Research Methodology

RESEARCH
METHODOLOGY
A Beginners Approach
BY
MAKUMBA S ARNOLD

Research Methodology Makumba S Arnold Page 2
CHAPTER ONE
Meaning of Research project
RESEARCH can be defined as a process of enquiry and investigation; it is systematic,
methodical and ethical; research can help solve practical problems and increase knowledge.
Research has been defined in a number of different ways.
 A broad definition of research is given by Martyn Shuttleworth - "In the broadest sense of
the word, the definition of research includes any gathering of data, information and facts
for the advancement of knowledge."
 Another definition of research is given by Creswell who states - "Research is a process of
steps used to collect and analyze information to increase our understanding of a topic or
issue". It consists of three steps: Pose a question, collect data to answer the question, and
present an answer to the question.
 The Merriam-Webster Online Dictionary defines research in more detail as "a studious
inquiry or examination; especially : investigation or experimentation aimed at the
discovery and interpretation of facts, revision of accepted theories or laws in the light of
new facts, or practical application of such new or revised theories or laws".
 Systematic investigation to establish facts
 A search for knowledge
Research Project: Research into questions posed by scientific theories and hypotheses
The Importance of Research Project
A research project is important because it enables the researcher to;
 Review or synthesize existing knowledge
 Investigate existing situations or problems
 Provide solutions to problems
 Explore and analyze more general issues
 Construct or create new procedures or systems
 Explain new phenomenon
 Generate new knowledge
 Or a combination of any of the above!
 Understanding how knowledge is constructed
 Self confidence
 Understanding that claims require supporting evidence
 Clarification of a career path

Identifying and stating a research problem:
What Is a Research Problem?
A research problem, or phenomenon as it might be called in many forms of qualitative
research, is the topic you would like to address, investigate, or study, whether descriptively or
experimentally. It is the focus or reason for engaging in your research. It is typically a topic,
phenomenon, or challenge that you are interested in and with which you are at least somewhat
familiar.
Research Problem
 A research problem is a terminology for a topic that has been narrowed down and refined
appropriately for research. It is the why of the study. It is a hypothesis or a question of
interest to a researcher which can only be tested or answered through the collection and
analysis of fresh data.
 A research problem goes beyond surface problems which do not demand collection and
interpretation of data. Research is usually conducted because a deficiency or a need has been
identified.
 A research problem refers to what the researcher has identified as existing in literature,
theory or practice - a condition which needs to be probed and a solution found. It may arise
from issues, difficulties, current practices or problems that need to be solved or better
understood, or it may arise from deductions from existing theories related to the current
social or political issues, practical situations or personal experiences. It may be an issue that a
researcher wants to describe, an event that has been observed and needs to be explained, or a
problem for which a solution is needed. Or it may be a state of affairs that needs to be
changed, or anything that is not working as well as it ought to, or a difficulty to be
eliminated.
Identifying a Research Problem
 One of the most difficult tasks for beginning researchers is how to identify a research
problem. Students usually have so many ‘problems’ in mind, but such problems are not
always research problems. A research problem is different from ordinary or general
problems: it is a need or a difference that can only be solved through collection and analysis
of data.
 Some of the common pointers to research problems are issues which attract attention and
may need investigation, unanswered questions, missing links, imbalances, unsatisfactory
states of affairs, and problems of adjustment to technological advances. The list is endless. It
is up to the researcher to look into these areas and identify problems that require research to
solve. But how exactly does one identify a research problem?
 To identify a research problem, a researcher should answer YES to the following questions:

