and the amount of
sampling error, which can be tolerated. Stratification and
cluster sampling procedures may appear very similar;
hence it is important to take note of the important
difference. The very characteristic which makes
stratified sampling efficient, make cluster sampling
inefficient. With stratified samples, the attempt is to
maximise differences between strata and minimize
differences within each stratum; whereas, with cluster
samples, the attempt is to minimize differences between
clusters and to maximise difference within each cluster
(Ndagi, 1984).
(b) Non-Probability Sampling: this does not follow the
guidelines of mathematical probability. Again, the non-
probability sampling does not allow the generalisation
procedure. However, the significant characteristic
distinguishing the two types of samples is that
probability sampling allows researchers to calculate the
amount of sampling error present in a research study
while non probability sampling does not. The non
probability method is desirable when we are analysing
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situation, issues, attitude or good behaviour pattern. You
adopt a probability procedure when you have a large
population. When you are using probability procedure,
you must make sure it is practicable. That is, time and
facilities. Under non probability sampling, the following
types are considered:
i. Convenience Sampling: this has to do with selecting
those available to take part in the research. It also
refers to as accidental sampling where the selection
is base on the availability of items or people. The
researcher finds a place that is convenient for him
and he stays there to distribute his questionnaires.
The subjects are contacted by accident.
According to Asika (2009) like all non probability
sampling methods, convenience sampling lacks
precision. This characteristic makes them unsuitable
for certain types of sophisticated statistical analysis.
ii. Availability Sampling: here, there is no attempt at
the representation in whatsoever; any man in the
street can be given a questionnaire. This method
should be avoided.
iii. Purposive Sampling: it is a sampling method in
which the researcher uses his judgement to choose
respondents and selects those that best meet the
purpose of the study. It is the sampling method
whereby the researcher selects those considered to
possess the required attributes or information. It is
also called expert choice or judgement sampling.
The common practice is to select cases that you feel
are typical or representative of the population of
interest. The assumption here is that errors of
judgement allow the researcher to purposely target a
group of people, believed to be reliable for the study.
The population may have something in common;
this is done to eliminate certain members of the
population, who do not have the characteristics
desired by the researcher.
137
iv. Snowball: this is otherwise known as ‘referral’
sampling. This type of non probability sampling is
not frequently used in academic research. It involves
searching for people in areas that have useful
information on what you are looking for, perhaps
because of their experiences concerning the issue
under investigation. It is particularly useful to
researchers conducting observational research and
community studies. The research is conducted in
stages. In the first stage, a few persons with the
required characteristics are identified and
interviewed. These persons are used as informants to
identify others, who qualify for inclusion in the
sample. The second stage involves interviewing
these persons who in turn, lead to other persons to be
interviewed and the process continues in that order.
Snowball or chain referral sampling is particularly
useful in the study of deviant sub-cultures, where
respondents may not be visible and routine sampling
procedure impractical. The method is loosely
codified with the result that it lacks rigour.
When to Use Non-Probability Sampling Techniques
In practice, there are researches or sampling situations
where only non-probability sampling method can be used and
the question of probability sampling being superior does not
arise at all. Situations where non-probability sampling could be
used are as identified by Asika (2009) thus:
1. Where the researcher finds that he is dealing with an
infinite population where most sample subjects cannot
be reached or the population elements can only be
imagined.
2. Where random sampling technique is not likely to
guarantee the inclusion of typical cases or subjects. For
example, a researcher who is studying the effectiveness
of a technique for the treatment of alcoholic is not likely
to use random sampling in selecting his sample subjects.
138
He has to reach out for identified alcoholics, who are
likely to participate in the exercise.
3. Again, the type of statistical analysis envisaged by the
research may determine the sampling method.
Statisticians insist on the use of non-parametric statistics
for the analysis of data gathered through non-probability
sampling method. Their argument is that parametric
statistics can only be applied in situations where the
population distribution is known or normal. And since
one cannot state with any level of accuracy the shape of
distribution of some population, the only alternative is to
use a distribution free sample, which is a non-
probability, non-random sampling.
4. Similar to the preceding case is a research situation
where generalisation of result is not necessary or not be
intended. In such a situation, the researcher may not
bother whether or not the sample is representative of the
population.
5. Above all, the costs and the time that are required to
conduct the study may be a very strong determinant of
the use of either probability or non-probability sampling.
In most cases, probability sampling is more expensive
and time consuming than non-probability sampling.
Sampling Terminologies or Concepts
The following are some of the terminologies used in
sampling procedure:
1. Elements: an element is that unit about which
information is collected and, which provides the bases of
the analysis and usually in survey, the elements are the
people.
2. Universe: a universe is a theoretical and hypothetical
unspecified aggregation of all elements as defined by the
study. A universe is only unspecified as regards to time
and space.
3. Population: is a theoretical specified aggregation of a
survey’s elements. The nature of the population will
139
include: the definition of the element and properly the
time references for the study. Population is specific
whereas, universe is not. There are two types of
population: (i) Target population and (ii) Study
population.
(i). Target Population: this is the total group of the entire
individual who fit into a theoretical specification of the
universe. For instance, in a study of radio listeners, a
selection of Freedom Radio listeners indicates your target
population. So, the target is the total population about which
we need information.
(ii). Study Population: some people also refer to it as survey
population. A study population is the total aggregation from
which the sample is selected. It is the part of the target
population from which we can realistically obtain
information. The population could be demographic, which
we can delineate along gender, occupation, age, etc.
4. A sample is a sub-set or sub-part of the population. That
is, with a limited number of elements selected from a
study of a population. E.g. universal students, target
students may be secondary school students or university
students. Thus, for a sample to be good, it has to satisfy
two criteria:
a) The sample must be representable and
b) It must be adequate.
A sample should be drawn base on the problem, the
research hypothesis, research questions or certain other
consideration.
5. Sampling Frame: it is the actual list of sampling unit
from which the sample is selected. Here, the researcher
has no choice of who is to be in the study. All the
elements that appear in the study are by chance or
accident. As such, one cannot conduct survey research
without a sampling frame. For instance, a sample of
electorate of a vote register can serve as a sampling
frame for a particular study. Note, before you choose a
140
sampling frame, one has to be very careful because one
has to examine the adequacy.
Chapter Summary
In this Chapter, the need for the understanding of
sampling in research becomes apt. In this regards, sampling is
said to be a critical component of any scientific inquiry and for
sampling to be effective it must be adequate and representative.
Attempt was also made to discuss population of the study which
constituted the basic integral part of a study. It is the basic
principle that shapes the outcome of the result. Equally, the
sample which is only a portion of the entire population has to be
handled with extreme care, otherwise, all effort put in place for
the successes of the study will be in vain. Consequently, the
researcher may not be able to achieve the representativeness of
a good research sample. When this occurs, the research will
lack validity. Sampling error in this perspective has been
described as the degree to which a sample differs from
population characteristics one measures. In general, as the
sample size increases, the amount of sampling error is reduced.
In Chapter five also, the two basic types of sampling
like probability and non-probability sampling were identified.
Probability sampling is further classified into simple random
techniques, systematic random sampling techniques, stratified
sampling and cluster sampling while non-probability sampling
is further classified into convenience sampling, casual sampling,
purposive sampling and snowball. Similarly, some
terminologies that are used in sampling ranging from elements,
universe, sampling frame among others were given due
cognizance.
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Chapter Six
Statistical Procedure in Social Science Research
Introduction
Statistics is a form of mathematical analysis that uses
quantified models, representations and synopses for a given set
of experimental data or real-life studies. Statistics studies
methodologies to gather, review, analyse and draw conclusions
from data. Statistics is a term used to summarise a process that
an analyst uses to characterise a data set. If the data set depends
on a sample of a large population, then the analyst can develop
interpretations about the population primarily based on the
statistical outcomes from the sample. Statistical analysis
involves the process of gathering and evaluating data and then
summarising the data into a mathematical form. Statistics is the
science concerned with developing and studying methods for
collecting, analysing, interpreting and presenting empirical data.
Statistics is a highly interdisciplinary field, research in statistics
finds applicability in virtually all scientific fields and research
questions in the various scientific fields motivate the
development of new statistical methods and theory. In
developing methods and studying the theory that underlies the
methods, statisticians draw on a variety of mathematical and
computational tools (Maikaba, 2011).
Apparently, two fundamental ideas in the field of
statistics are uncertainty and variation. There are many
situations that we encounter in science (or more generally in
life), which the outcome is uncertain. In some cases the
uncertainty is because the outcome in question is not
determined yet (e.g., we may not know whether it will rain
tomorrow) while in other cases the uncertainty is because
although the outcome has been determined already we are not
aware of it (e.g., we may not know whether we passed a
particular exam).
Therefore, probability is a mathematical language used
to discuss uncertain events and probability plays a key role in
142
statistics. Any measurement or data collection effort is subject
to a number of sources of variation. By this, it means that if the
same measurement were repeated, then the attempt to
understand and control (where possible) the sources of variation
in any situation. Thus, statistics plays a pivotal role in social
science research. Today, researchers make use of software in
analysing data. This software often needs statistical applications
especially when using a quantitative method.
Why Students or Researchers Need the Knowledge of
Statistics?
There are so many reasons why the knowledge of
statistics is significant to students or researchers. Among the
reasons put forward by Abubakar (2019) include:
1. Statistics knowledge enables students or researchers to
recognise which problem is applicable to statistical
solution and which statistical procedure best suit the
problem.
2. Statistics allow students or researchers to summarise
results or data in meaningful and convenient form.
3. Statistics is the basis for quantitative research because
it allows the researcher to collect empirical evidence.
4. A student or researcher needs the knowledge of
statistical concepts for advanced courses.
5. It enables students or researchers to read professional
literature.
Frequency Distribution Tables
In a frequency table, we arrange the data or values in a
distribution. That is, in a group and ungrouped data.
Ungrouped Data
When the data has not been placed in any categories and
no aggregation or summarization has taken place on the data
then it is known as ungrouped data. Ungrouped data, which is
also known as raw data, is data that has not been placed in any
group or category after collection. Data is categorized in
143
numbers or characteristics. Therefore, the data which has not
been put in any of the categories is ungrouped. For example,
you may be asked to prepare a frequency distribution of the
following numbers or values:
5,4,3,3,5,1,2,5,1,5,3,2,3,3,5,3,2,1,2,3,2,5,4,3.
In order to solve this, we need to have “array” which
normally start from lowest to the highest or highest to the
lowest.
Arary: 1,1,1,2,2,2,2,2,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5.
No
Frequency
1
3
2
5
3
8
4
2
5
6
24
Group Data
When raw data have been grouped in different classes
then it is said to be grouped data. As mentioned above, grouped
data is the type of data, which is classified into groups after
collection. The raw data is categorized into various groups and a
table is created. The primary purpose of the table is to show the
data points occurring in each group. For instance, when a test is
done, the results are the data in this scenario and there are many
ways to group this data. Therefore, when the range of values or
numbers is wide, the data is broken into groups or classes with
the corresponding frequencies (Abubakar, 2019). A grouped
frequency table has the following features:
a. Class Limits: these are the extreme values of class. The
lower class limit and the upper class limit. For instance,
Class (class interval is 2)
144
0 - 2
3 - 5
6 - 8
9 - 11
12 - 14
LL UL
b. Class Mark or Class Mid Point: this is the value mid-
way between the class limits. It is the arithmetic
mean of the lower and upper limits.
For example,
=
= 1
=
= 4
=
= 7
c. Class Interval: is the difference between the lower and
the upper class limits and it has to be uniform.
d. Cumulative Frequency: is simply the successive addition
of frequencies.
e. Relative Frequency: this is the frequency of each class
divide by the submission of frequencies in the
distribution.
Using the class interval of three, prepare a frequency
distribution of the following scores:
24,1,9,32,13,8,20,4,28,13,21,16,12,14,17.
Array: 1,4,8,9,12,13,13,14,16,17,20,21,24,28,32.
Class
Freq.
(f)
Class
Mark
(x)
Cumulative
Freq.
Relativ
e Freq.
0 - 3
1
1.5
1
0.67
4 - 7
1
5.5
2
0.67
8 - 11
2
9.5
4
0.13
12 - 15
4
13.5
8
0.27
145
16 - 19
2
17.5
10
0.13
20 - 23
2
21.5
12
0.13
24 - 27
1
25.5
13
0.67
28 - 31
1
29.5
14
0.67
32 - 35
1
33.5
15
0.67
Ʃ = 15
Measurement of Association or Correlation
This is a statistical procedure which examines the
relationship between two or more variables. For instance, the
variable may be education and income. It establishes
relationship or no relationship.
Characteristics of Correlation Procedure
a. There must be two pairs of scores based on the same
individual events.
b. The values of correlation variables ranges between + 1
and – 1.
c. The mean correlation procedure can be in positive or
negative. The positive relation is the one in which an
increase in one event or variable corresponds to an
increase in the other. While negative relation is the one
in which an increase in one event or variable
corresponds to decrease in the other.
d. Correlation is not causation: in examining correlation,
one cannot say one thing causes another. One is just
relating the two. It is the relation that is established not
the causation.
Pearson Product-Movement Correlation Coefficient: this
is the most common method of computing correlation
coefficient which was developed by Karl Pearson and it
is symbolized by “r”.
The formula is r =
146
It varies + 1 and – 1. A correlation coefficient of + 1 indicates
perfect positive correlation. A correlation coefficient of – 1
indicates a perfect relationship in a negative direction.
Therefore, the lowest value that the Pearson Correlation
Coefficient can achieve is 0.00, which represents no
relationship. Steps to Follow:
a. Find X
b. Find Y
c. Find the mean of X
d. Find the mean of Y
e. Find X – X for X – score
f. Find Y – Y for Y – score
g. Square your mean deviation for X (X – X)2
h. Square your mean deviation for Y (Y – Y)2
i. Find (X – X) x (Y – Y)
Question 1: calculate the product-movement coefficient
between the variable X and Y in the table below and state the
nature of the relationship (adopted in Abubakar, 2019 lecture
note)
The formula is r =
X
1
3
4
6
8
9
11
14
Y
1
2
4
4
5
7
8
9
X
Y
x- x
y- y
(x–x)2
(y– y)2
(x-y)x(y- y)
1
1
-6
-4
36
16
24
3
2
-4
-3
16
9
12
4
4
-3
-1
9
1
3
6
4
-1
-1
1
1
1
8
5
-1
0
1
0
0
9
7
2
2
4
4
4
11
8
4
3
16
9
12
14
9
7
4
49
16
28
Ʃx=56
Ʃy=40
Ʃ= 132
Ʃ= 56
Ʃ= 84
147
Key: Y=
=
= 5 X =
=
= 7. Thus, =
=
=
=
= 0.9769
= 0.98
Therefore, the nature of the relationship is positive.
Bar chart, Pie chart, Ogive and Frequency Polygon
Bar Chart is the representation of a given distribution
by different rectangles of equal widths at uniform distances
apart. A bar graph is a graphical representation of frequency
distribution of ungrouped data. It is a pictorial representation of
the numerical data by a number of bars of a uniform width
erected vertically or horizontally, with equal spacing between
them. Bar chart or bar graphs are made of bars placed vertically
or horizontally. The height or length of each bar indicates the
size or frequency of items or values or quantity or quality being
represented. Example, the table below shows the expenditure of
Bayero University, Kano faculty during the last month.
Construction of Bar Graphs
In the process of constructing bar graphs, the following
steps are considered:
Step 1: take a graph paper and draw two lines perpendicular to
each other and call them horizontal and vertical axes.
Step 2: along the horizontal axis, take the values of the variables
and along the vertical axis, take the frequencies.
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Step 3: along the horizontal axis, choose the uniform width of
bars and the uniform gap between the bars, according to the
space available.
Step 4: choose a suitable scale to determine the heights of the
bars. The scale is chosen according to the space available.
Step 5: calculate the heights of the bars, according to the scale
chosen and draw the bars.
Step 6: mark the axes with proper labeling.
Example, represent the information below on a Bar Chart.
Faculties
Expenditure
Agric (A)
400
Education (E)
750
Basic medical (B)
540
Communication (C)
240
Science (S)
470
Displaying the information using a bar chart
Bar Chart
0
100
200
300
400
500
600
700
800
A E B C S
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Histogram: Is a bar gram of frequency distribution. The
base of each bar has its centre at the class mark and its aims at
the class boundaries living no gaps between bars. A histogram
is used to summarise discrete or continuous data. In other
words, it provides a visual interpretation of numerical data by
showing the number of data points that fall within a specified
range of values (called “bins”). It is similar to a vertical bar
graph. However, a histogram, unlike a vertical bar graph, sows
no gaps between the bars.
Parts of a Histogram
a. The title: the title describes the information include in
the histogram.
b. X-axis: the X-axis are intervals that show the scale of
values, which the measurements fall under.
c. Y-axis: the Y-axis shows the number of times that the
values occurred within the intervals set by the X-axis.
d. The bars: the height of the bar shows the number of
times that the values occurred within the interval, while
the width of the bar shows the interval that is covered.
For a histogram with equal bins, the width should be the
same across all bars.
HISTOGRAM
400
750
540
240
470
0
200
400
600
800
Agric Education Basic Science
Communication Science
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Pie Chart: A pie chart or a circle graph is a circular
chart divided into sections, illustrating proportion. In a pie
chart, the arc length of each sector (and consequently its central
angle and area), is proportional to the quantity it represents. The
pie chart is perhaps, the most ubiquitous statistical chart in the
business world. However, it has been criticised and some
recommend avoiding it, pointing out in particular, that it is
difficult to compare different sections of a given pie chart or to
compare data across different pie charts.
A pie chart is a circular statistical graphic, which is
divided into slices to illustrate numerical proportion. In a pie
chart, the arc length of each slice is proportional to the quantity
it represents. It’s a circle divided into radially in a section. The
area of each sector is proportional to the size of the component
its represent. The following is how Aondover Eric spends his
salary:
School fees N 2180
Rent N 1200
Food and clothing N 1060
Electricity N 800
Savings N 940
Others N1020
Total = 7200
Solution:
109o
= 60o
= 53o
= 40o
= 47o
= 51o
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Pie Chart
Ogive or Cumulative Frequency Distribution: In
statistics, ogive, also known as a cumulative frequency polygon,
can refer to one of two things: any hand drawn graphic of a
cumulative distribution function and any empirical cumulative
distribution function. The ogive is a frequency distribution
graph of a series. The ogive is a graph of a cumulative
distribution, which explains data values on the horizontal plane
axis and either the cumulative relative frequencies, the
cumulative frequencies or cumulative percent frequencies on
the vertical axis. This is a distribution, which the cumulative
frequency is plotted against the frequency of the classes.
Therefore, less than Ogive is the line graph obtained by
plotting frequency against their respective cumulative
frequencies. More than Ogive is the linear graph obtained by
plotting the lower boundaries against their respective
cumulative frequencies. See the example below:
109
60
53
40
47
51
Expenditure
school fees
Rent
Food & clothing
Electricity
Savings
Others
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Class
Frequency
Class Mark
Cumulative
0 – 3
1
1.5
1
4 – 7
1
5.5
2
8 – 11
2
9.5
4
12 – 15
4
13.5
8
16 – 19
2
17.5
10
20 – 23
2
21.5
12
24 – 27
1
25.5
13
28 – 31
1
29.5
14
32 – 35
1
33.5
15
Frequency Polygon:
A frequency polygon is the joining of the mid-points of
the tops of the adjoining rectangles. The mid-points of the first
and the last classes are joined to the mid-points of the classes
preceding and succeeding respectively at zero frequency to
complete the polygon. Frequency polygon is the polygon by
joining the points got by plotting the class marks (mid-point of
class intervals) against their respective frequencies (Asemahet
al., 2012).
0
5
10
15
20
0 1 2 3 4 5
Axis Title
Axis Title
OGIVE GRAPH
Y-Values
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A frequency polygon is a graph constructed by using
lines to join the midpoints of each interval or bin. The heights
of the points represent the frequencies. A frequency polygon
can be created from the histogram or by calculating the
midpoints of the bins from the frequency distribution table. To
draw a frequency polygon, for a distribution, we normally plot
the frequency against the class mark and join the point with
straight line. See example of a frequency polygon below using
the preceding figures.
Alternatively: Draw a histogram of the given
distribution and then superimpose frequency polygon on it by
joining the midpoints of the tops of the rectangles.
0
5
10
15
20
25
30
35
40
0 1 2 3 4 5
FREQUENCY POLYGON
Y-Values
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Examples: Draw a frequency polygon of the following
distribution Class boundaries Frequency
26-30 4
31-35 3
36-40 2
41-45 5
46-50 1
51-55 3
56-60 2
Solution Class interval Midpoint
Frequency
21-25 23 0
26-30 28 4
31-35 33 3
36-40 38 2
41-45 43 5
46-50 48 1
51-55 53 3
56-60 58 2
61-65 63 0
N.B: Mark off and label axes as for a frequency
histogram but add one interval below the lowest and one above
the highest class interval and assign them frequencies.
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Frequency Polygon
Statistical Package for Social Science (SPSS)
SPSS is the set of software programs that are combined
together in a single package. The basic application of this
program is to analyze scientific data related with the social
science. This data can be used for market research, surveys, data
mining, etc. With the help of the obtained statistical information,
researchers can easily understand the demand for a product in
the market, and can change their strategy accordingly. Basically,
SPSS first store and organize the provided data, then it compiles
the data set to produce suitable output. SPSS is designed in such
a way that it can handle a large set of variable data formats.
SPSS is a window base program that is used to perform
data analysis and to create tables and graphs. It is capable of
handling large amount of data and can perform all the analysis
covered in the text and much more (Abubakar, 2019). SPSS is
commonly used in the social science and in the business world.
This means that it is an interactive user friendly for the social
science. Statistical Package for Social Science is made up of
two things: data editor (it is used for creating and modifying
data set) and statistical procedures (it is used for analysing data
set).
0
10
20
30
40
50
60
70
0 2 4 6
Y-Values
Y-Values
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How SPSS Helps in Research and Data Analysis Programs
SPSS is revolutionary software mainly used by research
scientists. It helps them process critical data in simple steps.
Working on data is a complex and time consuming process but
this software can easily handle and operate information with the
help of some techniques. These techniques are used to analyze,
transform and produce a characteristic pattern between different
data variables. In addition to it, the output can be obtained
through graphical representation so that a user can easily
understand the result. Read below to understand the factors that
are responsible in the process of data handling and its execution.
1. Data Transformation: this technique is used to convert the
format of the data. After changing the data type, it integrates
same type of data in one place and it becomes easy to manage it.
You can insert the different kind of data into SPSS and it will
change its structure as per the system specification and
requirement. It means that even if you change the operating
system, SPSS can still work on old data.
2. Regression Analysis: it is used to understand the relation
between dependent and interdependent variables that are stored
in a data file. It also explains how a change in the value of an
interdependent variable can affect the dependent data. The
primary need of regression analysis is to understand the type of
relationship between different variables.
3. ANOVA (Analysis of variance):it is a statistical approach to
compare events, groups or processes and find out the difference
between them. It can help you understand which method is more
suitable for executing a task. By looking at the result, you can
find the feasibility and effectiveness of the particular method.
4. MANOVA (Multivariate analysis of variance):this method is
used to compare data of random variables whose value is
unknown. MANOVA technique can also be used to analyze
different types of population and what factors can affect their
choices.
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5. T-tests: it is used to understand the difference between two
sample types and researchers apply this method to find out the
difference in the interest of two kinds of groups. This test can
also understand if the produced output is meaningless or useful.
Layout of SPSS
The Data Editor window has two views that can be
selected from the lower left hand side of the screen. Data View
is where you see the data you are using. Variable View is where
you can specify the format of your data when you are creating a
file or where you can check the format of a pre-existing file.
The data in the Data Editor is saved in a file. The other most
commonly used SPSS window is the SPSS Viewer window
which displays the output from any analyses that have been run
and any error messages. Information from the Output Viewer is
saved in a file.
On the File menu, click Open and select Output. Select
appendixoutput.spo from your disk. Click Ok. The following
will appear. The left hand side is an outline of all of the output
in the file. The right side is the actual output. To shrink or
enlarge either side, you have to put your cursor on the line that
divides them. When the double headed arrow appears, hold the
left mouse button and move the line in either direction. Release
the button and the size will be adjusted.
Finally, there is the Syntax window which displays the
command language used to run various operations. Typically,
you will simply use the dialog boxes to set up commands and
would not see the Syntax window. The Syntax window would
be activated if you pasted the commands from the dialog box to
it.
SPSS Menus and Icons
a. File: it includes all of the options you typically use in
other programs, such as open, save, exit. Notice, that
you can open or create new files of multiple types as
illustrated to the right.
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b. Edit: includes the typical cut, copy and paste. It allows
you specify various options for displaying data and
output. Click on Options and you will see the dialog
box to the left. You can use this to format the data,
output, charts, etc.
c. View: it allows you to select which toolbars you want to
show, select font size, add or remove the gridlines that
separate each piece of data and to select whether or not
to display your raw data or the data labels.
d. Data: it allows you to select several options ranging
from displaying data that is sorted by a specific variable
to selecting certain cases for subsequent analyses.
e. Transform: includes several options to change current
variables. For example, you can change continuous
variables to categorical variables, change scores into
rank scores, add a constant to variables, etc.
f. Analyse: this includes all of the commands to carry out
statistical analyses and to calculate descriptive statistics.
g. Graphs: it includes the commands to create various
types of graphs including box plots, histograms, line
graphs and bar charts.
h. Utilities: this allows you to list file information which is
a list of all variables, there labels, values, locations in
the data file and type.
i. Add on: is a program that can be added to the base SPSS
package.
j. Window: it can be used to select, which window you
want to view (like, Data Editor, Output Viewer or
Syntax).
k. Help: it has many useful options including a link to the
SPSS homepage, a statistics coach and a syntax guide.
Using topics, you can use the index option to type in any
key word and get a list of options or you can view the
categories and subcategories available under contents.
This is an excellent tool and can be used to troubleshoot
most problems.
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Steps for Data Analysis Using SPSS
Basically, there are four steps of data analysis using
SPSS. They include:
i. Get your data into data editor. Here, you can open a
previously set data file or read a spreadsheet, text file or
data base or enter your data directly in the data editor.
ii. Select a procedure from the menus to create charts.
iii. Select the variables you want to use in the analysis. The
variable in the data files are displayed in a dialogue box
for the procedure.
iv. Run the procedure and study the result.
Atlas.ti
Atlas.ti is a powerful workbench for qualitative data
analysis, particularly for large sections of text, visual and audio
data. This software offers support to the researcher during the
data analysis process where texts are analysed and interpreted
using coding and annotating activities. It provides a
comprehensive overview of a research project, which is called
the Hermeneutic Unit (HU) in Atlas.ti and it facilitates
immediate search and retrieval functions (Silverman, 2000).
This programme also has a network-building feature, which
allows one to visually connect selected texts, memos and codes
by means of diagrams. The software facilitates the qualitative
analysis of research data. This software helps in making the
analysis process to be organised transparently, integrated and
grounded in the evidence. It also facilitates the triangulation of
research data collected through multiple methods of data
collections, such as: semi-structure or unstructured interviews,
focus group, literature reviews, photo voice, photographic
videos, etc.
Analytical Strategies in Qualitative Data Analysis
a. Sketching ideas.
b. Taking note.
c. Working words.
d. Identifying codes.
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e. Reducing codes to themes.
f. Counting frequency or codes.
g. Relating categories.
h. Relating categories into analytic framework in literature.
i. Creating a point of view.
j. Displaying the data.
Data analysis in qualitative research consist of preparing
and organising the data (text data as in transcripts or image data
as in form of photographs) for analysis, then reducing the data
into themes through a process of coding and condensing the
codes and finally representing the data in figures, tables or in
discussion.
NVivo
Nvivo is a large and complex piece of software, which is
most helpful when working with large amounts of data,
particularly where the data include different format. It is useful
for managing and organising projects with many separate data
sources to support more transparent and systematic approaches
to coding. For projects with small datasets, Nvivo may be
unnecessarily complex. Nvivo is a software program used for
qualitative and mixed-methods research. Specifically, it is used
for the analysis of unstructured text, audio, video and image
data, including (but not limited to) interviews, focus groups,
surveys, social media and journal articles.
Nvivo allows the researcher to bring order to their data
and to identify commonalities and themes. Some scholars
suggest that because of the search facility, it provides more
rigour, thus strengthening the validity of findings (Welsh,
2002). Whilst the search facilities can provide more rigour, one
should not solely rely on these methods. Indeed, this book
stresses this point enough: Nvivo does analyse data, it is the
researcher(s) that analyse and interpret the data. After reading
the transcripts of focus groups and interviews one will begin to
see certain themes emerging. For example, one could find that
certain words or phrases that are utilised by certain members of
161
the community, such as young men or women, to describe the
practice. It is these aspects that one code in Nvivo.
Analysing or coding qualitative data is time consuming.
It should be done in pairs and coding frameworks should be
discussed with colleagues in order to avoid ‘misinterpretation’
of data. Coding frameworks will change as the project
progresses. It is advisable that you revisit full transcripts when
reviewing the coding frameworks. Nvivo is an excellent data
management tool but over reliance on it can result in the
‘wrong’ kind of analysis taking place. In order to achieve the
best outcome it is important that researchers combine the use of
Nvivo with manual analysis.
Managing the analysis with Nvivo as projects are mostly
collaborative, it is important that one manages the data analysis
in a thorough manner. In managing this aspect of the project,
one will avoid repetition, loss of data and improve the level of
analysis. Project partners should do the following:
a. There should be an allocated project manager for this
aspect of the project. This project manager will be
responsible for maintaining the Master Copy of the
Nvivo project and regularly backing up the project.
b. There should only be one Master Copy of the Nvivo
project. There should not be multiple copies of the
project as this will result in confusion.
c. If there is only one person working on the data analysis
per partner, it is still necessary to discuss your findings
with colleagues and community based researchers.
d. Project managers should implement an identification
system so that each coder’s activities can be identified.
This can be done in Nvivo.
e. Before coding, make sure you are working on the most
recent version of the project.
f. Save the project on a central system so that coders can
access the project. Liaise with one another so that you
are not working on the project at the same time without
each other’s knowledge.
162
g. Manage the amount of data that is analysed at any one
time. For example, work through one transcript at a
time.
h. As the project progresses, researchers should agree on a
coding structure. This can be documented by a
codebook. This will indicate all the descriptions of the
nodes developed. It is important that node descriptions
are agreed upon as this will provide rigour and avoid
‘misunderstandings’. Data analysis is time consuming. It
takes time to really immerse oneself in the data and to
get ‘a feel’ for the different themes or ideas that
participants are espousing. Therefore, time management
regarding this aspect of the project is vitally important.
We need to be proactive in terms of arranging internal
deadlines and organising regular meetings between
project partners.
Why Use Nvivo?
i. Analyze and organize unstructured text, audio, video or
image data.
ii. Playback ability for audio and video files, so that
interviews can easily be transcribed in Nvivo.
iii. Ability to capture social media data from Facebook,
Twitter and LinkedIn using the NCapture browser plug-
in.
iv. Import notes and captures from Evernote - great for field
research.
v. Import citations from EndNote, Mendeley, Zotero or
other bibliographic management software-great for the
literature reviews.
vi. User interface and text analysis available in English,
French, German, Spanish, Portuguese, Japanese and
Simplified Chinese.
Mendeley
Mendeley is designed to help you to achieve three main
goals: organizing your references, by allowing you to create a
163
personal library of materials and structuring it as you see fit. It
can help you keep track of different papers you are reading, by
adding notes and highlights, and by remembering where you
had reached. Mendeley allows you to come together with other
users to share references and to exchange ideas. You can use
private groups to share full-text papers and to collaboratively
annotate. You can use this functionality to work with people
you see every day or use Mendeley’s social features to find
people with similar interest from around the world. In addition
to helping you discover new people to work with, Mendeley can
also help you to find news research being published in your
field and to recommend new reading based on the contents of
your personal library.
It is a free referencing and academic social network
software. It allows you to collect, manage, store, share and use
research papers and articles, as well as generate bibliographies
in the citation style of your choice. It can be used with MS
Word to add citations as you type as well as compile a reference
list at the end of your assignment. It is useful for researchers
who manage a significant number of journal articles and
research papers in their studies but is not essential for smaller
assignments. Mendeley allows you to collect, manage, share
and use references you find in the course of your research. It
can be used with Word to add citations and produce a reference
list within a document. Mendeley has a web-based element that
can be used with any Internet browser; however you need to use
the desktop element to use the Citation Plugin with Word
(Haustein and Lariviere, 2014).
Mendeley is a free reference manager and academic
social network. It helps researchers to organize their materials,
to collaborate with others online, to discover the latest research
in their field and find career opportunities. Mendeley provides
an online account that allows a user to build a personal library
of references. References can be added to this library by using
papers in PDF format, by importing from online catalogs or by
manually adding the details of a reference. Users can easily
migrate their references to Mendeley from other reference
164
managers. By adding references, users are able to keep track of
their materials, to organize them as they see fit to read and
annotate PDF documents. The Mendeley Citation Plugin then
allows users to insert citations using references in their library,
setting them out according to specific style rules. Once a
manuscript has been completed, the Citation Plugin will also
generate a full bibliography at the click of a button.
In addition to reference management, Mendeley
provides features to allow researchers to collaborate together.
By creating and joining groups, users can share resources and
ideas with one another directly. Mendeley’s other social
features allow users to create a personal profile, connect with
other researchers and to discover important new work in their
field as well as understand the impact of publications.
How Do I Use It?
Mendeley can be used on your desktop, on the web, on
your phone or other device and as a Word plug in. It depends on
what your need it and how you plan to use it.
a. Web – The web version is great for storing, organising
and annotating full text PDFs within your own personal
library.
b. Desktop – The desk top version is essential if you plan
to use the bibliographical data to cite as you write or
create a bibliography.
c. App – The app version is perfect for accessing and
reading PDFs saved in your personal ‘library’ whilst on-
the-go.
d. Word plug-in - The word plug in allows you to
seamlessly cite as you write using the citation style of
your choice.
Layout
Broadly speaking, Mendeley Desktop offers a three-
column view. The left-most column allows ‘high level’
navigation, with a number of different view filters available
from the time of installation. Users can also create custom
165
filters for their documents ‘folders’, which will also be listed in
this column. The main column provides a list of references,
along with details of each entry. These details, such as a paper’s
title, author and year of publication are displayed in columns
within the main panel. When using a view filter selected in the
left-hand column (e.g. Recently Added), only the relevant
documents will be displayed in the main panel (Gunn, 2014).
The right-hand column displays all the details of the
currently selected reference. This column should be used to
ensure that a reference’s details have been entered correctly.
Clicking on a field allows existing details to be modified or
missing details to be added. There are several ways to get
references when using Mendeley but it’s also recommended that
users install the Mendeley Web Importer, which is covered
below.
The simplest way to add a file (such as a PDF of a
paper) to Mendeley is to drag and drop it into the main window.
This will cause Mendeley to automatically create a new entry
for the paper. When adding a PDF paper to Mendeley,
Mendeley will attempt to extract the metadata (such as Author,
Title, etc.) from the paper to use for the document details.
Although this is undertaken using sophisticated algorithms, the
sheer variety of formatting options for papers means that this
can never be 100% accurate. Always check the details of a
newly added paper to verify the details Mendeley finds.
a. Single files can also be added using the ‘Add Files’
command, found under the File menu. This will allow
you to browse your computer for a specific file and add
it to your library.
b. The entire contents of a folder (e.g. multiple PDFs
stored in the same location) can be added using the ‘Add
Folder’ found under the File menu.
c. You can opt to ‘Watch’ a folder using the ‘Watch
Folder’ command found under the File menu. This
allows you to specify a folder on your computer for
Mendeley to monitor. Whenever a new file is added to
166
this folder, it will be automatically imported into
Mendeley.
d. For references, other than PDF papers, it’s possible to
create a ‘metadata only’ entry in your library. This can
be useful for books and other non-digital (or non-text)
media. To create a manual entry, select the ‘Add Entry
Manually’ command, found under the File menu. This
opens a tool that allows you to specify the reference type
and to input the document details yourself.
Features
Francese (2012) established that Mendeley is a free,
web-based tool for organizing research citations and annotating
their accompanying PDF articles. It has the following features:
i. Cross Platform: Mendeley has the ability to install in
many operating system, like Windows, Linux, MacOS.
Now Mendeley is also available in mobile version
Android app and iPad app
ii. Storage: Mendeley can store up to 2GB freely available
to the user if user wish to extend the storage capacity by
upgraded with minimum cost.
iii. Drag and drop: this is adding feature of Mendeley you
can quickly add data with your existing library by drag
and drop and save them securely in to the Mendeley
desktop for future access.
iv. Web Importer: Mendeley helps to import documents
directly from the web and academic database to
Mendeley software. It is available in the important web
browser, such as Firefox, Chrome, Internet and Safari.
v. Import: Mendeley offer import record from many well-
known data base. User can easily export the
bibliographic data from web. It supports variety of
website, like Amazone, Bomed Central, ACMPortal,
BioOne, Cite SeerX, IEEE, CiteULike, Google Scholar,
Google Book Search and EBSCO, etc. User can also
import the data from EndNote, RIS, Zotero and Bibtex,
etc.
167
vi. Export: Mendeley can export different data formats
such as Bibtex, RIS, End note Xml VS, Xl or X2
vii. Word Processing: it has compatible plug-in with Ms-
Word, open Library and Libre Office. A user can easily
export full bibliography, cite the paper in a minute. This
feature is very much important for a researcher when he
or she is writing an academic paper.
viii. Reference style: Mendeley offers more than 6,000 styles
from all the top journals. It uses Citations style
language (CSL) and regularly fetches citations style
from citation style repository.
ix. Reading facilities: a researcher can store the research
papers, organise it, sort it, by title, year, author and date.
Researchers can read the PDF documents, highlight it,
tag it and save it for future reference. A researcher can
see the recent added documents, recently read document
in an easy way. A user can use keyword search from the
store data within the Mendeley desktop.
x. Full text searching: Mendeley facilitates full text
searching to the user. User can easily search a document
by keywords and the search will reflect in a second.
How Does Mendeley Help Your Research Work?
a. Social network: It has social networking features.
Mendeley allows a researcher to build his or her
research network with other researchers. He or she is
able to create an online account and create research
interest page and save it. The Mendeley automatically
suggest some papers, authors related to your research
area of interest. A researcher can create group, maintain
it and share it view on the old group list.
b. Create private group and public: the Mendeley has
power tool for a user to create private group and can
share the full text documents with limited people.
c. Readership statistics: Mendeley helps the researcher to
view the statistic of reading article and connect it and
168
also see the statistics of research publications. Statistics
will help you to meet new people.
d. Data sharing facilities: Mendeley helps the researcher to
put the research data online so that another researcher
can see and read and also cite your research work. It will
help to promote your own research work.
e. Careers: A user can search for job in the field of science
and technology jobson Mendeley. A research scholar
can search for job in various ways by choosing and
filtering the options, like discipline wise and location
base search. A user can set job alert service, see the job
vacancy by filtering options.
f. Web library: Mendeley helps the researcher to access
materials online through web browser; user can see the
data, add documents and manage it. But a user has to
synchronise regularly the Mendeley desktop. User can
access all the data through web browser.
g. Mendeley Web Catalog: Mendeley web Catalog allows a
user to search the data, which are added by other
Mendeley users and if the full text is available, users can
directly down load.
Therefore, Mendeley is reference manager or citation
software that allows a user to manage his or her research work
and also allows you to share the data worldwide. Mendeley
helps the user to build professional relationship to others.
Mendeley helps and guides you for your research work. It is of
the power reference toll among other citations management
software.
Chapter Summary
This Chapter presents the statistical application suitable
in the field of social science research. In this regards, statistics
is said to be a form of mathematical analysis that uses
quantified models, representations and synopses for a given set
of experimental data or real-life studies. The reason why
statistics is needed by students and researchers was established,
including how to handle un-grouped and grouped data. Other
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statistical procedures, like measurement of correlation, bar
chart, frequency polygon, ogive and pie chart also constitute
some of the issues highlighted. Apparently, some of the
software that facilitates data analysis in social research, like
Statistical Package for Social Science (SPSS), Atlas.ti, Nvivo
and Mendeley were examined.
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Chapter Seven
Perspectives on Validity, Reliability, Variables,
Scales and Measurement
Introduction
A research instrument depends largely on the
researcher’s ability to collect data and select the most
appropriate statistical methods to compute and remedy the
difficulties. To do this, the researcher needs dependable and
relevant knowledge about the topic chosen and the instrument to
be used. Valid and reliable information can help the researcher
to modify instrument to meet the challenges faced in the
research topic and it can also promote changes in the society,
based on empirical relationships, rather than subjectivity. Thus,
validity refers to the accuracy or truthfulness of a measurement.
Are we measuring what we think we are? There are no
statistical tests to measure validity. All assessments of validity
are subjective opinions, based on the judgement of the
researcher. Whenever a researcher wants to check whether the
study has achieved the purpose of conducting it or not, it is
done through validity. There are two major types of validity as
examined below:
(a) Internal validity: this deals with the control over
research conditions and it is necessary to enable researchers to
rule out all plausible of incorrect results. Researchers are
interested in verifying that “Y is a function of X2, or Y = f(x)
where B is an extraneous variable. Any such variable that create
a rival explanation of results are known as artifacts. The
presence of an artifact indicates a lack of internal validity. In
this instance, the study has failed to investigate its hypotheses.
Causes of Extraneous Variables
1. History: various events that occur during a study may
affect the subject attitudes, opinions and behaviours.
2. Maturation: subjects, biological, psychological
characteristics change during the course of a study and
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that may affect the outcome e.g. hunger, tiredness or
becoming older may influence your response in the
study.
3. Testing: this in itself may be an artifact, particularly
when subjects are given similar pre-test and post-test.