1. Is there a perceived inconsistency or difference between “what is” (the actual) and “what
should be” (the ideal)? In other words, are you seeing what you want to see or are you seeing
something different? If your answer is NO, then there is no problem because things are just
as they should be. You now need to look elsewhere for a problem. But if the answer is YES,
then there is a problem, but it may not necessarily be a research problem. The YES scenario
should lead to the second question.
2. Is there a question about why there is a difference? In other words, is the difference
understood? If there is no question about the difference, then there is no research problem
because the difference has been, or can be explained from the available facts and data, and
there is no need for research. But if the answer is YES, then the difference is not understood,
and it cannot be explained using the already available data. Hence a problem exists, but it
may not necessarily be a research problem. The YES scenario should lead to the third
question.
3. Are there possible and reasonable solutions or answers to the difference? If the answer is
NO, then the problem cannot be investigated through research since it is not possible to
generate or formulate hypothesis. Hence it is not a research problem. But if the answer YES,
then there is a research problem, and these possible answers now form the basis of
investigation.
Examples of Research Problems;
 Early Marriages in Somalia: An examination of the causes and effects of early marriages
on Female students undertaking undergraduate studies in Universities
 Teaching Strategies: The impact of various teaching strategies in relation to students
performance
 Clan Disputes in Sanaag: Factors causing clan disputes in Sanaag and methods of conflict
resolution
Where Do You Find a Problem or Phenomenon to Study?
Since a research problem is usually something you have some knowledge of, that personal
experience is often a good starting point. Realistically, you have to select something that you are
interested in, because you are going to commit yourself to a significant investment of time and
energy. Thus, if you are not personally interested, it will be difficult to sustain the effort needed
to complete the research with any measure of quality or validity. You may want to talk to
teachers, counsellors, administrators, psychologists, or others about some of the problems they
face

What Is a Research Question?
A research question is a way of expressing your interest in a problem or phenomenon. Research
questions are not necessarily an attempt to answer the many philosophical questions that often
arise in schools, and they are certainly not intended to be an avenue for grinding personal axes
regarding classroom or school issues. You may have more than one research question for a
study, depending on the complexity and breadth of your proposed work. Each question should be
clear and specific, refer to the problem or phenomenon, reflect an intervention in experimental
work, and note the target population or participants
Qualities of a Good Research Problem
A well stated research problem statement should:
1. Clarify what exactly is to be solved or to be determined. It should be written in a clear, non-
technical language avoiding jargon, clearly identifying an area of concern. It must carefully
fit into the broader context of current theories and relevant research without making
assumptions or unsupported claims or statements.
2. Contain the variables and the target population that is to be studied.
3. Restrict the scope of the study to a specific question or questions, hypothesis or hypotheses;
and be sufficiently limited in scope to be manageable.
4. Be feasible and amenable to research; not be too wide and data for solving it should be
available. Whether or not data is available is crucial because usually a researcher may not
have time to collect fresh data for the background information. Hence, a researcher needs to
be sure of the sources of data and the means of accessing it.
5. Not raise ethical issues. Ethical issues are paramount in research and a good research
problem should not raise or overlook ethical concerns.
6. Be original. Originality is important in research because knowledge cannot be advanced by
duplicating solutions to problems that have already been solved.
7. Be significant: it should result in advancement of knowledge or significant improvement of
life. There should be some pay off if the uncertainties about the problem are resolved or at
least reduced. A good problem should explore an important question, address a recognizable
and significant need, and make a useful contribution to knowledge. It must be current and
timely.

Justification for Research:
What makes a good research question is often in the eye of the author, but there are several
general best-practices criteria that can be used to assess the justification for research.
1. Is the question scientifically well-posed, i.e. is it stated in a hypothetical form that leads
to a research design and analysis with scientific credibility?
2. Does the research question require data that is easy to get to or attainable at a reasonable
cost or effort?
3. Is the research question posed in a way that can explain variability, different outcomes
under different conditions?
4. Are the units of analysis (observation) clearly identified?
5. Is the question posed in a way that more than one result is possible, i.e. the working
hypotheses can be refuted?
6. Does the research extend our understanding of the phenomena being investigated; does it
elaborate, extend, or fill in gaps in our present knowledge?