When people are aware that they are been observed,
they tend to give you what you want. For example, they
may likely tend to change their behaviour to suit their
interest.
4. Instrumental decay: all the methods may no longer be
visible. Equipments may fade out, observer may become
casual in recording their result. The interviewers
frequently asked questions not in the way they are. Any
material used in the course of research is an instrument
e.g. recording sheet, tape recorder, books, pen, etc.
Thus, if the instruments get spoilt or bad, it may affect
your studies and brings about extraneous or compound
variables.
5. Experimental mortality: falling out of the subjects that
are under study. Whatever happen to your subject at the
course of your research or study that makes them fall out
is surely going to have an effect on the outcome of your
study.
6. Sample selection: improper selection of sample is an
artifact. If two or more groups exist, there groups must
be randomly selected and tested for homogeneity to
ensure that results are not due to the type of sample
used. Others are demand characteristics, experimental
bias, evaluation apprehension, casual time order and
statistical regression.
(b) External Validity: this refers to how well the result of
the study can be generalised across population, settings and
times. The external validity of a study can be affected by the
interaction in analysis of variables such as subject selection,
instrumentation and experimental condition. A study that lacks
external validity cannot be applied to other situations; it can
only be valid for the sample used. Cook and Campbell (1979)
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identified three procedures that can be used to increase the
external validity of research study as follows:
i. Random sampling
ii. Heterogeneous samples that replicates the study
several times
iii. Select a sample that is representative of the
group which the result will be generalised.
Another way to increase external validity is to conduct
research over a long period of time. Unfortunately, studies like
mass media among others are often designed as short term
projects. Subjects are exposed to an experimental treatment and
are immediately tested or measured.
Methods of Measuring Validity
There are six methods of estimating validity of the
findings of a study:
1. Face Validity: face validity is the least statistical
estimate (validity overall is not as easily quantified as
reliability) as it is simply an assertion on the researcher’s
part claiming that they have reasonably measured what
they intended to measure, it is essentially a “take my
word for it” kind of validity. Usually, a researcher asks a
colleague or expert in the field to vouch for the items
measuring what they were intended to measure. Face
validity is the extent to which a test, data or instrument
or item appears relevant, important and interesting to a
researcher or examiner. Items can be included in test or
instruments that measure important content as judge by
the examiner. Face validity therefore, is referred to as
whether the test looks valid “on the face of it”, how
would people see it and appreciate its contents and
spread of the items or would they take the test to be
likely, to think the test is measuring what its author
claims? Thus, it refers to the likelihood that a question
will be misunderstood or misinterpreted. Pre-testing a
survey is a good way to increase the likelihood of face
validity.
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2. Content Validity: content validity goes back to the ideas
of conceptualisation and operationalisation. If the
researcher has focused in too closely on only one type or
narrow dimension of a construct or concept, then it is
conceivable that other indicators were overlooked. In
such a case, the study lacks content validity. Content
validity is making sure you have covered all the
conceptual space. There are different ways to estimate it,
but one of the most common is a reliability approach,
where you correlate scores on one domain or dimension
of a concept on your pre-test with scores on that domain
or dimension with the actual test. Another way is to
simply look over your inter-item correlations. Content
validity is the determination of whether students or
researchers have mastered, excelled in or failed items or
tests measuring specific objectives. The instruments in
the research have content validity if they meet the
required objectives. Content validity is the true
representation of sample from a given topic(s) and the
sampling adequacy of the content of the research
instrument from the topic. In a true sense, content
validity is determined through a thorough inspection of
the items and not through a numerical expression. It
refers to whether an instrument provides adequate
coverage of a topic. Export opinions, literature searches
and pre-test open-ended questions help to establish
content validity.
3. Criterion Validity: criterion validity is using some
standard or benchmark that is known to be a good
indicator. With criterion validity, you are concerned
with how well your items are determining your
dependent variable.
4. Construct Validity: construct validity is the extent to
which your items are tapping into the underlying theory
or model of behaviour. It is how well the items hang
together (convergent validity) or distinguish different
people on certain traits or behaviours (discriminant
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validity). It is the most difficult validity to achieve. You
have to either do years and years of research or find a
group of people to test what has the exact opposite traits
or behaviours you are interested in measuring. This may
be referred to as the logical validity and it is concerned
with the question of how well a test or instrument
conforms to the underlying psychological theory or
construct. Construct validity is the extent to which
measurement justify or support the existence of
psychological traits, abilities, attributes, motivation,
assertiveness, compulsiveness, etc.
5. Predictive Validity: it is the coefficients expressed in
correlation forms, which are affected by factors like
amount of time in the measurement of the predicator and
the number of items in the predicators. The success of
the People’s Democratic Party (PDP) in 2019 polls can
be predicated accurately from the score sheet or rating
obtained, based on the number of projects executed, then
the predicative validity of the instrument can be said to
be high.
6. Concurrent Validity: this refers to the ability of
instrument to determine the current status of a research
topic. It is concerned with happenings in the current
development. For instance, 2019 political situation in
Nigeria. A concurrent validity coefficient can be
determined when measurements of the researcher and
criterion test are obtained at about the same time.
Concurrent validity is how well something estimates the
actual day-by-day behaviour; predicative validity is how
something estimates some future event or manifestation
that has not happened. The latter type is commonly
found in criminology.
Reliability
The measurement of human behaviour belongs to the
widely accepted positivist view or empirical-analytic approach,
to discern reality (Smallbone and Quinton, 2004). Since most
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behavioural researches take place within this paradigm,
measurement instruments must be reliable.
The interpretation and analysis of the articles is
interpretation. However, the interpretation is grounded in the
literature review. Weber (1990) remarked that to make valid
inferences from the text, it is important that the classification
procedure is reliable in the sense of being consistent. According
to Padget (1998) it is always necessary to judge the soundness
of the research to identify if its findings are authentic and its
interpretations credible. Reliability is the extent to which
measurements are repeatable, when different persons perform
the measurements, on different occasions, under different
conditions, with supposedly alternative instruments, which
measure the same thing.
It is important to recognise that a methodology is always
employed in the service of a research question. As such,
validation of the inferences made on the basis of data from one
analytic approach demands the use of multiple sources of
information (Nunnally, 1978). Measurements that are reliable to
the extent that they are repeatable and that any random
influence which tends to make measurements different from
occasion to occasion or circumstance to circumstance is a
source of measurement error (Gay, 1987). Reliability is the
degree to which a test consistently measures whatever it
measures.
Method of Measuring Reliability
There are four good methods of measuring reliability;
namely:
i. Test-retest.
ii. Multiple forms.
iii. Inter-rater.
iv. Split-half.
Test-Retest: the test-retest technique is to administer
your test, instrument, survey or measure to the same group of
people at different points in time. Most researchers administer
what is called a pre-test for this and to troubleshoot bugs at the
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same time. All reliability estimates are usually in the form of a
correlation coefficient, so, here, all you do is calculate the
correlation coefficient between the two scores on the same
group and report it as your reliability coefficient.
Multiple Forms: the multiple forms technique has other
names, such as parallel forms and disguised test-retest but it is
simply the scrambling or mixing up of questions on your survey
and giving it to the same group twice. The idea is that it is a
more rigorous test of reliability.
Inter-Rater: it is most appropriate when you use
assistants to do interviewing or content analysis for you. To
calculate this kind of reliability, all you do is report the
percentage of agreement on the same subject between your
raters.
Split-Half: here, reliability is estimated by taking half of
your test, instrument or survey and analysing that half as if it
were the whole thing. Then, you compare the results of this
analysis with your overall analysis. There are different
variations of this analysis with your overall analysis. There are
different variations of this technique, one of the most common
being called Cronbach’s alpha (a frequently reported reliability
statistic), which correlates performance on each item with
overall score. Another technique, closer to the split-half method,
is the Kuder-Richardson coefficient or KR-20. Statistical
packages on most computers will calculate these for you,
although in graduate school, you will have to do them by hand
and understand that all test statistics are derived from the
formula that all observed scores consist of a true score and error
score.
Variables
Variables refer to as anything of interest to a researcher.
Kerlinger (1973, p. 29) describe a variable as a property that
takes on different values. Kerlinger puts it succinctly when he
said that a variable is something that can change. A variable is
any phenomenon, fact, value or observation, which is capable of
being changed or inducing a change in another entity. This
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means that the variable can be tangible object, an abstract,
symbol or social phenomenon. Its basic feature is its
susceptibility to change; meaning that the variable can change,
depending on the situation.
Looking at the above definitions, it becomes important
that a variable is anything that can vary. The variable can be
age, sex, nation, gender, weight, well-being, social situation,
etc. Variables are useful in research because, hypothesis uses
variables to make predictions. They help or guide the researcher
in designing his research questions. Variables can be used to
guide the researcher when determining the sample size.
Researchers attempt to test a number of associated variables to
develop an underlying meaning. For example, the variable
“gender” consists of two test values: “male” and “female” (M or
F). We can, if it is useful, assign quantitative values instead or
(or in place of) the text values but we do not have to assign
numbers in order for something to be a variable. It is also
important to note that variables are only things that we measure
in the traditional sense.
Types of Variables
1. Independent variable.
2. Dependent variable.
3. Discrete variable.
4. Continuous variable.
5. Intervening variable.
Independent Variable: these are variables that can stand
on their own without depending on other variable; rather, it
influences other variables. An independent variable is the
presumed cause of the dependent variable. In experiments, the
independent variable is the variable manipulated by the
experimenter. Independent variables are variables that can stand
on their own in a cause and effect relationship. They are
therefore, the cause of a relationship. That is, there can be no
relationship without the independent variable. Kerlinger (1973)
describes an independent variable as the presumed cause of the
dependent variable, which is the presume effect.
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Dependent Variable: are those variables that cannot
stand on their own rather it depends on other variables to
survive. The dependent variable is the presumed effect, which
varies concomitantly with changes or variation in the
independent variable. They are variables that relay on the
existence of the independent variables. They are dependent on
the independent variables. The dependent variables are the
variable whose activities are presumed to be the consequence of
independent variables.
Discrete Variable: these are variables that do not
change. For instance, if you are a female you will continue to be
so also if you are male. A discrete variable includes only a finite
set of values; it cannot be divided into subparts.
Continuous Variable: these are variables that continue to
change from time to time. For example, age. A continuous
variable can take on any value, including fractions and can be
meaningfully broken into smaller subsections. Height is a
continuous variable. If the measurement tool is sophisticated
enough, it is possible to distinguish between one person that is
72.113 inches tall and another 72.114 inches tall. Time spent
watching television is another example.
Intervening Variable: any variable that does not play
any significant role in the research is refers to as intervening
variable. These unwanted or uninvited variables have no place
in the research work. The intervening variable is the one that
lies between two other variables, usually between the
independent and dependent variables. Kerlinger (1973)
describes intervening variable as a term used to account for
internal and directly unobservable psychological processes,
which account for behaviour. For example, love, emotion,
interest, etc. They are the variables that mediate the independent
variables’ prediction of the dependent variable.
Scales
Scale is the measurement of the intensity of an attitude
or emotion. Specifically, scales exist in the ordinal level of data.
Usually, scales are constructed, using the ordinal level of
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measurement, which organises items in an order, in order to
determine degrees of favour or disfavour, but does not provide a
meaning of distance between degrees. According to Asemah et
al., (2012) they are composite, multiple measures about a
particular aspect of a theoretical concept. Scales are generally
used with complex variables that do not easily lend themselves
to single item or single indicator measurement. Scales are used
to measure theoretical concerns, which are generally measures
of independent variables.
Types of Scale
a. Likert Scale:
According to Wimmer and Dominick (2014) Likert-
Scale or summated rating is the most popularly used
questioning technique. Furthermore, Bhattacherjee (2012, p.47)
added that “Likert-scale is a very popular rating scale for
measuring ordinal data in social science research”. A Likert
scale is a psychometric scale commonly used in questionnaires
and it is the most widely used scale in survey research, such that
the term is often used interchangeably with rating scale, even
though the two are not synonymous. When responding to a
Likert questionnaire item, respondents specify their level of
agreement or disagreement on a symmetric agrees or disagree
scale for a series of statements. Thus, the scale captures the
intensity of their feelings. Often, five ordered response levels
are used. This was developed by Rensis Likert in 1932. It
requires the individual to make a decision on their level of
agreement, generally on a five-point scale (Strongly Agree,
Agree, Undecided, Disagree, Strongly Disagree) with a
statement. The number beside each response becomes the value
for that response and the total score is obtained by adding the
values for each response, hence, the reason why they are also
called summated scale (the respondent’s score is found by
summing the number of responses).
Likert scale lends itself to a straightforward method of
scale construction. It has five response category scores of one to
five, which may be assigned according to the level of the
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respondent’s feeling towards the item in question. Each
subject’s responses are added to produce a single score on the
topic. In addition to the fact that Likert scale lends itself to a
straightforward measurement of attitude and strength of the
scale in discriminating reliable range of responses typically
offered on the scale.
Things to Consider When Using the Likert Scale
Asemah et al., (2012, p. 214) established them as
follows:
1. Get your data ready for analysis by coding the
responses. For example, you have a survey that asks
respondents whether they agree or disagree with a set of
positions in a political party’s platform. Each position is
one survey question and the scale uses the following
responses: strongly agree, agree, neutral, disagree and
strongly disagree. In this example, one will code the
responses accordingly: strongly disagree = 1, disagree =
2, neutral = 3 agree = 4, strongly agree = 5.
2. Remember to differentiate between ordinal and interval
data, as the two types require different analytical
approaches. If the data are ordinal, one can say that one
scale is higher than another. One cannot say how much
higher, as one can with interval data, which tells you the
distance between two points.
3. Begin to analyse your Likert scale data with descriptive
statistics. Although, it may be tempting, resist the urge
to take the numeric responses and compute a means.
Adding a response of “strongly agree” (5) to two
responses “disagree” (2) would give us a means of 4, but
what is the significance of that number? Fortunately,
there are other measures of central tendency one can use
besides the mean.
4. Proceed next to inferential techniques, which test
hypotheses posed by researchers. There are many
approaches available and the best one depends on the
nature of your study and the questions you are trying to
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answer. A popular approach is to analyse responses,
using analysis of variance techniques, such as the Mann
Whitney or Kruskal Wallis test, etc.
5. Simplify your survey data further by combining the five
response categories (e.g., strongly agree, agree, disagree
and strongly disagree) into two nominal categories, such
as agree or disagree, accept or reject, etc). This offers
other analysis possibilities. The chi-square test is one
approach for analysing the data in this way. This is the
best basic procedures for developing a Likert Scale:
i. The compilation of a large number of statements that
relate to a specific dimension. Some statements are
positively worded while some are negatively worded;
ii. Administer the scale to a randomly selected sample
respondents;
iii. Code the responses consistently, so that high scores
indicate stronger agreement with the attitude in question;
iv. Analyse the responses and select for the final scale,
those statements that most clearly differentiate the
highest from the lowest.
b. Guttman Scaling:
Guttman scaling was developed by Louis Guttman in
1944. It allows progressive investigation in the nature of
interview probing, such that you can find out to what degree
respondents agree with a concept or principle. The group of
questions seeks to investigate just one factor or trait. Guttman
scaling is also known as cumulative scaling or scalogram
analysis. Guttman scaling, like the Thurstone scale, recognises
that different questions provide different intensities of
indication of preferences. It is based on the assumption that the
agreement with the strongest indicators also signifies agreement
with weaker indicators.
It uses a simple “agree” or “disagree” scale, without any
variation in the intensities of preference. In statistical surveys
conducted by means of structured interview or questionnaire, a
subset of the survey items having binary (e.g. Yes or No)
answers forms a Guttman scale. If they can be ranked in some
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order so that, for a rational respondent, the response pattern can
be captured by a single index on that ordered scale.
c. Thurstone Scale:
Thurstone scaling was developed by Louis Leon
Thurstone in 1928. It is a format that seeks to use respondents,
both to answer survey questions and to determine the
importance of the questions. One group of respondents, a group
of “judges”, assigns various weights to different variables,
while another group actually answers the questions on the
survey. In psychology, the Thurstone scale was the first formal
technique for measuring an attitude. It was developed by Louis
Leon Thurstone as a means of measuring attitudes towards
religion. This technique for developing an attitude scale
compensates for the limitation of the Likert scale. That is the
strength of the individual item is taken into account in
computing the attitude score. It also can accommodate neutral
statements. Thurstone scaling is also called Equal-Appearing
Interval Scaling.
d. Semantic Differential Scale:
Osgood, Suci and Tennenbanum were the originator of
this scale in 1957. The semantic differential scale is similar to
Likert scaling; however, rather than allowing varying degrees of
responses, it asks the respondent to rate something in terms of
only two completely opposite adjectives. This question type
does not label each rating point with an individual descriptive
like a Likert Scale. Instead, it places one statement on the far
left of the scale and the opposite of that statement on the far
right. It uses a numbering system within the scale and the
respondent is asked to pick the number on the scale where they
fall between the two statements. Thus, a semantic differential
scale is a list of opposite adjectives.
Measurement
Measurement is a way of giving an activity a precise
dimension, by comparism to some standards. This is usually
done in a numerical or quantifiable manner. Put more
succinctly, measurement may be described as the process of
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determining dimensions, values or degrees. This measurement
may involve person’s height, behaviour, character, weight,
riches, etc.
What Do Communication Researchers Measure?
In social science research; (communication research
inclusive) scholars are very interested in identifying and
defining concepts, variables and constructs. After this has been
done, researchers have the responsibility of measuring these
research elements in real life. For instance, the concept,
“newspaper readership” could severally be measured in the
following ways:
1. Yes or no response (to find out whether respondents
read newspapers).
2. Number of items a week or month a respondent reads
newspaper.
3. The number of minutes or hours the respondents spends
reading newspapers, etc.
These are all different measures of a particular concept,
“newspaper readership”. Some researchers may prefer a single
measure while others prefer multiple measures. It all depends
on the researcher’s needs, predispositions and the theoretical
framework guiding the problem being investigated.
Levels of Measurement
Basically, there are four (4) levels of measurement in
research; they are:
i. Nominal measurement.
ii. Ordinal measurement.
iii. Interval measurement.
iv. Ratio measurement.
Nominal Measurement: this is the level of measurement
that describes variables that are categorical in nature. The
characteristics of the data you are collecting fall into distinct
categories. If there are a limited number of distinct categories
(usually only two), then you are dealing with a continuous
variable. The lowest level of measurement is the nominal scale,
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also referred to as the classificatory scale. This scale consists of
mutually exclusive categories, meaning that once something is
placed in one category, it cannot be put into any other category.
Ordinal Measurement: here, variables are ordered or
ranked in some order of importance. It describes most
judgments about things, such as big or small, strong or weak.
Most opinion and attitude scales or indexes in the social
sciences are ordinal nature. Ordinal scales have all of the
requirements of nominal scales, but also include the property of
order. If the categories of a scale are ordered, they constitute an
ordinal scale. For categories that use number, the numbers must
correspond to the order of the categories.
Interval Measurement: this describes variable that may
have more or less equal intervals or meaningful distances
between their ranks, for instance, if you were to ask somebody
if they were first, second or third generation immigrant, the
assumption is that the distance or number criminal justice are at
interval level measures, as is any kind of rate. An interval scale
has a constant unit that makes the distance between values
meaningful. The interval or distances between any two adjacent
units on the scale are assumed to be equal to the interval
between any other two adjacent units on the same scale. This
scale has no fixed zero that represents a zero quantity of the
dimension of interest.
Ratio Measurement: in radio level of measurement,
variables that have equal intervals and a fixed zero (or
reference) point are described. It is possible to have zero
income, zero education and no involvement in crime but rarely
do we see ratio level variables in social science, since it is
almost impossible to have zero attitudes on things, although
“not at all”, “often” and “twice as often” might qualify as radio
level measurement. Advanced statistics require at least, interval
level measurement, so the researcher always strives for this
level, accepting ordinal level, (which is the most common) only
when they have to.
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Error in Measurement
Most scientific, measurements do have errors if not all.
Knowing the error of measurement is important in determining
the meaning of a change and is important to determine
measurement precision. The overall degree to which
measurement in a sample represents the phenomenon or event
of interest in the population is a function of two sources of
errors: sampling error and measurement error. Both of these
errors have random (wrong result due to chance) and systematic
(wrong result due to bias) components.
Chapter Summary
In the nutshell, whenever a researcher wants to check
whether the study has achieved the purpose of conducting it or
not, it is done through validity. Similarly, anything that is of
interest to the research is regards as a variable. In this
perspective, the typologies of variables were highlighted and
they include: independent variable, dependent variable, discrete
variable, continuous variable and intervening variable. The need
to understand validity, reliability, variables, scales and
measurement was also apt. The four levels of measurement
ranging from nominal, ordinal, interval and ratio were
examined. These constitute a hierarchy where the lowest scale
of measurement, nominal, has far fewer mathematical properties
than those lined up in this hierarchy of scales. Nominal scales
yield data on categories; ordinal scales give sequences; interval
scales begin to reveal the magnitude between point on the scale
and ratio scales explain both order and the absolute distance
between any two points on the scale.