CHAPTER TWO
RESEARCH PROJECT PRPOSAL
Types of Research Projects
Types of research projects are;
Quantitative Research
The emphasis of Quantitative research is on collecting and analyzing numerical data; it
concentrates on measuring the scale, range, frequency etc. of phenomena.
The researcher focuses on variables of factors that can be proved and verified.
This type of research, although harder to design initially, is usually highly detailed and structured
and results can be easily collated and presented statistically.
Qualitative Research
Qualitative research is more subjective in nature than Quantitative research and involves
examining and reflecting on the less tangible aspects of a research subject, e.g. values, attitudes,
perceptions, feelings.
It seeks to describe and analyze the culture and human behaviour and their groups.
Although this type of research can be easier to start, it can be often difficult to interpret and
present the findings; the findings can also be challenged more easily.
Exploratory Research
Exploratory research is undertaken when few or no previous studies exist. The aim is to look for
patterns, hypotheses or ideas that can be tested and will form the basis for further research.
Typical research techniques would include case studies, observation and reviews of previous
related studies and data.
Descriptive Research
Descriptive research can be used to identify and classify the elements or characteristics of the
subject, e.g. number of days lost because of industrial action.
Quantitative techniques are most often used to collect, analyze and summarize data.
Analytical Research
Analytical research often extends the Descriptive approach to suggest or explain why or how
something is happening, e.g. underlying causes of industrial action. An important feature of this
type of research is in locating and identifying the different factors (or variables) involved.
Predictive Research
The aim of Predictive research is to speculate intelligently on future possibilities, based on close
analysis of available evidence of cause and effect, e.g. predicting when and where future
industrial action might take place

Basic/Applied Research
The primary aim of Basic Research is to improve knowledge generally, without any particular
applied purpose in mind at the outset. Applied Research is designed from the start to apply its
findings to a particular situation.
Deductive/Inductive Research
Deductive
Deductive research moves from general ideas/theories to specific particular & situations: the
particular is deduced from the general, e.g. broad theories.
Inductive
Inductive research moves from particular situations to make or infer broad general ideas/theories.
Examples of Deductive/Inductive Research in Action
Imagine you wanted to learn what the word ‘professional’ meant to a range of people.
Deductive Approach
It is clear that you would want to have a clear theoretical position prior to collection of data. You
might therefore research the subject and discover a number of definitions of ‘professional’ from,
for example, a number of professional associations. You could then test this definition on a range
of people, using a questionnaire, structured interviews or group discussion.
You could carefully select a sample of people on the basis of age, gender, occupation etc.
The data gathered could then be collated and the results analyzed and presented.
This approach offers researchers a relatively easy and systematic way of testing established ideas
on a range of people.
Inductive Approach
If you adopted this approach you might start by talking to a range of people asking for their ideas
and definitions of ‘professional’. From these discussions you could start to assemble the common
elements and then start to compare these with definitions gained from professional associations.
The data gathered could then be collated and the results analyzed and presented.
This approach might lead you to arrive at a new definition of the word – or it might not! This
approach can be very time-consuming, but the reward might be in terms of arriving at a fresh
way of looking at the subject.
Selection of a Project
Factors to consider when selecting a research project:
I. Type of project
II. Sources of data
III. Quality specification
IV. Available technology, materials and equipment
V. Personal Requirements
VI. Time
VII. Finances available