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Chapter Eight
The Pilot Study
Introduction
A pilot study is a standard scientific tool for “soft”
research, allowing scientists to conduct a preliminary analysis
before committing a full-blown study or experiment. The term
pilot study is used in two different ways in social science
research. It can refer to feasibility studies which are (small scale
version(s) or trial run(s), done in preparation for the major
study). However, a pilot study can also be the pre-testing or
‘trying out’ of a particular research instrument (Baker 1994, p.
182). One of the advantages of conducting a pilot study is that it
might give advance warning about where the main research
project could fail, where research protocols may not be
followed or whether proposed methods or instruments are
inappropriate or too complicated.
Rationale for Conducting Pilot Studies
1. Developing and testing adequacy of research
instruments.
2. Assessing the feasibility of a (full-scale) study or
survey.
3. Designing a research protocol.
4. Assessing whether the research protocol is realistic and
workable.
5. Establishing whether the sampling frame and technique
are effective.
6. Assessing the likely success of proposed recruitment
approaches.
7. Identifying logistical problems, which might occur,
using proposed methods.
8. Estimating variability in outcomes to help determine
sample size.
9. Collecting preliminary data.
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10. Determining what resources (finance, staff) are needed
for a planned study.
11. Assessing the proposed data analysis techniques to
uncover potential problems.
12. Developing a research question and research plan.
13. Training a researcher in as many elements of the
research process as possible.
14. Convincing funding bodies that the research team is
competent and knowledgeable.
15. Convincing funding bodies that the main study is
feasible and worth funding.
16. Convincing other stakeholders that the main study is
worth supporting.
Pilot studies can be based on quantitative or qualitative
methods and large-scale studies might employ a number of pilot
studies before the main survey is conducted. Thus, researchers
may start with “qualitative data collection and analysis on a
relatively unexplored topic, using the results to design a
subsequent quantitative phase of the study” (Tashakkori and
Teddlie 1998, p. 47). The first phase of a pilot might involve
using in-depth interviews or focus groups to establish the issues
to be addressed in a large-scale questionnaire survey. Next the
questionnaire, e.g. the wording and the order of the questions or
the range of answers on multiple-choice questions, might be
piloted. A final pilot could be conducted to test the research
process.
Problems of Pilot Studies
It should be recognised that pilot studies may also have
a number of limitations. These include the possibility of making
inaccurate predictions or assumptions on the basis of pilot data,
problems arising from contamination and problems related to
funding. These issues are now discussed below:
Completing a pilot study successfully is not a guarantee
of the success of the full-scale of the study. Although pilot
study findings may offer some indication of the likely size of
the response rate in the main survey, they cannot guarantee this
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because they do not have a statistical foundation and are nearly
always based on small numbers. Furthermore, other problems or
headaches may not become obvious until the larger scale study
is conducted.
A further concern is that of contamination. This may
arise in two ways:
1. Where data from the pilot study are included in the main
results, and
2. Where pilot participants are included in the main study
but new data are collected from these people.
Social scientists engaged in predominantly quantitative
research are likely to argue that: “an essential feature of a pilot
study is that the data are not used to test a hypothesis or
included with data from the actual study when the results are
reported” (Peat, 2002, p. 57). The obvious concern is that if
there were problems with the research tool and modifications
had to be made in the light of the findings from the pilot study,
data could be flawed or inaccurate. However, where an
established and validated tool is being used and the pilot study
is determining other methodological aspects such as recruitment
rates, it could be argued that such data may be of value.
A more common problem is deciding whether to include
pilot study participants or site(s) in the main study. Here the
concern is that they have already been exposed to an
intervention and, therefore, may respond differently from those
who have not previously experienced it. This may be positive,
for example the participants may become more adept at using a
new tool or procedure. However it may also be negative with
participants showing a decline in following a protocol because it
is no longer novel. Indeed both changes in behaviour have long
been recognised and a ‘run in’ period, where an intervention is
introduced prior to a study, is often used for these reasons. The
concern about including participants from the pilot study in the
main study arises because only those involved in the pilot and
not the whole group will have had the experience. In some cases
however it is simply not possible to exclude these pilot-study
participants because to do so would result in too small a sample
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in the main study. This problem arises in particular where the
samples are clusters, for example schools, prisons or hospitals.
In such cases one can conduct a sensitivity analysis (or sub-
group analysis) to assess to what extent the process of piloting
influences the size of the intervention effect.
Contamination is less of a concern in qualitative
research, where researchers often use some or all of their pilot
data as part of the main study. Qualitative data collection and
analysis is often progressive, in that a second or subsequent
interview in a series should be ‘better’ than the previous one as
the interviewer may have gained insights from previous
interviews, which are used to improve interview schedules and
specific questions. Some have therefore argued that in
qualitative approaches separate pilot studies are not necessary
(e.g. Holloway, 1997, p. 121). For example, a qualitative
interviewer conducting 12 focus group interviews will listen to
the recordings or read through the transcripts of the first three or
four in order to improve the questions, the way of introducing
the issues into the group interview or even to add new topics.
Thus, although there is no specific pilot study, analysis of the
earlier focus groups may help improve the later ones. However,
Frankland and Bloor (1999, p. 154) argue that piloting provides
the qualitative researcher with a “clear definition of the focus of
the study”, which in turn helps the researcher to concentrate
data collection on a narrow spectrum of projected analytical
topics. Piloting of qualitative approaches can also be carried out
if “the researcher lacks confidence or is a novice, particularly
when using the interview technique” (Holloway, 1997, p. 121).
Problems may also arise where a pilot study requires a
significant investment of resources, making it difficult for the
study team to call a halt to the research after an unsuccessful
pilot study. Researchers might be tempted to make considerable
changes in the main study, rather than deciding that the
proposed study is not possible with the available resources,
time, population, etc. In contrast, funding bodies may be
reluctant to fund a further study if the pilot has been substantial
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as they may view the research as no longer original, especially
if results from the pilot study are published.
Piloting Questionnaire
Before you deliver any questionnaire, you should pilot it
to check that it is going to function effectively. There are a
number of reasons why it is important to pilot a questionnaire:
1. To test how long it takes to complete.
2. To check that the questions are not ambiguous.
3. To check that the instructions are clear.
4. To allow you to eliminate questions that does not yield
relevant data.
How to Write and Analyse a Questionnaire
Questionnaires can be used in a wide range of settings to
gather information about the opinions and behaviours of the
audiences. Questionnaire surveys are particularly reliant on the
willingness of the subjects to take part. Considerable effort is
therefore required from the onset to ensure that the
questionnaire is acceptable to the target population to maximise
response rates. Asemah et al., (2012) established them as
follows:
a. Define Research Questions and Study Population: it is
important to define your research question, study
population and the objectives of your study at the
beginning of your study. You should continually refer
back to these during the study design process. This is
particularly important in questionnaire studies, where
there is a temptation to be “nosey” and delve into a wide
range of issues, which although, interesting to you, the
research questions are not relevant to your study. You
should also consider the associations that you wish to
test at the design stage, so that the relevant data, for
example, social class indicators, can be collected as part
of your questionnaire.
b. Decide how the Questionnaire will be Administered:
questionnaires can be used either as the basis of a
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structured interview, which is administered by a trained
interviewer or completed by the subject by themselves.
When you decide how a questionnaire should be
administered, you need to achieve a balance between
practical considerations, such as the time-frame and
funding available for the study and the issues you wish
to examine. Structured interviews can be undertaken
face-to-face or may be conducted over the telephone or
the Internet. Interviewer-administered questionnaires
have the advantage that unclear questions can be
clarified to the respondents and open-ended questions
can be used to collect a range of possible responses.
c. Formulate Your Questions: once you have decided how
you are going to administer your questionnaire, you can
go on to formulate your questions. Questions can be
divided into those directly related to the research
questions, filler questions that explore the characteristics
of the different study groups “filler” questions that,
although, not part of the research question, aid the flow
of the questionnaire. Wherever possible, you should
incorporate questions from existing questionnaires (with
the permission of the author).
d. Formulate Your Responses: questions can be divided
into open-ended questions, where the subjects are free to
give their own responses to a question or closed
questions, where a choice of predetermined answers is
given.
e. Design the Layout: the layout of your questionnaire is
important not only for ensuring that all the questions are
answered but also, facilitating data coding and analysis.
It is important that you capture people’s attention and
make them pick interest in completing the questionnaire.
It is also a good idea to use at least, a size 14 font size
for the questions and to avoid piling too many questions
into a page in an effort to save paper.
f. Pre-pilot the Questions and Lay Out: it is essential that
you pre-pilot your questionnaire to identify any
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ambiguities in your questions and to identify the range
of possible responses for each question. You should sit
down with a few suitable subjects, who may be friends
or colleagues and go through the questions together to
identify potential problems. After each session, you
should amend the questionnaire before re-piloting with
another group of testers. This process needs to continue
until you are confident that your questions are
unambiguous, appropriate and acceptable to
respondents.
g. Pilot Your Study: as with other forms of science, you
need to be able to show that the data collected from your
questionnaire are valid and reliable. Ideally, every
questionnaire should undergo a formal pilot during,
which the acceptability, validity and reliability of the
measure is tested. You should also pilot the data
collection process and covering letters to participants.
The pilot should be based on subjects from a similar
population to that being examined in your survey. Since
people will be involved, you will need to obtain ethical
approval for this part of your study.
h. Design Your Coding Scheme: coding is the process of
converting questionnaire data into meaningful categories
to facilitate analysis. You need to think about your
coding scheme at the beginning of your study and
wherever possible, build it into your questionnaire. For
instance, by numbering the response, tick boxes for each
question. This will allow you to enter data directly from
the questionnaire into your database, for analysis. The
numbers within the boxes should correspond to the
variables in the database where the responses will be
stored. The alternative is to code the questionnaire
responses unto a separate coding sheet and then to enter
the data from the coding sheet into the database. The
process is not only laborious, but also doubles the
margin for error and observer’s bias. It is a good idea to
test your coding scheme and data entry process during
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the pilot study, so that problems can be rectified before
the main study starts.
Chapter Summary
Pilot study is one of the essential stages in a research
project and is conducted to identify potential problem areas and
deficiencies in the research instruments and protocol prior to
implementation during the full study. Reports of pilot studies
are rare in the research literature. When reported, they often
only justify the research methods or particular research tools
used. Too often, research papers only refer to one element of the
pilot study, for example, to the pre-testing or pilot testing of a
questionnaire. The chapter also discussed pilot study and
rationale for conducting pilot studies, problems of pilot studies,
steps on how to write and analyse a questionnaire. Thus, some
of these processes and outcomes from both successful and failed
pilot studies might be very useful to others embarking on
projects, using similar methods and instruments.
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Part Three
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Chapter Nine
Research Proposal Writing
Introduction
It is imperative to consider early in planning the study,
the major points that need to be addressed in a proposal. These
points or topics need to be interconnected to provide a cohesive
picture of the entire project. For me, these topics seem to span
all proposals, whether the project is qualitative, quantitative or
mixed methods. Therefore, research proposal is a
comprehensive blueprint of your study. If the blueprints are
clear and well done, the work can proceed with assurance; if
incomplete and unclear, there is likely to be considerable
misdirected effort. Apparently, every research exercise begins
with a proposal. The proposal is an elaborate description of how
to carry out a research exercise; it is a description of a student’s
research plan, which will be conducted later. The proposal is a
plan of action that is strategically designed to explain how to
investigate a subject matter; it opens an insight into what the
researcher intends to do. The researcher must know what the
problem is, how to solve it, the research instruments to use, etc.
Writing the proposal entails the construction of all the elements
that would determine the relevance in the course of study.
Therefore, students are expected to conceptualise the
topic they want to write about. The essence is for students to
convince their supervisors that they know what they are going
to do in the course of the study. Note that your supervisor is not
there to help you write the project or the research work. His
duty is to guide you on how to go about it. As such, students are
expected to choose an area of their interest with a time span that
they can be able to handle. The proposal is like a research report
but it is written before the research project begins, it describes
the research problem and its importance and gives a detailed
account for the methods that will be used and why they are
appropriate.
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What Does Proposal Do?
According to Jibril (2019) a good research proposal
should be able to accomplish the following:
a. It provides a detailed and clear outline of a research
project following a clear structure and a style approved
by the senate of an institution.
b. It should be able to explain the major area(s) where the
research is located.
c. It should also be able to identify the research problem
under investigation.
d. It should be able to state the purpose of the research.
e. It must also provide an insight about the research.
f. It should explain and justify the most appropriate
methodology adopted.
g. It should explain the limitations.
h. It must explain briefly the significant prior research and
accurate literature that exist in the study.
i. It must also explain the report and its potential
contribution to the body of knowledge.
Common Mistakes in Proposal Writing
Asemah et al., (2012) established some of the common
mistake in writing proposal as follows:
1. Failure to provide the proper context to frame the
research question.
2. Failure to delimit the boundary conditions for your
research.
3. Failure to cite landmark studies.
4. Failure to accurately present the theoretical and
empirical contributions by other researchers.
5. Failure to stay focused on the research question.
6. Failure to develop a coherent and persuasive argument
for the proposed research.
7. Too much detail on minor issues, but not enough detail
on major issues.
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8. Too much rambling, going “all over the map” without
clear sense of direction (the best proposals move
forward with ease and grace like a seamless river).
9. Too many citation lapses and incorrect references.
10. Too long or too short proposal.
11. Failing to follow the APA style.
12. Slop writing.
Proposal Format
There is no straight-jacketed way of writing the research
proposal, as different scholars have adopted different techniques
of writing the research proposal. Normally, when your proposal
is well-written, you have automatically taken care of your
chapters’ one, two and three. That is why it is always advisable
for researchers (project students) to pay adequate attention to
their research proposal (Asemah et al., 2012). Students should
make sure that their research proposals are comprehensive and
well written.
It is imperative to note that the research proposal is
written in simple present tense or future tense. For example,
“the researcher will use content analysis method or the
researcher uses content analysis method” and not the researcher
used content analysis method. This is because; the work has not
been approved. But, when is has been approved and it is ready
for report, it becomes, “the researcher used content analysis
method”. It becomes past tense because the research has been
conducted and it has been approved thus, most research studies
begin with a written proposal. Again, nearly all proposals
follow the same format. In writing the research proposal, the
researcher must avoid the use of first person pronouns; referring
to yourself or the research team in the third person. Instead of
saying, “I will or we will…” say the researcher will or the study
will use content analysis. You can also use passive voice rather
than active voice in your research proposal.
The researcher must first of all know what he wants to
investigate before he will start putting pen on paper. Ideally, a
topic should not be imposed on a student but he should select a
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topic of his choice and which is interesting, current and
significant. Remember that any research undertaken should be
able to contribute to the body of knowledge and most at times,
looking at current issues will help you to achieve that.
Conducting research in areas where enough have been done by
other researchers is not apparent as, such findings tend to be
somewhat similar with what others scholars or researchers have
already established in the literature.
Elements of Research Proposal
In order to achieve the essence of research proposal, the
following elements are considered:
1- Topic
2- Background to the study
3- Problem statement
4- Aim or purpose of the study
5- Objectives of the study
6- Research questions or hypothesis
7- Significance of the study
8- Scope of the study
9- Limitations to the study
10- Operational definition of terms or concepts
11- Organisation of the study
12- Brief literature review
13- Brief methodology
14- References
Students or researchers should understand that the
proceeding elements are distinctive elements that make up a
comprehensive research proposal. Thus, such elements should
be treated separately and independently. For example, it is not
apparent to join “aim and objective” or “scope and limitations”
together. These are two distinctive elements and should be
treated as such.
(1). The Topic or the Title:
This is the starting point of your journey. The topic has
to be boldly stated in the proposal and it must be relevant and
researchable. Selecting a research topic is a difficult task to
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many students who carry out research, because for a student to
come up with a relevant topic, he or she needs to brainstorm and
digest several ideas and issues before selecting the one that is
relevant to the discipline he is acquainted with. However,
selecting a research topic is a concern for many beginners,
especially those writing term papers, project, dissertations and
thesis. The problem is to know where to start. Fortunately, there
are virtually unlimited sources available in searching for a
research topic. Few available are:
a. Academic Journals: journals are excellent sources of
topic derivation. Although, academic journals tend to
publish research that is 12 to 24 months old, the articles
may provide ideas for research topic. Most authors
conclude their research by discussing problems
encountered during the study and suggesting topics that
need further investigation.
b. Magazines and Periodicals: magazines, newspapers,
periodicals are good sources of topic derivation.
Looking into them will help in locating problem to
research. Meanwhile, many educators feel that
publication other than professional journals contain only
“watered down” articles written for the general public.
To some extent it is true but these articles tend to
eliminate the tedious technical jargons and are often
good sources for problems and hypotheses. In addition,
more and more articles written by highly trained
professionals are appearing in weekly and monthly
publications such as Daily Trust, Weekly Trust, The
Nation, Vanguard, The Punch, to mention a few.
c. Research Summaries or Abstract: research summaries or
abstract are good sources of research topics.
Professional research organisations regularly publish
summaries that provide close look at the major areas of
research in various fields. These summaries are often
useful for obtaining information about research topics.
Since they survey a wide variety of studies.
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d. Everyday Situations: daily contacts with people in all
spheres of life in the society are good source of topic.
Because, each day people are confronted with various
types of communication via broadcasting and print,
interpersonal communication, public relations
campaigns etc. These confrontations can be excellent
sources of research topics for the researchers who take
an active role in analyzing them. What types of
messages are produced? What effects are expected from
the various types of communication? These and other
questions may help develop a research idea. Significant
studies based on questions arising from everyday
encounters with the media and other forms of
communication have covered investigation of television
violence, layout of newspaper advertisements, advisory
warnings on television programmes and approaches to
public relations campaigns.
e. Data Achieves: libraries and special libraries for special
information on specific usages where information is
stored could be good sources of research topic e.g.
Arewa House, Mumbayya House, Saadu Zungur
Monumental and others are valuable sources for
researchers. These achieves act as storage facilities
where data are deposited for other investigators who
want to conduct further research to ask different
questions. This process is known as secondary analysis
which has become a major research approach, because
of the time and resource savings it offers.
Secondary analysis provides an opportunity for
researchers to evaluate otherwise unavailable data.
Backer (1981) the use of social science data after they
have been put aside by the researcher who gathered
them, they are used for data that can be original or
someone uninvolved in any way in the initial research
project. The research questions examined in the
secondary analysis can be related to the original research
endeavour or quite distinct from it.
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f. Internet: the most recent and reliable in searching of
topic is the internet. It provides so many researches and
other related papers that one can easily originate a
research topic from it.
Determination of the Topic Relevance
Once a research topic is been selected, the next thing to
do is to determine whether the topic is researchable or has
merit. In getting a viable topic, eight (8) questions are needed to
be answered as established by Wimmer and Dominick (2011) as
follows:
a) Is the topic too narrow or broad? Significantly, most
studies concentrate on one small area of field; few
researchers attempt to analyze an entire filed in one
study. It is very important for a researcher to look at the
topic critically and examine the horizon where the
research will cover. Whenever the researcher finds out
that the topic is too broad, it is needed to be modified to
the level in which it can be concluded based on the
stipulated time.
On the other hand, when the researcher finds out that the
topic is too narrow, the researcher needs to widen his or
her horizon in other to be able to achieve the element of
generality and avoid the problem of internal validity.
b) Can the problem really be investigated? Taking the issue
of broadness aside, a topic might prove unsuitable for
investigation simply because the question being asked
has no answer or at least cannot be answered with the
facilities and information at hand.
Another point to take into cognizance is the issue of
whether all terms of the proposal study are definable.
Always remember that all measurable variables must be
operationally defined. That is, if a researcher examining
the effect of television programmes in influencing the
learning behaviour of starlets. In order to avoid
confusion, the word “starlets” needs to be defined based
on a working definition.
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A researcher that is under this segment needs to consider
reviewing available literature to determine whether the
topic has been investigated. Were there problems in the
previous studies? What methods were used to answer
the research questions? What conclusions were drawn?
c) Can the data be analysed? A topic does not lend itself to
productive research if it requires the collection of data
that cannot be measured reliably and validly. When a
researcher chooses a topic, he needs to close check the
reliability or viability of the data being gathered whether
it can be generalised. The use of sufficient subjects that
are willing to provide valid information when contacted
will assist in analysing the data effectively.
Secondly, the researcher’s previous experience with the
statistical method selected to analyse the data will assist.
Also in analyzing the data, some of the researchers may
tend to use advanced statistical method which they do
not have a well background on and decided to use. The
researcher needs to understand how the proposed
statistic works and how to interpret the results. If care is
not taking, using an unknown statistical method by a
researcher may likely create errors in terms of
computation and interpretation. Research method should
not be selected because they are popular or because
research director suggests a given method but rather
because they are appropriate for a given study and are
understood by the person conducting the analysis. Using
a statistical method without understanding what the
method produces is called the law of the instrument.
d) Is the problem significant? Before a researcher delves
into researching any given topic he must first and
foremost find out whether the topic has merits, that is
whether the study will have practical or theoretical
value.
There are some questions that a researcher needs to pose
at this level; will the result add knowledge to the
information already available in the field? What is the
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real purpose of the study? Is the study intended for a
class paper, a thesis, a journal article or a management
summary?
e) Can the results of the study be generalised? Generability
means the ability of the study to be applicable to other
similar contents. It is only used when using quantitative
method of research. It also brings about the idea of
external validity, that is, one must be able to generalise
from it to other situations e.g. a study carried out on the
reading culture of mass communication students and the
findings should be similar to that of other department if
they use the same procedures and processes.
f) What cost and time are involved in the study? Most of
the researchers have the zeal and excellent idea of
conducting a particular study but the cost always
become a hindrance to the actualization of the study. At
the end, the project will be abandoned. A cost analysis
must be completed. It is not an ideal situation to develop
specific designs and the data-gathering instrument for a
project then end up cancelling it because of lack of
funds.
A carefully itemized list of all materials, equipments and
other facilities required is necessary before beginning a
research project. If the costs seem prohibitive, the
researcher must determine whether the same goal can be
achieved if costs are shaved in some areas.
Time is also an important consideration in research
planning. Research studies must be designed in such a
way that they can be completed in the amount of time
available. Many studies have failed because enough time
was not allotted for each research step and in many
cases; the pressure created by deadlines creates
problems in producing reliable and valid results.
g) Is the planned approach appropriate to the study? On the
issue of this question, it simply means the methodology
to use in conducting the research. The most marvelous
research idea may be greatly and often needlessly
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hindered by a poorly planned method of approach. A
close look at every study is required to plan the best
approach. Every procedure in a research study should be
considered from the starting point of the parsimony
principle.
h) Is there any potential harm to the subject? Thus, the
harm could be physical and psychological. In the
process of carrying out your research, you have to put it
into consideration whether the study is likely to inflict
any harm to your subject. This will enable you to
properly reframe or reconstruct your research. At this
level, a pilot or pre-test is required to be conducted.
(2). Background to the Study
Background to the study normally sets the stage for the
entire project. Background to the study provides readers with
the background information for the research reported in the
paper. Its purpose is to establish a framework for the research,
so that readers can understand how it is related to other
research. It establishes the issue or concern leading to the
research by conveying information about a problem. Because it
is the initial passage in a study or proposal, special care must be
given to writing it. The background needs to create reader
interest in the topic, establish the problem that leads to the
study, place the study within the larger context of the scholarly
literature and reach out to a specific audience. All of this is
achieved in a concise section of a few pages.
Asika (2009) is of the view that the problem under
investigation certainly belongs to a larger area of concern and
this larger area of concern must be described in general terms.
This description will form the background to the study, a base
on which the problem will be introduced. The background to the
study normally begins with a short introductory paragraph. The
primary aim of the background is to arrest the attention of the
readers and get them tuned to the subject matter. The
background set the stage for your work and puts your topic in to
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perspective. In this section, attempts are often made by the
researcher to provide background information to the study.
Background to the study should focus on the subject
matter. The problem under investigation needs to be properly
articulated to give a convincing reason for the work.
Assumption would not suffice here. The background to the
study should not be mix up with general and the specific,
instead of the usually approach of general to specific or specific
to general.
(3). Problem Statement
Problem statement has been one of the major challenges
of students in proposal writing. In articulating the problem
statement, the researcher is expected to first of all have access
to literature on the topic and he should review them in order to
understand what has been done on the area, what has been
found, what were the challenges, what are the missing gaps and
what he (the researcher) intends to do on the area. In essence,
you must identify the missing gap and with the intention to fill
it up. Problem statement can even come in a single paragraph
depending on how the researcher structured it. However, most
students tend to articulate the problem statement in a complete
page or more thinking that by establishing so many arguments
by scholars it will translate into a good problem statement. This
is far from it. The problem statement can be followed with a
short paragraph giving the nature and rationale of the problem.
The problem statement is the focal point of the researcher.
After selecting the topic and reviewing the available
literature, the next thing is to articulate the problem statement.
Under this, one is expected to state the problem of a research
that is being undertaken. Problem statement is simply the
motivation of the study. What spring you into action to embark
on the study? In articulating the statement of the problem, one is
expected to first of all read through the literature in order to be
aware of the arguments of other scholars and researchers
concerning the topic under investigation. This means that for
one to articulate the problem statement, one is expected to first
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of all review the available literature. This will give you an
insight of what other researchers have done in their previous
studies before you can be able to formulate an appropriate
problem statement.
As a researcher, you are looking for a lacuna that needs
close attention or existing methods that no longer seem to be
working. The problem statement itself is just one sentence, the
researcher needs to present persuasive arguments on why the
problem is important enough to be studied. Problem statement
is simply setting the research within the ongoing dialogue in the
literature. After establishing the research problem, next is to
justify its importance by reviewing studies that have examined
the issue. The problem statement must be identified and
properly articulated. A paragraph must be dedicated to touch the
gap in the literature. The problem must be written to address the
missing gap and providing a gap to fill or an articulated
problem.
(4). Aim or Purpose of the Study
According to Locke, et al., (2013) the purpose statement
indicates why you want to conduct the study and what you
intend to accomplish. It is called the purpose statement because
it conveys the overall intent of a proposed study in a sentence or
several sentences. It may also be called a study aim. In
proposals, researchers need to distinguish clearly between the
purpose statement, the research problem and the research
questions. The purpose statement sets forth the intent of the
study, not the problem or issue leading to a need for the study.
Given the importance of the purpose statement, it is helpful to
set it apart from other aspects of the proposal or study and to
frame it as a single sentence or paragraph that readers can easily
identify. Although the qualitative, the quantitative and the
mixed methods purpose statements share similar topics.
The aim of the study is the broad statement of desired
outcomes or the general intentions of the research, which ‘paint
a picture’ of your research project. It emphasizes what is to be
accomplished (not how it is to be accomplished). It addresses
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the long-term project outcomes. For instance, the aim of the
study should reflect the aspirations and expectations of the
research topic.
The aim is therefore the goal of the study; it is the actual
motive for carrying out a research work. The aim of the study is
normally stated in general form. Thus, the researcher should
ensure that he has only one aim in the study and it should be
written in a simple and concise form. Normally, a good research
work should be calculated at achieving the aim. Students should
note that when writing the “aim” of the study, there is no “s”
attach to it. The researcher should have in mind the aim that the
study hopes to achieve. For example, a researcher doing “A
Comparative Study of Hate Speech in the 2015 and 2019
General Elections in the Daily Trust, The Nation and The Sun
newspapers. The aim of the study could be written in this way:
The purpose of the study is to analyse the manifestation of hate
speech in the 2015 and 2019 general elections in the Daily
Trust, The Nation and The Sun newspapers. Most atimes, the
aim of the study is originated from the topic of the research
work.
(5). Objectives of the Study
The objectives of the study are the strategy that
facilitates the actualization of the aim. The objectives of the
study are more than one depending on the interest of the
researcher. The objectives are usually presented in numerical
sequence and they are specific. Research objectives describe
concisely what the researcher is trying to achieve. They
summarize the accomplishment a researcher wishes to achieve
through the project and provides direction to the study. A
research objective must be achievable, that is, it must be framed
keeping in mind the available time, infrastructure required for
research and other resources. Before forming a research
objective, you should read about all the developments in your
area of research and find gaps in knowledge that need to be
addressed. This will help you come up with suitable objectives
for your research project.
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Apparently, the objective of the study has to do with
what the researcher intends to achieve with the study or what he
intends to accomplish with his study. Having stated your aim,
you carve out your objective from there. The objectives of the
study normally come in specific forms. Askia (2002, p. 100)
advise that the statement of the objectives of the study should
begin with a clear statement of the problem, followed by other
related specific statements so that all of them will give the
reader a clear understanding of the problem being investigated.
(7). Research Questions or Hypothesis
The research questions or hypotheses narrow the
purpose statement to predictions about what will be learned or
questions to be answered in the study. The research questions
are the basic tools of inquiry in the study. They are the
templates that guide or assist the researcher to achieve the
objective of the study. The researcher should note that it is the
objectives of the study that are turn into research questions and
the objectives of the study must be aligned with the research
questions. The research question should be written in active
verb, that is, “what” and not “do” or “does”, these are inactive
verbs. The researcher must avoid what is called “so what
questions” like “do Daily Trust, The Nation and The Guardian
newspapers report corruption scandals?” Yes, so what? This
type of question should be avoided because they do not require
any formal or scientific measurement of variable.
On the other hand, hypothesis guides the researcher in
planning the course of the inquiry, in choosing the kinds of data
needed, in deciding the proper statistical treatment and in
examining the results of the study. As a researcher, you need to
make a declarative statement about the relationship between the
variables. Thus, hypothesis is a tentative statement that
establishes relationship among variables.
(8). Significance of the Study
In project(dissertations or thesis), writers often include a
specific section describing the significance of the study for
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selected audiences in order to convey the importance of the
problem for different groups that may benefit from reading and
using the study. By including this section, the writer creates a
clear rationale for the importance of the study. The more
audiences that can be mentioned, the greater the importance of
the study and the more it will be seen by readers to have wide
application. In designing this section, one might include the
following as outlined by Creswell and Creswell (2018) thus:
a. Three or four reasons that the study adds to the scholarly
research and literature in the field.
b. Three or four reasons about how the study helps
improve practice.
c. Three or four reasons as to why the study will improve
policy or decision making.
The significance of the study is simply its practical and
theoretical relevance. The importance of the study should be
examined clearly in policy, geography, theory and method.The
significance can also be measured at the following levels:
i. Significant to the methodology.
ii. Significant to the theoretical framework.
iii. Significant to you as a researcher.
iv. Significant to the body of knowledge.
v. Significant to the society.
There are some questions that a researcher needs to pose
to himself at this levels, will the result add knowledge to the
information already available in the field? What is the real
purpose of the study? Is the study intended for a class paper, a
thesis, a journal article or a management summary?
(9). Scope of the Study
The scope of the study is measured based on the
geographical, theoretical, methodological and demographical
parameters. It could be geographical entity, a particular
population, newspapers, individuals, radio, television or even
animals that the researcher deems fit to cover in his research
work. The scope could also be the time span of the study,
months or years. All these can constitute the scope of the study
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in your research proposal. The theoretical, methodological and
demographical scopes should be clearly itemised and spelt out
to the understanding of the reader.
(10). Limitations to the Study
Limitation refers to the likely variable that affects the
validity of the finding of the study. These could be social,
theoretical or methodological. Note that limitations have
nothing to do with money, time and transportation; these are not
part of the limitations. In some cases, limitations may come in
chapter one, but in most cases, limitations normally come at the
end of chapter five depending on the orientation of the
researcher and the place where the research is being conducted.
Methodological weaknesses and theoretical criticism should be
explained in the perspective and content of the study and also
demonstrate how these constitute limitations to the study.
Students or researchers should understand that by simply
discussing the limitations without stating how to overcome
them, they are simply telling people that their research is not
credible. Therefore, limitations should be discussed alongside
with solutions; this will add more credibility to the study.
(11). Organisation of the Study
Chapter one normally considers the background to the
study by looking at general overview of issues in a holistic
manner. After, which the motivation of the study (problem
statement) is considered. The aim and objectives of the study
are put into perspective as well as research questions. Chapter
one also considered justification, significance of the study,
scope and limitations as well as definition of concepts or terms.
Chapter two is literature review; it normally starts with
conceptual review where the author addresses some of the
concepts as articulated by scholars and researchers. After
conceptual review, empirical review is normally considered,
which examines some of the existing literature that has direct
bearing to the subject matter. Similarly, chapter two is also
located within the context of a theoretical framework.
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Theoretical framework consists of the following: the proponents
of the theories, basic tenets or assumptions of the theories,
strength and weaknesses of the theories and the nexus between
the theory and the study.
Chapter three basically explains the process of data
collection, the sources of data, sampling technique adopted and
the procedure for data presentation and analysis. Methodology
in any research work is important as the work itself.
Methodology determines whether a study will stand or will fall.
Under methodology, authors are expected to present and
articulate the method, study design and some of the instruments
that will facilitate the success of the study.
Chapter four is divided into three sections. The first
section addresses the field performance of the research
instruments. That is, the details of what transpires in the field
work. The second section emphasizes on the analysis of data
based on each research question. All the research questions are
answered in this regards. Section three of this chapter discusses
the main findings in relation to the theoretical, empirical and
conceptual reviews.
Chapter five examines the summary, conclusion and
recommendations. It captures and highlights the purpose,
method and major findings, which is just like an extended
abstract. Finally, conclusion is drawn from the study, which
addresses the inference, that is, the lesson that can be learnt
from the findings through the provision of answers to the
general objectives of the study. In conclusion, the researcher is
expected to summarise by analysing some important points that
were raised in the research work. Recommendations are also
drawn based on the findings as well as the sources consulted
(the references).
(12). Operational Definition of Terms or Concepts
The terms should be defined operationally as they are
used in the study.The researcher needs to explain and clarify all
the key terms in the study. This is to make the reader have a
better understanding of such terms in the course of the research
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exercise. The researcher often operates with certain terms and
concepts, which may be ordinarily unintelligible to the reader.
Key terms are evident in the research topic, aim and objectives
and must be defined in the context of the study. In this
perspective, the researcher needs a working definition. Students
should note that, dictionary or scholarly definitions will not
suffice.
(13). Literature Review
The literature review is an evaluative report of scholarly
information found in the related literature to your area of study.
Literature review has the following: it describes, it provides
summary to the existing literature, it evaluates the opinion, it
clarifies what exist, it gives theoretical basis of the work and it
must help you in determining what connects with the existing
literature. Apparently, literature review conveys to the reader
what knowledge has been established in an area and what are
the strength and weaknesses. The major role is to analyse the
existing literature and give justification as to how your research
work will fit into the existing knowledge. Your literature review
should provide a context for the research.
Literature review helps to determine whether the topic is
worth studying and it provides insight, which the researcher can
limits the scope to a needed area of inquiry. Once the researcher
identifies a topic that can and should be studied, the search can
begin for related literature on the topic. The literature review
accomplishes several purposes. It shares with the reader the
results of other studies that are closely related to the one being
undertaken. It relates a study to the larger, ongoing dialogue in
the literature, filling in gaps and extending prior studies
(Marshall and Rossman, 2016). It provides a framework for
establishing the importance of the study as well as a benchmark
for comparing the results with other findings. All or some of
these reasons may be the foundation for writing the scholarly
literature into a study. Studies need to add to the body of
literature on a topic and literature sections in proposals are
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generally shaped from the larger problem to the narrower issue
that leads directly into the methods of a study.
Standard research studies need literature review which
has to do with going through what other scholars or researchers
have articulated in their previous studies. Here, you review
materials that are relevant to your study. This is very important
because it gives the researcher a sense of focus and direction.
Effective literature review should facilitate the identification of
an interesting and significant knowledge gap in the area. Thus,
literature reviewer should attempt to discover a gap in the
selected area, which the new study can be conceived. Literature
review normally captures conceptual, empirical and theoretical
reviews.
Therefore, students or researchers should understand
that, a mere assembling of literature does not make it literature
review; you need to interrogate the literature. In carrying out
literature review, the researcher should also look at some of the
deficiencies in the existing studies. This will help to identify the
strengths and weaknesses of such studies. Aside this, the
researcher should be able to connect previous literature to the
current study. Once you only assemble literature without
interrogating them, you are simply doing what is called “stand-
alone” literature and this will not help you to locate the current
study with the existing literature.
(14). Theoretical Framework
One component of reviewing the literature is to
determine what theories might be used to explore the questions
in a scholarly study. Theories are formulated to explain, predict
and understand a phenomenon and in many cases, to challenge
an existing knowledge within the limit of critical bounding
assumptions. Theoretical framework is the structure that can
hold or support a theory of a research study. It introduces,
describes and explains why the research problem under study
exists and connects to the previous existing knowledge
(Richard, 2013).
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In the quantitative research, researchers often test
hypotheses stemming from theories. In a quantitative
dissertation, an entire section of a research proposal might be
devoted to presenting the broader theory guiding the study
hypotheses. In the qualitative research, the use of theory is
much more varied. The inquirer may generate a theory as the
final outcome of a study and place it at the end of a project,
such as in grounded theory. In other qualitative studies, it comes
at the beginning and provides a lens that shapes what is looked
at and the questions asked, such as in ethnographies or in
participatory, social justice research. In the mixed methods
research, researchers may both test theories and generate them.
Moreover, the mixed methods research may contain a
theoretical framework within, which both the quantitative and
the qualitative data are collected. These frameworks can be
drawn from feminist, racial, class or other perspectives and they
flow through different parts of a mixed methods study (Creswell
and Creswell, 2018).
The researcher should review and select a theory that
will aid the understanding of the findings of his study. Theory is
appropriate to a study when its assumptions describe, explain or
predict the problem under study. To locate your study within a
particular body of theory, one needs to pay absolute attention to
the discussion of the main variables in the study. It is through
understanding the main tasks and the real meaning of what a
researcher is studying that he will be able to choose a theory
that has direct relevance with the study and that best explain the
main tenants of the study. The researcher must also link the
theory to his study. There must be a nexus between the theory
and the study. Theoretical framework consists of the following:
a. The proponents of the theory.
b. Basic tenets or assumption should be identified.
c. Weakness and the strength of the theory should also be
established.
d. The nexus between the theory and the study should be
articulated.
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(15). Research Method
The research methodology describes your basic research
plan. It is the research methodology that determines whether
your research will stand or not. The method section is very
important, because it tells your research committee how you
plan to tackle your research problem. It will provide your work
plan and describe the activities necessary for the completion of
your project. These include the research design, population,
sampling techniques, sample size, data collection and analysis
instruments, etc. Under research method, the following shall be
discussed:
(a) Research Design
Research design entails the traditional approach to data
generation and analysis, which can be positivists,
constructivism, transformative and pragmatism. The researcher
not only selects a qualitative, quantitative or mixed methods
study to conduct, the inquirer also decides on a type of study
within these three choices. Research designs are types of the
inquiry within the qualitative, the quantitative and the mixed
methods approaches that provide specific direction for
procedures in a research study. Others have called them
strategies of inquiry (Denzin and Lincoln, 2011). The designs
available to the researcher have grown over the years as
computer technology has advanced data analysis and ability to
analyze complex models and individuals have articulated new
procedures for conducting social science research.
A research design is a plan approach for collecting and
analysing data in order to answer research questions. Research
design is view from the quantitative, the qualitative or the
mixed methods. The former is mostly attributed to the positivist
researchers (empiricists) who care more about quantity,
frequency and numerical values of data that can be analyzed
statistically, while the latter is usually ascribed to the critical
and cultural social science researchers whose concern is quality,
meaning and interpretation of data presented in a ‘text’ and they
mostly derive their answers through interpretation, experiential
and inferences (American Psychological Association, 2020).
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Basically, the clarity of thought of the researcher is the
secret of an excellent design. The essence of design is to
propose a great measure of harmony among the elements of
theories, data gathering, analysis and interpretation of findings.
Design refers to the pattern and techniques guiding scientific or
philosophical investigation inquiry (Gwandu, 2019).
(b) Population Description
Population is the aggregate of people, institutions, text
or anything else investigated and is a function of the specific
research objective. There are two dimensions that are used to
determine an appropriate population in a study: the topic area
and the time period. This implies that the researcher has to
define the communication population to be studied. There is the
need to identify and separate the communication domain so that
it will be consistent with the problem or question raised by the
study. The population to be sampled should be defined narrowly
enough to permit gathering manageable size of information.
Appelbaum, et al., (2018) note that what one is asking here is
simple, whether one is going to consider words, statements,
sentences, paragraphs or an entire article. This implies that the
study has to describe the area of focus.
The researcher needs to describe the population of the
study. The population of a study is the census of all the items or
subjects that possess the characteristics or that have the
knowledge of the phenomenon being studied. The researcher
must know the nature of the population, because it helps in the
choice of the sampling technique, this will guide appropriate
and operationalisation of the population of the study.
(c) Sample Size
As the population describes the group or individual
within the area of focus, the sample size describes the number
of people that will be examined. Sample size is the smallest
element that is taken to represent the population of the study.
Sample should be selected scientifically and must satisfy the
criteria of representativeness and adequacy. Wimmer and
Dominick (2011, p.102) established that there is no single
sample-size formula or method available for every research
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method or statistical procedure. Therefore, sample size should
be part of the elements or subjects that will realistically
represent the population of a study.
(d) Sampling Technique
This entails the researcher using probability or non-
probability technique in the selection of the sample. (See details
about sampling technique in Chapter five of this book).
Sampling technique is a way or a system that researchers adopt
in drawing samples from the population. The process of
sampling consists of three stages:
1. Defining the population of the study.
2. Drawing the sample from the population.
3. Applying the appropriate statistics.
(e) Data Gathering Instruments
This is an obligation on the researcher to be explicit
about the procedure, instruction and rules of the data gathering
process (Creswell and Poth, 2018). This enables the reader to
understand how the data were generated. Data gathering
instruments are mechanisms for the generation, analysis and
interpretation of data, variable for answering research questions
and or testing hypothesis. There are different instruments that
are used for collecting data, some of them include:
questionnaire, coding sheet, filed notes, audio or video
recording, etc.