Formulation of project objectives
Project Objectives
Project objectives are the specific intentions for which the project works to achieve them within
a stipulated time. They should directly address the problem mentioned in the Problem Statement
or Research Question. They should be specific: the more specific it is the better to design
activities, indicators and the Logical Framework Analysis
These should be SMART: Specific, Measurable, Achievable, Relevant and Time-bound.
Tips:
 Think about what success means for your project and how you would show that success
 Refer to the results you expect from the project
 Describe the focus population and the desired change among the population
 Include the location and time period for each objective
 Reflect the intended changes in systemic conditions or behaviours that must be achieved
to accomplish the goal/strategic objective
 Objectives should have measurable indicators which show what, when, and how
conditions, behaviours, and practices will change
 Objectives must be verifiable at some point during the execution of the project
Writing a Hypothesis
Research Hypotheses
 A research hypothesis is a proposal about a solution to a problem: It is an “intelligent” or an
“educated” guess, or a tentative solution to a problem. Hypotheses are declarative statements
on the relationships between two or more variables on the nature of some phenomenon.
 They form the elements for testing to enable the researcher make an opinion about certain
phenomenon being investigated, and contain the variables which the researcher wishes to
consider or test in order to observe their actions or reactions so that meaningful conclusions
can be drawn.
 A hypothesis is some prediction of some sort, regarding the possible outcomes of a study.
 Hypotheses, as opposed to questions, are stated if the researcher has an idea of the possible
solutions to the problem under investigation, and only wants to find out if the ‘solutions’ hold
under the certain circumstances or not. While purpose indicates the anticipated contributions
of the study, and specific objectives indicate what will be done or measured, hypotheses
specify the expected relationships between the variables.

Types of Hypotheses
 Hypotheses may be stated either in a null (non-directional) form and symbolized as (Ho), or
in alternative and directional forms and symbolized as HA and H1 respectively.
 A null hypothesis states that there is no relationship between the variables being studied or
that no difference will be found in the dependent variable due to manipulation of the
independent variable. It is referred to as null because since scientists tend to state that
differences between a sample and the population is a sampling error and significantly
different from zero.
 An alternative hypothesis generally states a relationship between the variables being
investigated, or that a difference will occur in the dependent variable due to the manipulation
of the independent variable.
Advantages and Disadvantages of stating Research Hypotheses
A well stated hypothesis enables the researcher to:
1. Think more deeply about the possible outcomes of the study. Elaborating a question by
stating a hypothesis leads to a more detailed understanding of what the question implies and
exactly what variables are involved.
2. Make specific predictions based on prior evidence or theoretical arguments. If these
predictions are borne out by subsequent research, the entire procedure gains both in
persuasiveness and efficiency.
3. Focus the research on specific areas of investigation.
Hypotheses have their weaknesses too. For example;
1. Hypotheses lead to bias on ten part of the researcher. Once hypothesis are stated, the
researcher may be tempted to arrange the procedure to bring about the desired results.
2. Hypotheses are unnecessary or inappropriate in some types of research, like in qualitative
research designs.
3. Focusing attention on hypothesis may prevent the researcher from noting other phenomena
that might be relevant or important to the study. For example once hypotheses are stated,
they become the sole focus of the study and all other issues, no matter how significant,
become irrelevant.

What is a research project proposal?
This is a request to implement a project or study with a detailed plan of action.
Importance of a project proposal
The research proposal can serve many useful functions.
 The most important is that it helps you to think out the research project you are
about to undertake and predict any difficulties that might arise.
 For those who aren't quite sure what their focus will be, the research proposal can
be a space to explore options -- perhaps with one proposal for each potential topic
(which can then be more easily compared and evaluated than when they are still
just ideas in one's head).
 Research proposals can be effective starting places to discuss projects with your
professors, too.
 A professor who is initially sceptical about a project may be able to imagine it
more easily after reading a well written research proposal (this doesn't mean he or
she will approve the topic, especially if there are significant potential difficulties
that you haven't considered).
 Once you have begun your research project, a research proposal can help you to
remain on track -- and can also remind you why you started this project in the first
place!
 Researchers very often begin to lose heart about two thirds of the way into a
project when their research hits a snag or when they are having problems
developing a thesis, organizing the ideas, or actually starting to write. Rereading
the initial research proposal, especially "Significance" can reenergize the project
or help the researcher to refocus in an effective manner.
Preparation of a Research Project Proposal
When preparing a project proposal you should be careful to include the following information;
 Introduction
 Objectives
 Problem Statement
 Literature Review
 Methodology
 Analysis
 Budgeting
 Timing