(f) Method of Data Presentation and Analysis
Method of data presentation and analysis can be through
bar chart, histogram, frequency polygon, ogive or pie chart with
raw figures and simple percentage analysis. Again, most studies
used descriptive techniques. In the quantitative analysis, studies
take into account of numerical values or the frequencies with,
which the various delineated items are used to analyse the data.
In terms of the qualitative data, some studies adopt
Interpretative Phenomenological Analysis or thematic
analysis.IPA is an approach that wishes to explore individuals
or social groups’ perception, account of events or state as
opposed to attempting to produce an objective record of the
events or state. Thus, the method is a holistic approach to the
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construction of philosophical social science of consciousness
and identity through experience. Most IPA is conducted using
intensive qualitative research approach such as in-depth
interview (Baran and Davis, 2012).
Similarly, thematic analysis according to Braun and
Clarke in Musa (2019) is a qualitative research method, which
seeks to identify, evaluate and report pattern (theme) from the
data. Apparently, Musa (2019) adds that thematic analysis is an
approach, which intends to recognize pattern in a study where
emergent themes become the unit of analysis.
Chapter Summary
In this Chapter, the book discusses the fundamental
objectives of a research proposal. The research proposal is said
to be a blue-print of a research project. Research proposal is the
plan, which shows how a researcher intends to go about a
research exercise. It is the blue print of a research work. The
proposal is a plan action that is strategically designed to explain
how to investigate a subject matter, it opens an insight into what
the researcher is, how to solve it, the research instruments to
use, etc. The proposal also captures your chapter one to three
with all the relevant information needed in it. All the
instruments must be put in place to ensure that the goal of the
research is accomplished. The elements that constitute a
research proposal, from conceptual to conclusion were
discussed extensively.
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Chapter Ten
Format of Research Report
Introduction
Research report(thesis, dissertation, long essay or
project), ususally follows a fairly standardised pattern. Research
report is the hallmark of any research endeavour. The thesis,
dessertation or project shall consist of parts arranged in the
following order. However, there could be variations according
to disciplines.
1. Preliminary Pages
(a) Flyleaf
(b) Title
(c) Declaration (by Candidate)
(d) Certification or Approval (by Supervisor or examiner)
(e) Acknowledgements
(f) Dedication (if any)
(g) Table of Contents
(h) Abstract
Flyleaf: This shall be blank
Title: it is also known as the cover page. It includes title of the
study, which is stated at the upper half of the page, followed by
the author’s full name. The page shall bear the following:
i. Approved title of the thesis or dissertation all capitalised
at the top of the page;
ii. Full name of the author, surname last(all capitalised)
followed by the registration number and the
qualification(s) of the author at the time of submission
of the thesis or dissertation at the centre of the page;
iii. Degree for which the thesis or dissertation is submitted,
stated in the following words:
A Dissertation Submitted to the Department of Mass
Communication, Faculty of Communication, Bayero
University, Kano, In Partial Fulfillment of the
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Requirements for the Award of the Degree of Master
of Science in Mass Communication.
Note: Month and year of submission at the bottom
centre of the page.
Declaration: this page shall contain the following statement of
declaration by the candidate: “I hereby declare that this work is
the product of my research effort undertaken under the
supervision of (Title and names(s) of supervisor(s) and has not
been presented and will not be presented anywhere for the
award of a degree or certificate.Immediately below the
declaraton and to the centre of the page, the candiate shall
append his or her signature and the date. The candidate’s full
name and registration number, as it appears on the cover of the
thesis or dissertation, shall be typed under the signature.
Certification: this is a statement of the supervisee with his
signature and has a narration standard.
Approval: is a collaboration statement of the supervisee, HOD
and External Examiner. The space is provided for the signature
of all the members of thesis or dissertation committee or the
supervisor of the work or in some cases, the Dean of the faculty
or of the Postgraduate School or whoever has the final say on
the work.
Dedication: in this page, the author expresses his gratitude to
those he holds so dearly and those who in one way or the other
have been of immense help to him or her in life. These people
may not have necessarily contributed directy to the work.
Authors normally dedicate their works to their parents, wife or
husband, children, girl friend, fiance, fiancee or even their
mentors. E.g. To my mother, Mnguungwan.
Acknowledgements: the author may acknowledge in his or her
own words the assistance given by others during the research
and preparation of the thesis or dissertation. He acknowledges
the help and contributions of different people, who through their
involvement, like supervision of the work or making available
some materials and even typesetting of the manuscripts, have
made the work a success. The acknowledgement is not the
preface. The preface is used in writing the synopsis of the work.
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Remember that in the acknowledgement, it is only those who
contributed to the work that are acknowledged.
Table of Content: it carries a list of the chapters in the book
and their titles with corresponding pages. Other parts of the
table of contents are list of the tables and the list of numbers.
Only the first letter of all the words in the major section
headings shall be capitalised. For subsection headings, only the
first letter of the first word shall be capitalised.
Abstract: an abstract is a brief, comprehensive summary of the
contents of the paper. A well-prepared abstract can be the most
important paragraph in an article. An abstract is a stand-alone
statement that enables readers to obtain an overview of the
whole work. NB: It is closely knitted with your conclusion
more than your introduction. It contains the following:
a. It briefly conveys all the essential information of your
essay or thesis.
b. Present the objective, methods, results and conclusions
of a research project.
c. Contain all the key terms associated with your research.
d. Have a succinct, non-repetitive style.
e. Must not be more than one page (150-300 words) in
length.
The abstract comes first in your paper but you present it last.
The abstract has the opening sentence, objectives, method,
findings (which should reflect the objectives) conclusion and
recommendation.
Qualities of a Good Abstract
A good abstract must be:
Accurate: ensure that the abstract correctly reflects the
purpose and content of the paper. Do not include information
that does not appear in the paper body. If the study extends or
replicates previous research, cite the relevant work with an
author date citation.
Non-evaluative: report rather than evaluate; do not add
to or comment on what is in the body of the paper.
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Coherent and readable: write in clear and deliberate
language. Use verbs rather than their noun equivalents and the
active rather than the passive voice (e.g., “investigated” instead
of “an investigation of”, “we present results” instead of “results
are presented”. Use the present tense to describe conclusions
drawn or results with continuing applicability; use the past tense
to describe specific variables manipulated or the outcome
measured.
Concise: be brief and make each sentence maximally
informative, especially the lead sentence. Begin the abstract
with the most important points. Do not waste space by repeating
the title. Include only the four or five most important concepts,
findings or implications. Use the specific words in your abstract
that you think your audience will use in their searches.
Four Steps to Writing an Abstract
Sept one: begin with a draft of your essay:
i. Highlight the objectives and conclusions from your
introduction and conclusion.
ii. Underline keywords from the methods section.
iii. Highlight results and findings from the discussion
section.
Step two: group the above information into a single paragraph,
then:
i. Condense any definitions or explanations.
ii. Delete repeated words and phrases.
iii. Cut out any background information.
Step three: rephrase so that the abstract begins with your
specific findings (i.e. your conclusions), rather than an
introduction to the topic in general.
Step four: revise once more to ensure your abstract contains
only essential information, in the fewest possible words, and cut
out the obvious, such as “This paper examines…” or “The first
chapter provides a description of …” They have no place in
your abstract and try to avoid them. Below is a sample of an
abstract:
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Source: (Msughter and Ya’u, 2018)
List of Tables: this page is where you have the list of tables,
diagrams and figures used in the work.
Note that the preliminary page is numbered in roman figures
and where your work starts is the main body.
2. The Main Body
Chapter One: Introduction
1.1 Background to the Study
1.2 Problem Statement
1.3 Aim or purpose of the study
1.4 Objectives of the Study
1.5 Research Questions
1.6 Research Hypothesis
1.7 Significance of the Study
1.8 Scope of the Study
1.9 Operational Definition of Terms
References
Sample of Abstract
Attitudes towards university study have more impact on the
retention rates of students who enroll more than five years after
leaving school than external influences, such as workload, financial
pressures and family constraints. A 2005 survey of 150 first year
students, at Victoria University of Wellington, showed that mature
students who become actively involved in university life, by making
contact with academic staff, utilising Student Services, forming
study groups and joining recreational clubs, have a 70%
reenrollment rate the following year. This compares with only 35%
retention for mature students who study in isolation.
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Chapter Two:
Review of Related Literature
2.1 Introduction
2.1.1 Conceptual Review. Under this section, one could have
the following: 2.1.2, 2.1.3, etc.
2.2 Empirical Review
2.3 Theoretical Framework
References
Chapter Three:
3.1 Introduction
3.2 Research Design
3.3 Description of the Population of the Study
3.4 Sample Size
3.5 Area of the Study
3.6 Sampling Procedure
3.7 Research instrument or Administration
3.8 Method of Data Collection
3.9 Reliability and Validity
3.10 Method of Data Analysis
References
Chapter Four:
4.1 Introduction
4.2 Data Presentation or Analysis
4.3 Answering Research Questions
4.4 Testing Hypothesis
4.5 Discussion of Findings
References
Chapter Five:
5.1 Summary
5.2 Conclusion
5.3 Recommendations
5.4 Limitations to the Study
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Appendix
It has to do with attaching your coding guide, coding
sheet to the study. It enables the work to be referred to easily.
References or Bibliography
Reference or bibliography is a list of all written works
consulted in the course of the study, including those that may
not have been directly referred to in the body of text. It is
arranged in alphabetical order and surname should come first.
Chapter Summary
Research report is the hallmark of any research
endeavour. Writing a research report is fundamental not only in
social science but in any discipline. Research report (thesis,
dissertation, long essay or project), usually follows a
standardised pattern. A research report should be written in a
clear, concise and dignified manner. This chapter discusses the
format of research report, how to write preliminarily pages and
how to construct the body of the research work.
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Chapter Eleven
Guidelines for Citations and Reference Formations
Introduction
American Psychological Association Style provides a
foundation for effective scholarly communication because it
helps authors present their ideas in a clear, concise and
organized manner. Uniformity and consistency enable readers
to focus on the ideas being presented rather than formatting and
to scan works quickly for key points, findings and sources.
Style guidelines encourage authors to fully disclose essential
information and allow readers to dispense with minor
distractions, such as inconsistencies or omissions in
punctuation, capitalization, reference citations and presentation
of statistics. When style works best, ideas flow logically,
sources are credited appropriately and papers are organized
predictably and consistently. People are described using
language that affirms their worth and dignity. Authors plan for
ethical compliance and report critical details of their research
protocol to allow readers to evaluate findings and other
researchers to potentially replicate the studies. Tables and
figures present data in an engaging, consistent manner
(American Psychological Association, 2020).
Excellence in writing is critical for success in many
academic and professional pursuits. APA style is a set of
guidelines for clear and precise scholarly communication that
helps authors, both new and experienced, achieve excellence in
writing. It is used by millions of people around the world in
psychology and also in fields ranging from nursing to social
work, communications to education, business to engineering
and other disciplines for the preparation of manuscripts for
publication as well as for writing student papers, dissertations
and theses (American Psychological Association, 2010).
APA is one of many referencing styles used in academic
writing. APA is used across a variety of disciplines. When
referencing, you use the standardised style to acknowledge the
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source of information used in your assignment, research paper
or project. It is important (morally and legally) to acknowledge
someone’s ideas or words you have used. Academic writing
encourages paraphrasing information you have researched and
read. Paraphrasing means re-wording something you have read
into your own words. If you use someone else’s words or work
and fail to acknowledge them, you may be accused of
plagiarism and infringing copyright.
Referencing correctly enables the marker or reader of
your assignment to locate the source of the information. They
can verify the information or read further on the topic.
Referencing also allows one to retrace the steps and locate the
information used for assignments and discover further views or
ideas discussed by the author. By referencing clearly and
correctly, it demonstrates that one has undertaken research on
the assignment topic and located relevant information.
There are two main parts to referencing:
1. The first one is indicating within your assignment,
research paper or projects the sources of the information
you have used. This demonstrates support for your
ideas, arguments and views. Sometimes this is referred
to as: citing in text, in-text citations or text citations.
In-text citations, we have parenthetical and narrative
citations. Parenthetical citations are citations to original
sources that appear in the text of your paper. This allows
the reader to see immediately where your information
comes from and it saves you the trouble of having to
make footnotes or endnotes. The APA style calls for
three kinds of information to be included in in-text
citations. The author’s last name and the work’s date of
publication must always appear and these items must
match exactly the corresponding entry in the reference
list. The third kind of information, the page number,
appears only in a citation to a direct quotation. Example
of parenthetical and narrative citations:
Parenthetical Citation: (Msughter, 2020)
Narrative Citation: Msughter (2020)
231
2. The second part to referencing is the construction of a
reference list. The reference list shows the complete
details of everything you cited and that appeared in an
alphabetical list on a separate page, at the end of your
assignment or research work.
Note: Everything you have cited in text appears in your
reference list and likewise, everything that appears in your
reference list will have been cited in text. (The exception is
when using a personal communication. Personal
communications are cited in text but do not appear in the
reference list).
In-Text References (APA 7th Edition)
APA uses the ‘author-date’ style of referencing. That is,
in-text references (generally) appear in the following format:
(Author’s Last Name, Year of Publication, Page Number(s) in
the case of direct quotation.
Example: (Msughter, 2020, p. 13).
You are also permitted to include the Author’s name in a
sentence, omitting it from the brackets.
Example: Msughter (2020, pp. 13-15) observes that…
Note: For multiple pages, use the abbreviation ‘pp.’ Include the
full page range, i.e. ‘pp. 64-67’ as opposed to ‘64-67’.
When directly quoting from a source, you must include
page number(s) and enclose the quote in double quotation
marks.
Example: “A woman must have money and a room of her own
if she is to write fiction” (Woolf, 1929, p. 6).
When paraphrasing or referring to an idea contained in
another work, the Publication manual of the American
Psychological Association advises: “you are encouraged to
provide a page or paragraph number, especially if it would help
an interested reader locate the relevant passage in a long or
complex text” (American Psychological Association [APA],
2010, p. 171). It is recommended that you verify this advice
with your unit of study coordinator, lecturer or tutor for each
subject.
232
If you are referring to an entire work, include only the
Author’s Last Name and Year of Publication in brackets. If you
are referring to part of a work, you must include Page Numbers
or their equivalent (see specific examples for more
information).
When citing a source you have not read yourself but
which is referred to in a source you have read (also known as
‘secondary referencing’), use the following method:
Moore (as cited in Maxwell, 1999, p. 25) stated that…
Important: You will cite Maxwell, not Moore, in the Reference
List.
Note: It is always preferable to cite the original source.
Reference List
i. The reference list should appear at the end of your work
on a separate page.
ii. Only include references you have cited in your work.
iii. All references should have a hanging indent. That is, all
lines of a reference subsequent to the first line should be
indented (see examples in the tables below).
In general, references should be listed alphabetically by the last
name of the first author of each work.
Special Reference List Cases:
a. In the case of works by different authors with the same
family name, list references alphabetically by the
authors’ initials.
b. In the case of multiple works by the same author in
different years, list references chronologically (earliest
to latest).
c. In the case of multiple works by the same author in the
same year, list references alphabetically by title in the
reference list.
d. When referring to Books, Book Chapters, Article Titles
or Webpages, capitalise only the first letter of the first
word of a title and subtitle and proper nouns. Example:
Aboriginals and the mining industry: case studies of the
Australian experience
233
e. When referring to Journal Titles, capitalise all major
words (do not capitalise words such as ‘of’, ‘and’, &
‘the’ unless they are the first word in the title).
Example: Journal of Exercise Science and Fitness
Notable Changes in Citing Sources in the 7th Edition of APA
1. Don’t include publisher location. For example, Covey,
S. R. (2013). The 7 habits of highly effective people:
Powerful lessons in personal change. New York. YN:
Simon & Schuster.
2. Shorten in-text citation for 3+ authors. E.g. 1st citation
(7th edition) (Msughter et al., 2020).
3. Include up to 20 authors in the reference. E.g. Pate, U.
A., Msughter, A. E., Akinfeleye, R. A., Kurfi, M. Y.,
Oso, L., Abubakar, U., Miller, T. C., Brown, M. J.,
Wilson, G. L., Evans, B. B. Kelly, R. S, Turner, S. T.,
Nelson, T. P., Lee, L. H., Hughes, W., Carter, D.,
Campbell, C., Baker, A. B., Flores, T., Gray, W. E.
(2020).
4. Format DOIs as URLs. E.g. doi:
10.1080/02626667.2018.1560449, use
https://doi.org/10.1080/02626667.2018.1560449
5. Don’t include “Retrieved from” in front of URL. E.g.
Walker, A. (2019, November 14). Germany avoids
recession but growth remains weak. Retrieved from
BBC News. https://www.bbc.com/news/business-
50419127.
6. Don’t include the format, platform or device for
ebooks. E.g. Burns, A. (2018). Mlikman [kindle
version]. Faber & Retrieved from
https://amzn.to/20bKrVf.
7. Use singular “they” as a gender-neutral pronoun. E.g.
a researcher’s career depends on how often he or she is
cited. Use “they” in place of he or she.
8. Use descriptive phrases instead of labels. E.g. The
poor (adjective as noun). Use “people living in
poverty” (descriptive phrase).
234
9. Use exact age ranges. E.g. over 65 (broad category).
Use “65 to 75 years old” (specific).
10. More flexibility in font choices. Options include:
Calibril 11, Arial 11, Lucida Sans Unicode 10, Times
New Roman 12 and Georgia 11.
11. Use only one space after a period at the end of the
sentence.
12. Use double quotation marks for linguistic examples.
APA endorses the use of the singular pronoun “they”
and stay in italics (American Psychological
Association, 2020).
In-Text Reference
Reference List
BOOK & BOOK CHAPTERS
One author: in-text
reference Placement
Note: There are two
main ways to use in-
text references. Firstly,
to focus on the
information from your
source ‘information
prominent’. Secondly,
to focus on the author-
‘author prominent’.
‘Information
prominent’ (the
author’s name is within
parentheses):
The conclusion reached
in a recent study
(Cochrane, 2007) was
that…
OR
‘Author prominent’ (the
author’s name is outside
the parentheses):
(narrative)
Cochrane (2007)
concluded that…
Cochrane, A. (2007).
Understanding urban
policy: A critical
approach. Malden,
MA: Blackwell
Publishing.
One author: when
fewer than 40 words
are quoted
Include the material in
the paragraph and
include specific page
number(s).
Use double quotation
marks to show the
exact words.
An interesting view was
expressed that “the
connection of high
profile developments to
their surrounding
environment has
increasingly been
questioned” (Cochrane,
2007, p. 117).
OR
An interesting view was
expressed by Cochrane
(2007, p. 117) that “the
Cochrane, A. (2007).
Understanding urban
policy: A critical
approach. Malden,
MA: Blackwell
Publishing.
235
connection of high
profile developments to
their surrounding
environment has
increasingly been
questioned”
One author: when 40
or more
words are quoted
Begin quoting the
material on a new line,
indent it 5 spaces (use
the Indent tool to keep
all lines of the quote
evenly indented),and
include specific page
number(s).
Omit the quotation
marks.
Use double spacing
for both your text and
the indented quote.
Make sure the quote is
exactly as it was
published.
Much has been written
about acute care.
Finkelman (2006) for
example, points out that:
There are many changes
in acute care services
occurring almost daily,
and due to the
increasing use of
outpatient surgery,
surgical services have
experienced major
changes. Hospitals are
increasing the size of
their outpatient or
ambulatory surgery
departments and
adjusting to the need of
moving patients into
and out of the surgical
service in 1 day or even
a few hours (p. 184).
Recently, this trend has
been seen in some
Australian hospitals and
research here…
Finkelman, A. W.
(2006). Leadership
and management in
nursing. Upper
Saddle River, NJ:
Pearson Prentice
Hall.
Two authors
When considering the
Howard Government’s
Indigenous health
expenditure, Palmer and
Short (2010, p. 63)
maintain that…
Palmer, G. R., &
Short, S. D. (2010).
Health care and
public policy: An
Australian analysis
(4th ed.) Palgrave
Macmillan.
Three to five authors
For the first in-text
reference, use the first
author’s surname
followed by ‘et al.’
A recent study by
Seeley, et al., (2011)
concluded that…
Seeley, R., VanPutte,
C., Regan, J., &
Russo, A. (2011).
Seeley’s anatomy &
physiology. McGraw-
236
The et al., should be
italicize
Hill.
Works by different
authors with the
same family name
For in-text references,
include the initials of
the authors in question
to enable readers to
differentiate between
them.
List references
alphabetically by the
authors’ initials in the
Reference List.
These techniques have
been shown to improve
test scores among
primary school aged
children (R. Smith, 2010,
p. 56).
If funding were
enhanced, it is arguable
these problems could be
ameliorated (C. J. Smith
& Laslett, 1993, p. 24).
Smith, C., & Laslett,
R. (1993). Effective
classroom
management: A
teacher’s guide (2nd
ed.) Routledge.
Smith, R. (2010).
Rethinking teacher
education: Teacher
education in the
knowledge age.
AACLM Press.
Several works by the
same author in
different years
When citing
references separately,
no special rule needs
to be observed. When
citing references
collectively, separate
years with a comma
and insert years
earliest to latest.
List references
chronologically
(earliest to latest) in
the Reference List.
These techniques have
changed markedly in the
last decade (Greenspan,
2000, 2011).
Greenspan, A.
(2000). Orthopedic
radiology: A
practical approach
(3rd ed.). Lippincott
Williams & Wilkins.
Greenspan, A.
(2011). Orthopedic
imaging: A practical
approach
(5th ed.).
Philadelphia,
Lippincott Williams
& Wilkins.
Several works by the
same author in the
same year
Arrange alphabetically
by title in the
Reference List. Place
lowercase letters (“a”,
“b”, “c”, etc.)
immediately after the
year.
Leadership and change
in schools have been
major topics of
discussion for several
years (Fullan, 1996a,
1996b) and this
conference…
“Educational change”
has taken on a new
meaning in recent
Fullan, M. (1996a).
Leadership for
change. In
International
Hand book for
educational
leadership and
administration.
Kluwer Academic
Publishers.
237
years(Fullan, 1996b) …
Fullan, M. (1996b).
The new meaning of
educational change.
London, England:
Cassell.
Several authors,
different years,
referred to
collectively in your
work
List sources
alphabetically by
family name in the in-
text reference in the
order in which they
appear in the
Reference List.
Separate each
reference with a
semicolon.
The cyclical process
(Carr & Kemmis, 1986;
Kemmis & McTaggart,
1988; MacIsaac, 1995)
Dick, 2000; suggests…
Carr, W., & Kemmis,
S. (1986). Becoming
critical: Education
knowledge and action
research. England:
FalmerPress.
Dick, B. (2000). A
beginner’s guide to
action research.
Retrieved from
http://www.scu.edu.a
u/schools/gcm/ar/arp/
guide.html
Kemmis, S., &
McTaggart, R. (Eds.).
(1988). The action
research planner (3rd
ed.). Melbourne,
Australia: Deakin
University.
MacIsaac, D. (1995).
An introduction to
action research.
http://physicsed.buffa
lostate.edu/danowner/
actionrsch.
Html
eBook – online book
- If the URL leads to
information about how
to obtain the book,
don’t include
“Retrieve from” in
front of URL.
- If there is a DOI
We found helpful
information about deaf
children (Niemann,
Greenstein, and David,
2004) that meant we
could…
OR
Schiraldi (2001) offers
solutions to PTSD.
Niemann, S.,
Greenstein, D., &
David, D. (2004).
Helping children who
are deaf: Family and
community support
for children who do
not hear well.
http://www.hesperian
.org/
238
(digital object
identifier)
include it instead of
the ‘Retrieved from’
statement. A DOI is a
unique, permanent
identifier assigned to
many electronic
documents.
publications_downlo
ad_deaf.php
Schiraldi, G. R.
(2001). The post-
traumatic stress
disorder
sourcebook: A guide
to healing, recovery,
and growth
https://www.doi:10.1
036/0071393722.
Chapter in edited
book
A discussion about
Australia’s place in
today’s world (Richards,
1997) included reference
to…
OR
Richards (1997)
proposed that…
Richards, K. C.
(1997). Views on
globalization. In H.
L. Vivaldi (Ed.),
Australia in a global
world (pp. 29-43).
Australia: Century.
Brochure – author is
also publisher
The security of personal
information is addressed
in the TransACT
brochure (TransACT,
n.d.)
TransACT . (n.d.).
Guide to equipment
and service.
Canberra, Australia:
Author.
Editor
In discussing best
practice, Zairi (1999)
identified…
OR
Best practice indicators
in management have
been identified (Zairi,
1999) and…
Zairi, M. (Ed.).
(1999). Best practice:
Process innovation
management.
Butterworth-
Heinemann.
Compiler, or Reviser,
or Translator
Use the following
abbreviations after
the person’s name in
the Reference List:
This novel by Gaarder
(1991/1994) provides an
appealing approach to…
OR
Socrates has been
described as “enigmatic”
(Gaarder, 1991/1994,
Gaarder, J. (1994).
Sophie’s world: A
novel about the
history of philosophy
(P. Møller, Trans.).
London, England:
Phoenix House.
(Original work
239
Comp.
Rev.
Trans.
p.50) which provides us
with…
published 1991).
Corporate author –
when the author is
also the publisher
Spell out the full name
of the body each time
it is cited in-text,
unless it is long and
has a familiar or easily
understood
abbreviation. In the
latter case, give the
full name with the
abbreviation for the
first in-text reference.
Use the abbreviation
only for subsequent
references.
A recent study
(Australian Institute of
Health and Welfare
[AIHW] (2009)
highlighted …
Subsequent in-text
references:
The AIHW (2009) found
that…
Australian Institute of
Health and Welfare.
(2009). Indigenous
housing needs 2009:
A multi-measure
needs model
(AIHWcat. no. HOU
214). Canberra,
Australia: Author.
Corporate author –
commissioned
reports
The report prepared by
the South Australian
Centre for Economic
Studies (2009) was
discussed.
South Australian
Centre for Economic
Studies. (2009).
Local government’s
current and potential
role in water
management and
conservation: Final
report.
Commissioned by the
LocalGovernment
Association of South
Australia.
Adelaide,Australia:
Author.
No date of
publication
Some aspects of forensic
science are more
challenging than others
(Browne, n.d.) and for
this reason…
Browne, J. D. (n.d.).
Forensic science as a
career. Tower
Publishing.
Second or later
edition
Peters (2001, p. 6)
argued that “...”
Peters, T. (2001). The
elements of
counselling (2nd ed.).
240
Macmillan.
Multi-volume work
Inge, Duke and Bryer
(1978, p. 27) claim that
there is much to learn
about these writers
which results in…
OR
There is so much to learn
about our country (Clark,
1978, p. 42) that we kept
returning to…
Inge, M. T., Duke,
M., & Bryer, J. R.
(Eds.). (1978). Black
American writers:
Bibliographical
essays (Vols. 1-2).
New York, NY: St.
Martins.
Clark, C. M. H.
(1978). A history of
Australia: Vol. 4. The
earth abideth for
ever, 1851-1888.
Melbourne
University Press.
DICTIONARY OR ENCYCLOPEDIA
Dictionary or
Encyclopaedia-print
Include information about
editions, volume numbers
and page numbers in
parenthesis following the
title in the Reference List.
According to one
definition of
“bivalence”
(VandenBos, 2007,
p.123)…
VandenBos, G. R.
(Ed.). (2007). APA
dictionary of
psychology.
Washington, DC:
American
Psychological
Association.
Dictionary or
Encyclopedia – online
Include information about
editions, specific volume
numbers or page numbers
in parenthesis following
the title in the
Reference List.
A psychological
overview of ADHD
(Arcus, 2001)…
Arcus, D. (2001).
Attention deficit /
hyperactivity disorder
(ADHD). In B.
Strickland (Ed.), The
Gale encyclopedia of
psychology.http://ww
w.gale.cengage.com
Note: If retrieved
from a database, do a
Web search for the
home page of the
publisher of the
encyclopaedia and
use the URL in the
reference.
241
Journal, Newspaper & Newsletter Articles
Journal article with one
author – separated
paging (paginated by
issue)
If each issue of a journal
begins on page1, include
the issue number in
parenthesis immediately
after the volume number
in the Reference List.
In an earlier article, it
was proposed
(Jackson, 2007)…
Jackson, A. (2007).
New approaches to
drug therapy.
Psychology Today
and Tomorrow,
27(1), 54-59.
Journal article with two
authors/ continuous
paging throughout a
volume.
If the journal volume page
numbers run
continuously throughout
the year, regardless of
issue number, do not
include the issue number
in your Reference List
entry.
Kramer and Bloggs
(2002) stipulated in
their latest article…
OR
This article on art
(Kramer and Bloggs,
2002) stipulated
that…
Kramer, E., &
Bloggs, T. (2002).
On quality in art and
art therapy. American
Journal of Art
Therapy, 40, 218-
231.
Journal article with
three to five authors
For the first in-text
reference, use the first
author’s family name
followed by ‘et al.’ for
subsequent entries.
A recent study to
investigate the effects
of an organisational
stress management
program on
employees (Elo, et
al., 2008) concluded
that…
Elo, A., Ervasti, J.,
Kuosma, E., &
Mattila, P. (2008).
Evaluation of an
organizational stress
management program
in a municipal public
works organization.
Journal of
Occupational Health
Psychology, 13(1),
pp. 10-23.
Journal article with six
to seven authors
For all in-text references,
list only the first author’s
family name followed by
A simple ALMA is
described in a recent
study (Restouin et
al., 2009).
Restouin, A., Aresta,
S., Prébet, T., Borg,
J., Badache, A., &
Collette, Y. (2009). A
simplified, 96-well–
adapted, ATP
242
‘et al.’ All authors are
included in the Reference
List.
luminescence–based
motility assay.
BioTechniques
47, 871–875.
https://www.
10.2144/
000113250
Journal article with
eight or more Authors
For all in-text references,
list only the first author’s
family name followed by
‘et al.’ In the reference
list, include the first six
authors’ names, then
insert three ellipsis points
(...), and add the last
author’s name.
Traumatic injury is
the leading cause of
death and disability
worldwide(Steel et
al., 2010, p. 523).
Steel, J., Youssef, M.,
Pfeifer, R., Ramirez,
J. M., Probst, C.,
Sellei, R., ... Pape, H.
C. (2010). Health-
related quality of life
in patients with
multiple injuries and
traumatic brain injury
10+ years postinjury.
Journal of Trauma:
Injury, Infection, and
Critical Care, 69(3),
pp. 523-531.
Journal or magazine
article with no volume
or issue number
Wychick and
Thompson (2005)
foreshadow that scam
will still be
enticing…
OR
An interesting
approach to scam
(Wychick and
Thompson, 2005)
suggested that…
Wychick, J., &
Thompson, L. (2005,
November 24). Fallen
for a scam lately?
AustraliaToday, 54-
60.
Journal article retrieved
from a
database – with a DOI
(Digital Object
Identifier)
A DOI is a unique,
permanent identifier
assigned to articles in
many databases.
.
A study examining
priming (Johns &
Mewhort, 2009)
discovered …
Johns, E., &
Mewhort, D. (2009).
Test sequence
priming in
recognition memory.
Journal of
Experimental
Psychology:
Learning, Memory
and Cognition, 35,
1162-1174.
243
https://www.10.1037/
a0016 372
Journal article – in press
Influence of music in
running performance
(Lee and Kimmerly,
in press)
Lee, S., & Kimmerly,
D. (in press).
Influence of music on
maximal self-paced
running performance
and passive post-
exercise recovery
rate. The Journal of
Sports Medicine and
Physical Fitness.
Journal article –
Cochrane Review with
DOI
Overweight and
obesity are increasing
throughout the
industrialised world
(Shaw, et al., 2005)
…
Shaw, K., O'Rourke,
P., Del Mar, C., &
Kenardy, J. (2005).
Psychological
interventions for
overweight or
obesity. The
Cochrane database
of systematic reviews
(2).
https://www.10.1002/
14
65
1858.CD003818.pub
2
Journal article retrieved
from a
database – without a
DOI
- If there is no DOI, do a
Web search to locate the
URL of the journal’s
home page & include it in
the Reference List. The
journal URL can
sometimes be found in
the database record or in
the full text view of the
article.
- If the online article is
ONLY available from
The effects of climate
change on agriculture
are studied by
Ramalho, et al.,
(2009)…
Primary care is one
area marked for
improvement
(Purtilo, 1995, p.
111).
Example using URL
of journal home
page:
Ramalho, M., Da
Silva, G., & Dias, L.
(2009). Genetic plant
improvement and
climate changes.
Crop Breeding and
Applied
Biotechnology, 9(2),
189-195.
http://www.sbmp.org.
br/cbab
Example using URL
of database (where
244
a database (e.g. for
discontinued journals
where the journal home
page doesn’t exist),
include the entry page
URL of the database
where it was found. Give
the database name if not
in the URL.
there is no journal
home page):
Purtilo, R. (1995).
Managed care:
Ethical issues for the
rehabilitation
professions. Trends
in Health Care, Law
and Ethics, 10, 105-
118. http://www.
proquest.com
Book review in a journal
In his review of
Thomas Samaras’
latest book, Marson
(2009) identifies…
Marson, S. M.
(2009). How big
should we be? A
Herculean task
accomplished
[Review of the book
Human body size and
the
laws of scaling:
Physiological,
performance, growth,
longevity and
ecological
ramification, by T.
Samaras]. Public
Health
Nutrition, 12, 1299–
1300.
https://www.10.1017/
S1368980009990656
Newspaper article –
with an author
The notion of a Bill
of Rights may be
inappropriate in the
Australian context
(Waterford, 2007).
Waterford, J. (2007,
May 30). Bill of
Rights gets it wrong.
The Canberra Times,
p. 11.
Newspaper article –
without an author
The redesign of the
Internet (“Internet
pioneer”, 2007) is
said to…
Internet pioneer to
oversee network
redesign. (2007, May
28). The Canberra
Times, p. 15.
Newspaper article
retrieved from a
In an attempt to save
the tiger, Darby
Darby, A. (2002,
August 20). Rarest
245
Database
Do a Web search to locate
the URL of the
newspaper’s home page
& include it in the
reference list.
(2002) provided…
tiger skin a rugged
survivor. Sydney
Morning Herald.
http://www.smh.com.
au
Article in an online
newsletter
Australia’s casualty
rate was almost 65
per cent - the highest
in the British Empire
(“Australians and the
Western Front”,
2009)
Australians and the
Western Front.
(2009, November).
Ozculture newsletter.
http://www.
Cultureandrecreation.
gov.au/ newsletter/
CONFERENCE OR SEMINAR PAPERS
Conference or seminar
papers in published
proceedings – print
If the paper is from a
book, use the Book
chapter citation format. If
it is from regularly
published proceedings
(e.g. annual), use the
Journal article citation
format.
In a paper about
conservation of
photographs (Edge,
1996), the
proposition that…
Edge, M. (1996).
Lifetime prediction:
Fact or fancy? In M.
S. Koch, T. Padfield,
J. S. Johnsen, & U.
B. Kejser (Eds.),
Proceedings of the
Conference on
Research Techniques
in Photographic
Conservation (pp. 97-
100). Copenhagen,
Denmark: Royal
Danish Academy of
Fine Arts.
Conference or seminar
papers in published
proceedings – online
Tester (2008) points
to the value of using
geothermal sources
for power and
energy.
Tester, J. W. (2008).
The future of
geothermal energy as
a major global energy
supplier. In H.
Gurgenci & A. R.
Budd (Eds.),
Proceedings of the
Sir Mark Oliphant
International
Frontiersof Science
and Technology
Australian
Geothermal Energy
246
Conference,
Canberra, Australia:
Geoscience Australia.
http://www.ga.gov.au
/image_cache/
GA11825.pdf
GOVERNMENT PUBLICATIONS
Government
department as author
Spell out the full name of
the body each time it is
cited in-text, unless it is
long and has a
familiar/easily understood
abbreviation. In the latter
case, give the full name
with the abbreviation for
the first in-text reference.
Use the abbreviation for
subsequent references.
The need for
guidelines to manage
and use multiple
channels to deliver e-
government services
(Department of
Finance and
Administration
[DOFA], 2006)
presents Australian
Government agencies
with…
Subsequent in-text
reference/s: DOFA
(2006) identified …
Department of
Finance and
Administration.
(2006). Delivering
Australian
Government services:
Managing multiple
channels. Canberra,
Australia: Author.
Government publication
– with identifying
number
Includes report numbers,
catalogue numbers, etc.
Recently released
statistics from the
Australian Bureau of
Statistics (ABS)
(2007) reveal
interesting changes in
Australian society.
Subsequent in-text
reference/s: The
ABS (2007) reported
that …
Australian Bureau of
Statistics. (2007).
Australian social
trends (Cat. no.
4102.0). Canberra,
Australia: ABS.
Government report –
online
First in-text
reference:
A recent government
report (Department of
the Prime Minister
and Cabinet
[PM&C], 2008)
examines a selection
of key topics …
Department of the
Prime Minister and
Cabinet. (2008).
Families in
Australia: 2008.
http://www.
dpmc.gov.au/publicat
ions/
families/index.cfm#c
247
Subsequent in-text
references:
Families in Australia
were highlighted
(PM&C, 2008)…
ontact
Government approved
standards
…and “including
data in computer
systems, created or
received and
maintained by an
organisation”
(Standards Australia,
1996, p. 7) as well
as…
Standards Australia.
(1996). Australian
Standard AS 4390:
Records
Management.
Sydney, Australia:
Author.
Act – print
According to s. 8.1 of
the Anti-
Discrimination Act
1977 (NSW), it is
unlawful for an
employer to
discriminate against a
person on the ground
of race.
Anti-Discrimination
Act 1977 (NSW) s.
8.1 (Austl.).
Follow this
convention:
Short Title of the Act
(in italics) Year (in
italics) (Jurisdiction
abbreviation) Section
number Subdivision,
if relevant (Country
abbreviation).
Bill – print
The Mental Health
Bill 2013 (WA)
prohibits…
Mental Health Bill
2013 (WA) (Austl.).
Follow this
convention:
Bill Name (no italics)
Year (Jurisdiction
abbreviation)
(Country
abbreviation).
Act & Bill – online
According to s. 8.1 of
the Anti-
Discrimination Act
1977 (NSW), it is
unlawful for an
employer to
discriminate against a
Anti-Discrimination
Act 1977 (NSW) s.
8.1 (Austl.).
http://www.
legislation.nsw.gov.a
u/maintop/scanact/inf
orce/N ONE/0
248
person on the ground
of race.
Case
According to Ellis v.
Wallsend District
Hospital (1989)…
…in a land right case
(Mabo v.
Queensland, 1988)…
Ellis v. Wallsend
District Hospital
1989 17 NSWLR 553
(Austl.).
Mabo v. Queensland
1988 166 CLR 186
(Austl.).
Follow this
convention:
Case Name (in
italics) Year Volume
number Reporter
abbreviation First
page number
(Country
abbreviation).
IMAGES, MUSIC & AUDIOVISUAL MEDIA
CD recording
Lyrics from Paul
Kelly’s song “From
Little Things Big
Things Grow”
(Kelly, 1997, track
10) were used in
recent television
advertisements.
Kelly, P. (1997).
From little things big
things grow. On
Songs from the south:
Paul Kelly’s greatest
hits [CD].
Melbourne,
Australia: Mushroom
Records.
DVD/Video recording
Jane Austen’s world
came alive in Sense
and sensibility (Lee,
1995)
Lee, A. (Director).
(1995). Sense and
sensibility [DVD].
Australia: Columbia
TriStar Home Video.
Figure, Table, Graph,
Map or Chart
Cite each of these as you
would for a book.
Include, in square
brackets, the type of
entry immediately after
the title:
Graph
The internal
processes were well
described (Kaplan &
Norton, 2004)which
led to…
Map
To locate a property
Graph
Kaplan, R. S., &
Norton, D. P. (2004).
Internal processes
deliver value over
different time
horizons [Graph]. In
Strategy maps:
Converting intangible
249
[Figure].
[Table].
[Map].
[Graph].
[Chart].
just outside the
Australian Capital
Territory, use the
1:100 000 map
produced by
Geoscience Australia
(2004) which
covers…
assets into tangible
outcomes (p. 48).
Boston, MA: Harvard
Business School.
Map
Geoscience Australia
[NATMAP]
(Cartographer).
(2004). ACT region,
New South Wales and
Australian Capital
Territory [Map].
Canberra, Australia:
Author.
Image – online
The effective use of
light in Monet’s
‘Haystacks’ (Monet,
1890)…
Monet, C. (1890).
Haystacks, midday
[Painting]. National
Gallery of Australia,
Canberra
http://artsearch
.nga. gov.au/
DetailLRG.cfm?
IRN=29073&View=
LRG
Liner notes
The American jazz
trombonist,
bandleader and
composer Jack
Teagarden
(Weiner, 1995)…
Weiner, D. J. (1995).
[Liner notes]. J.
Teagarden
(Composer), Big ‘T’
jump [CD]. USA:
Jass Records.
Score
Craig Scott is one of
Australia’s leading
bassists (Scott, 2013)
Scott, C. (2013). C
minor waltz: For jazz
quintet [Score].
Sydney: Craig Scott
Streamed music
An analysis of the
jazz piano style of
“What’s Your Story
Morning Glory”
(Williams, 1978,
track 8) reveals…
Williams, M. L.
(1978). What’s your
story morning glory.
On Mary Lou
Williams: Solo
recital, Montreux
Jazz Festival
[CD].Fantasy. Naxos
250
Music Library Jazz.
Interview – on radio
In a recent interview
with the Prime
Minister (Mitchell,
2009)…
Mitchell, N.
(Presenter). (2009,
October 16).
Interview with the
Prime Minister,
Kevin Rudd. In
Mornings with Neil
Mitchell
[Radio broadcast].
Melbourne Australia:
Radio 3AW.
Interview – on television
He demonstrated his
professionalism and
sensitivity in an
interview with
Raelene Boyle
(Denton, 2006)
and…
Denton A. (Producer
and Interviewer).
(2006, September
25).
Interview with
Raelene Boyle. In
Enough Rope with
Andrew
Denton.
[Televisionbroadcast]
Sydney, Australia:
Australian
Broadcasting
Corporation.
Motion picture (movie)
Jackson and Pyke
(2003) provide
evidence that belief
in a world…
Jackson, P.
(Director), & Pyke,
S. (Producer). (2003).
The lord of the rings:
The return of the king
[Motion picture].
NewZealand:
Imagine Films.
Note: Give the
country where the
movie was made –
not the city.
Podcast (audio)
Listening to the news
on my MP3 player
(Nolan, 2007) was a
new experience and I
decided…
Nolan, T. (Presenter).
(2007, April 28). AM:
News & current
affairs [Audio
podcast].
251
http://abc.net.au/news
/
subscribe/amrss.sml
Radio program –
broadcast
When discussing how
people write about
music, Koval
(2009)…
Koval, R. (Presenter).
(2009, November
19). The Book Show
[Radio broadcast].
Melbourne,
Australia: ABC
RadioNational.
Radio program –
transcript
The views of the
internationally
renowned author and
public speaker,
De Bono, prompted
me to follow up one
of the interviews
(Mascall, 2005)
which…
Mascall, S.
(Reporter). (2005,
February 14). Are we
hardwired for
creativity? In
Innovations [Radio
program]
[Transcript].
Melbourne,
Australia: ABC
Radio Australia.
http://www.abc.net.a
u/ra/innovations/stori
es/s1302318.htm
Speech
Amongst the views
expressed about war
and peace (Hodson,
2000) were…
Hodson, A. (2000,
November 11). Peace
in today’s world.
Remembrance Day
Speech presented at
the Australian
Veterans Memorial
Service, Lightning
Ridge, Australia.
Speech – online
In her ANZAC Day
speech (Clark, 2007),
the Prime Minister of
New
Zealand referred to…
Clark, H. (2007,
April 25). Prime
Minister’s 2007
Anzac Day message.
http://www.anzac.go
vt.nz
Television
advertisement
The problems of
teenage anxiety were
graphically captured
(Beyondblue,
2009)…
Beyondblue
(Producer). (2009,
November 29).
Beyondblue: Anxiety
[Television
252
advertisement].
Canberra, Australia:
WINTV.
Television program –
broadcast
Examining future
plans for Canberra’s
city area (Kimball,
2009)…
Kimball, C.
(Presenter). (2009,
September 4).
Stateline
[Television
broadcast]. Canberra,
Australia: ABC TV.
Always check the
television station’s
website and use the
transcript, if one is
available for direct
quotes.
Television program –
transcript
Cyclones often affect
Australia, especially
in the north
(McLaughlin,
2004) and it is
worthwhile…
McLaughlin, M.
(Presenter). (2004,
November 7).
Cyclone Tracy. In
Rewind [Television
program]
[Transcript]. Sydney,
Australia: ABC
TV.http://www.
abc.net.au/tv/rewind/t
xt/s
1233697.htm
THESIS OR DISSERTATION
Thesis or Dissertation –
print
Nurses working in an
acute care
environment tend to
experience a high
degree of workplace
conflict (Duddle,
2009, p. ii).
Duddle, M. (2009).
Intraprofessional
relations in nursing:
A case study
(Unpublished
doctoral thesis),
University of Sydney,
Australia.
Thesis or Dissertation –
retrieved from a
Database
The field of
engineering has
largely developed
around the positivist
philosophical
Hector, D. C. A.
(2008). Towards a
new philosophy of
engineering:
Structuring the
253
position (Hector,
2008).
complex problems
from the
sustainability
discourse (Doctoral
thesis).
AustralasianDigital
Theses database.
(Record No. 185877)
Note: End the
reference with the
unique number or
identifier assigned to
the
thesis/dissertation.
Thesis or Dissertation –
retrieved from the web
Lacey (2011, p. 12)
differentiates
between instrumental
violence and violence
inflicting injury for
its own sake.
Lacey, D. (2011).
The role of
humiliation in
collective political
violence (Masters
thesis, University of
Sydney,
Australia).http://hdl.h
andle.net/2123/7128
UNIVERSITY PROVIDED STUDY MATERIALS
Lecture / tutorial notes,
etc. – online
Septicaemia is one of
many infections
commonly acquired
in hospitals (Maw,
2010).…
Maw, M. (2010).
NURS5082
Developing nursing
practice, lecture 2,
week 1: Healthcare-
associated infections
and their prevention
[Lecture PowerPoint
slides].http://learn-
online.
ce.usyd.edu.au/
SOCIAL MEDIA
Facebook update
List the author’s name as
it is written
(including nicknames).
$52 million will be
provided to deploy
Australian civilian
troops (Rudd, 2009)
Rudd, K. (2009,
October 24).
Australian civilian
corps to help in crises
[Facebook
update].http://www.f
acebook.com/note.ph
254
p?note_id=20012404
3571&ref=mf
Blog post
- List the author’s name
as it is used in the posting
(including nicknames).
- For a blog comment, use
‘web log comment’
instead of ‘web log post’
and include the exact title
(including ‘Re:’ if
used)
The plight of the
flapper skate was
recently highlighted
(Keim, 2009)…
Keim, B. (2009,
November 18). ID
error leaves fish at
edge of extinction
[Web log post].
http://www.wired.
com/
wiredscience/2009/11
/extinction-error/
Video blog post (eg
YouTube)
The Prime Minister,
speaking about
Australia’s role in the
G20 forum
(Rudd, 2009)…
Rudd, K. (2009,
September 29).
Update on new G20
arrangements [Video
file].
http://www.youtube.c
om/watch?v=i8IdJ-
0S5rs
Twitter tweet
If the author uses their
name as their Twitter
‘handle’, do not alter its
format to follow the
convention of ‘Family
name, Initial(s).’
President Obama
announced the launch
of the American
GraduationInitiative
(BarackObama,
2009).
BarackObama. (2009,
July 15). Launched
American Graduation
Initiative to help
additional 5 mill.
Americans graduate
college by 2020:
http://bit.ly/gcTX7
[Twitter post].
http://twitter.com/Bar
ackObama/status/265
1151366
Note: This reference
would be filed under
‘B’, not ‘O’
Discussion group, list,
etc. – online
There are strongly
held views about
knowledge
management
(Weidner, 2007) and
from personal
Weidner, D. (2007,
June 11). KM
reducing in
popularity
[Discussion list
message].http://actkm
255
experience…
.org/ mailman/listinfo
/actkm_actkm.org
Wiki
Include the date retrieved,
as the information is
likely to change in these
sources.
The role of media
corporations in the
media literacy
movement is
discussed (“Great
debates in media
literacy”, n.d.)
Great debates in
media literacy:
Theory and practice
of media literacy.
(n.d.). In Wikiversity.
http://en.wikiversity.
org/
wiki/Great_Debates_i
n_Media_Literacy
PERSONAL COMMUNICATION AND EMAIL
Personal communication
Includes private letters,
memos, email, telephone
conversations, personal
interviews, etc. These are
cited in-text only, not in
the reference list.
J. Francis (personal
communication,
August 6, 2007) was
able to confirm that
the floods had not
reached their area.
Not included in
Reference List. Cite
in-text only.
Email – NEVER cite
addresses without
permission of the owner
of the address
Ms Coleman
(personal
communication, July
11, 2007) provided
details in an email
and we acted on that
information.
Not included in
Reference List.
Treat as personal
communication and
cite in-text only.
WEB RESOURCES
Web document: author
or sponsor given, dated
Note: A web document is
a file (e.g. a Word or PDF
file) found on the Web.
Often there are links to
Web documents from
Web pages. A Web
document is not the same
as a web page.
An RBA paper
(Simon, Smith, &
West, 2009) found
that participation in a
loyalty program and
access to an interest-
free period…
Simon, J., Smith, K.,
& West, T. (2009).
Price incentives and
consumer payment
behaviour.
http://www.rba.gov
au/PublicationsAnd
Research/RDP/RDP2
009-04.html
Web document: author
or sponsor given but not
dated
The Commonwealth
Scientific and
Industrial Research
Organisation
(CSIRO) is designing
Commonwealth
Scientific and
Industrial Research
Organisation.(n.d.).
Reducing Australia’s
256
several energy-
efficient electric
machines to reduce
greenhouse gas
emissions (CSIRO,
n.d.).
greenhouse
emissions
factsheet.http://www.
csiro.au/
resources/ps282.html
Web page with no page
numbers
Include in in-text
references: A paragraph
number with the
abbreviation ‘para’ (count
paragraphs if numbers are
not visible)
OR
- A section heading and
paragraph number
(e.g. Introduction, para.
3). A long section
heading may be shortened
and enclosed
in double quotation
marks.
Note: Because Web pages
can be updated, you must
include the date on which
you accessed the source.
Usually the author or
creator of a work is
the copyright owner
(University of
Sydney, 2010, “Who
owns copyright?”,
para. 1).
Note: The heading of
the section was “Who
owns copyright?”
University of Sydney.
(2010). Guide to
copyright.
http://sydney.edu.au/
copyright/students/
coursework.
shtml#who
Web source – no author
or sponsor given
When there is no author
for a source you
find on the Web (whether
it be a Web
document or a Web page),
the title moves to the first
position of the reference
entry.
If the title is long, use an
abbreviated version of it
for in-text citations. Insert
This vaccine is 6
times more efficient
than vaccines
previously used to
immunise against the
condition (“New
child vaccine”,
2001).
New child vaccine
gets funding boost.
(2001).
http://news.ninemsn.
com.au/health/story_
13178.
Asp
257
double quotation marks
around the title.
Note: If you were citing
the title of a book,
periodical, brochure or
report, you would
use italics rather than
double quotation marks.
Website –entire website
The new website of
the Department of
Education,
Employment and
Workplace Relations
(http://www.deewr.g
ov.au) includes
useful information on
current government
education policy.
Not included in
Reference list.
Source: (American Psychological Association, 2020).
Chapter Summary
When writing a research paper, you will have to borrow
information from other people in order to prove your points.
Anytime you borrow information from another source, you
must show in your paper where you found the information.
Once you do not cite your source, it is called plagiarism. It is in
this context that this chapter examines the appropriate format of
referencing using the APA style. Thus, one of the duties of any
academic is project writing and supervision in order to
contribute to individual and societal development. To be able to
excel in this direction, constant and continuous education is
imperative. Therefore, researchers must adopt an appropriate
format of referencing the materials they have consulted in the
course of writing their research project.
258
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Index
A
Administration ... . 3, 88, 226, 246
Adorno ..................................... 14
Advertising ................................. 3
Aesthetic..................................... 5
Agricultural Science ................... 3
Alienation ................................. 14
American ....... 19, 59, 79, 90, 113,
217, 229, 231, 234, 240, 241,
249, 254, 257, 258, 265
Antecedent ............................... 15
Anthropology ..................... 28, 63
Arbitrary ............................. 39, 41
Archimedes ................................ 7
Artistic ................................ 19, 48
Autonomous ....................... 32, 33
B
Barthes In Chang ...................... 40
Bazerman ......................... 30, 259
Billig ................................ 36, 259
Bisexual .................................... 14
Blackledge .................. 33, 34, 259
Bourdieu’s Habitus ................... 34
Broadcast Media......................... 3
Business ............................. 3, 249
C
CDA . …… 21, 22, 23, 24, 25, 26,
27, 28, 29, 33, 34, 35, 36, 37,
77, 260, 263
Certificates ................................. 3
Chandler .................... 38, 40, 259
Chang ......................... 39, 41, 259
Civil Servants .......................... 28
CL ............................................ 34
Connotative Level.................... 39
Consequences ............ 15, 16, 259
Creswell . ….9, 10, 11, 13, 16, 20,
79, 113, 115, 211, 216, 219,
260
Critical Linguistics ............ 26, 34
Crotty ....................................... 13
CSM ........................... . 21, 71, 77
Culture .... .13, 23, 38, 48, 49, 205
D
Denotative Level...................... 39
Denzin And Lincoln ........ 20, 217
Discrimination ............. 14, 21, 23
Dissertation .. … 3, 216, 221, 222,
227, 253
E
Eclectic .................................... 22
Economics ................................. 3
Eiffel Tower ............................. 39
El-Sharkawy .... ….22, 24, 26, 29,
35, 260
Empirical Science .................... 11
Engagement ....................... 30, 84
Entertainment .................. 40, 101
Ethical Qualities ........................ 5
Ethnic ................. 14, 26, 135, 261
Ethnicity ...................... 15, 25, 82
Extra-Vocalization ................... 30
268
F
Fairclough . 22, 23, 24, 27, 29, 35,
36, 260
Feminists .................................. 14
FGD ...................... . 21, 58, 59, 77
Film ............................ 25, 52, 100
Foucault’s ................................. 34
Freire ........................................ 14
Fundamental ...... 38, 44, 111, 121,
141, 220, 227
G
Gay ........................................... 14
Gender Issues ........................... 37
Generalizability .......................... 6
Gopaldas........................... 20, 261
Gunter............. 3, 83, 95, 100, 261
H
Habermas ........................... 14, 22
Halliday And Bernstein ............ 34
Haradhan .......................... 20, 261
Hedging .................................... 30
Hegemony ................................ 35
Heterogeneity ........................... 34
Historical ..... ……..13, 17, 22, 23,
24, 28, 49, 50, 95
History .......................... 3, 73, 171
Humanistic ....................... 6, 7, 17
I
Ideologies .. …..23, 25, 27, 28, 33,
35, 37, 40, 48
IDI ................................ 21, 52, 77
Indexical Stage ......................... 39
Interdiscursivity.................. 29, 33
International 3, 236, 245, 259, 261
Interpretations ... 5, 20, 22, 24, 30,
48, 141, 176
Interpretivism .......................... 12
Intertextual ................... 29, 30, 32
Intertextuality ........ 29, 30, 31, 33
Intra-Vocalisation .................... 30
Investigates ........................ 20, 77
Issues Of Racism ..................... 37
J
Jahedi Et Al. ............................. 21
Jorgensen And Phillips ...... 21, 28
Justice ........ 14, 17, 116, 185, 216
K
Knowledge .... ……3, 4, 7, 11, 12,
16, 19, 20, 32, 34, 50, 56, 63,
64, 70, 77, 123, 134, 142, 161,
171, 198, 200, 204, 209, 211,
214, 215, 218, 236, 237, 254,
263
Kurfi ... …..20, 21, 41, 42, 51, 53,
60, 233, 262
L
Law ............................ 3, 126, 244
Legitimation ............................ 25
Lesbian .................................... 14
Linguistic .. …..22, 23, 24, 29, 30,
33, 34, 35, 36, 44, 234
Linguistically ..................... 30, 35
Literary Studies ......................... 3
Littlejohn And Foss ....... 4, 5, 6, 7
Lodges And Nilep .................... 27
269
M
Magazine .......................... 42, 242
Maikaba ..... ………4, 80, 94, 102,
141, 262
Manipulation ..... 21, 25, 105, 109,
110, 112
Manufacture ............................. 25
Marcuse .................................... 14
Marxists .................................... 14
Mathematical . ……..19, 132, 135,
141, 168, 186
Mertens....................... 14, 15, 263
Metaphor .................................. 30
Methodological .... … 34, 42, 189,
211, 212
Methodologies ... ……29, 32, 113,
141, 264
Meyer ............................... 23, 263
Micro-Discursive...................... 36
Miles And Huberman ......... 43, 45
Misinterpretation .............. 37, 161
Morphology .............................. 27
Msughter .... …….. 3, 80, 95, 230,
231, 233, 263
Music .... 25, 49, 52, 243, 249, 251
N
Neumann .................................... 3
O
Olofin ................................. 4, 263
Oppression ......................... 14, 15
P
Patton ............. 16, 43, 47, 54, 264
Peircean Model......................... 38
Phenomena ............ 7, 38, 73, 106
Phillips And Burbules .............. 11
Philo ................................. 37, 264
Philosophical .. ……..8, 9, 10, 14,
15, 16, 17, 28, 113, 218, 220,
252
Phonology ........................ 24, 262
Photographic ............ 39, 159, 259
Pictures .................. 25, 38, 49, 52
PO .............................. . 21, 62, 77
Political ……3, 14, 15, 17, 22, 23,
24, 26, 28, 33, 35, 36, 48, 49,
52, 103, 175, 181, 253
Political Science ................ 3, 266
Politician Speakers .................. 37
Polysemic ................................ 41
Postcolonial ....................... 14, 49
Post-Positivism .................. 11, 13
Post-Positivist .................... 11, 14
Power .. …..14, 15, 21, 22, 23, 24,
25, 26, 27, 28, 29, 34, 35, 36,
37, 101, 116, 129, 167, 168,
245, 259
Powerful ……21, 25, 37, 52, 106,
159
Pragmatic ............... 5, 17, 24, 117
Presentations ............................ 19
Print Media ................................ 3
Psychological ... …….19, 79, 113,
217, 229, 231, 234, 240, 243,
257, 258, 264
Public Relations ......................... 3
Punch ....................... 20, 201, 264
Q
QCA ............................. 21, 42, 77
Quantification . 42, 61, 62, 96, 97,
98
270
Queer Communities ................. 14
R
Racial ......................... 14, 26, 216
Recontextualisation .................. 33
Research………….3, 4, 8, 12, 69,
80, 89, 90, 105, 109, 111, 113,
121, 141, 156, 167, 191, 197,
200, 201, 204, 205, 209, 210,
217, 220, 221, 225, 226, 227,
245, 255, 258, 260, 261, 262,
263, 264, 265, 266
Research Project ... ….3, 159, 187,
194, 197, 198, 202, 205, 208,
209, 220, 223, 257
Researchers ……..3, 8, 10, 12, 13,
14, 16, 19, 20, 28, 32, 36, 40,
48, 49, 54, 61, 62, 75, 79, 81,
89, 90, 91, 93, 95, 96, 97, 108,
110, 111, 113, 121, 122, 123,
124, 125, 126, 131, 133, 135,
137, 142, 155, 157, 161, 162,
163, 164, 167, 168, 171, 174,
176, 181, 184, 188, 190, 198,
199, 200, 202, 203, 204, 205,
207, 208, 212, 215, 216, 217,
219, 229, 257
Rhetoric ...................... 24, 26, 259
Rose ................ 38, 39, 40, 41, 264
S
SA .............................. . 21, 37, 77
Saussurian ................................ 38
Schegloff .......................... 35, 264
Scholarship .. … 4, 6, 7, 17, 27, 33
Scientific .... …….. 3, 6, 7, 11, 17,
19, 24, 62, 63, 77, 102, 106,
121, 140, 141, 155, 186, 187,
210, 218, 261
Scollon Studies ........................ 24
Semantics ........................... 24, 27
Seminars .................................. 28
Semiotic ................. 25, 34, 38, 40
Semiotic Analysis . …. 21, 37, 38,
41, 77
Semiotic Dimensions ............... 25
Snapshot .................................. 20
Social Approaches ................... 22
Social Scientific ......................... 6
Societies ............................. 3, 261
Sociolinguistic ......................... 23
Sociology ............... 28, 33, 48, 63
Sociology ........................... 3, 265
Sociopolitical ............... 25, 28, 35
Sophisticated .... 38, 136, 165, 179
Sound ....................................... 25
Speech Acts ....................... 24, 26
Standardization .......................... 6
Standardized .......... 43, 45, 54, 98
Strategies .. 15, 24, 25, 26, 36, 76,
90, 116, 217
Symbolizing ............................. 39
Symiotic Analysis .................... 37
Syntax ........................ 24, 27, 158
Systematic …… 4, 27, 42, 43, 44,
63, 68, 69, 71, 80, 81, 89, 95,
96, 97, 98, 99, 101, 102, 114,
133, 140, 160, 186, 243
T
Tashakkori And Teddlie .... ….16,
115, 188
Teachers ............................ .28, 72
Technicalities ............................. 3
Theatre Art ................................. 3
271
Theoretical Premises ................ 28
Theoretical Synthesis ............... 34
Transparent ....................... 43, 160
Transsexual .............................. 14
TTA ............................ . 21, 48, 77
Typologies ............ . 6, 10, 17, 186
Typologies Of Scholarship ........ .5
U
Unsystematic ...................... 22, 27
V
Van Dijk …22, 24, 25, 26, 34, 35,
265
Van-Leeuwen ................... 32, 265
Verbal ................... 25, 26, 52, 109
Voice .... 15, 30, 31, 72, 159, 199,
224
W
Wang ......................... 30, 31, 265
Weiss And Wodak ........... 22, 259
Wodak .... 23, 24, 27, 28, 35, 263,
265, 266
World-Region .......................... 25
Y
Ya’u ................................... 3, 263
Z
Zaria ........................................... Ii