1. Introduction
The introduction should be as brief as possible (a paragraph or two). Whatever you do, don’t
ramble on for pages; you need to make this part of the proposal clear and crisp.
In the introduction, you need to give a sense of the general field of research of which your area is
a part. You then need to narrow to the specific area of your concern.
2. The Objectives
Objectives
 Objectives state the immediate intentions of the study, indicating the variables which will be
examined and measured.
 They constitute promises by the researcher that certain activities will take place, that certain
specific variables will be examined, and certain specific targets will be realized.
Why State Objectives?
Objectives are critical in any research process. Just a ship without an intended can go anywhere
in the waters, so is a study without objectives. It may attempt to achieve everything and in the
end achieve nothing constructive. Objectives are useful in research because:
1. They provide focus for the study by specifying its intended outcomes. Because the
researcher has an end in mind and he/she can work consciously towards that end.
2. They narrow the scope of the study to specific issues. This helps the researcher to
generate specific hypotheses and to develop research questions.
3. They enable the researcher to select a research design or method. Objectives that deal
with views, for example, require a different method from those that deal with effects; and
those that deal with associations require different designs from those that deal with lived
experiences.
4. They enable the researcher to select suitable tools for data collection and appropriate
methods for data analysis.
5. They enable the researcher to evaluate the outcomes of the study. It is by comparing the
intended outcomes against the actual that a researcher can tell whether or not the study
was successful.

Qualities of a Good Research Objective
It is very important that a researcher states good objectives as poorly stated objectives can
misguide the study. Research objective must be SMART. SMART is an acronym for Specific,
Measurable, and Attainable, Realistic and Time-bound or timeliness.
1. An objective is specific if it communicates clearly and explicitly, the intended outcome of the
study. It should be short, concise and precise, and should use words which do not lend
themselves to multiple interpretations. An objective should have a clear focus and should
relate only one operation of the independent variable to the dependent variable, and vice-
versa.
2. An objective is measurable if it is stated in terms of observable outcomes; and if it is
expressed in terms of external characteristics or determinants on which data can be collected.
Objectives should be written using active verbs (words that describe action such as find out,
assess, determine, describe, establish, etc). But use of words without terminal characteristics
such as know, understand, feel, enjoy, master should be avoided as they do not signify
readily observable or easily measurable attributes.
3. An attainable is feasible and manageable in the sense that it can be answered through
collection of data. An objective should not be stated on which data cannot be collected. An
objective is manageable if it can be accomplished within the constraints of the available
finances, equipment, personnel and even time.
4. An objective is realistic if it is of reasonable level of difficulty. An objective should neither
be too hard nor be too simple. At any level and for every study, a researcher should generate
objectives that are within the scope of the study.
5. An objective is time-bound if the period within which it will be achieved is stated, and if it
can be accomplished within the stated time. Usually researchers have set times within which
to submit their reports. Do not state objectives which cannot be achieved within the
stipulated period. An objective must also be timely; it should neither come too late nor too
early. The challenge of the researcher therefore is to (i) formulate objectives that are
achievable within the available time; and (ii) state the time frame within which each
objective is to be achieved.
3. The Problem Statement
A research problem is an issue that puzzles the researcher like say: Why students still don’t
enrol in the university even when it is within their area.
This research question may not be a question as such, but rather a statement of a problem to be
investigated.
These problems are what results in a problem statement.

4. Literature Review
 One of the requirements of research is a demonstration by the researcher of thorough
understanding of the issues and facts surrounding the problem under investigation. In order to
understand the problem at hand, a researcher must extensively read a lot of information
materials that relate directly to the topic under investigation. This is referred to as literature
review.
 Literature review is the systematic identification, location, retrieval, analysis and evaluation
of documents containing information that are related to the research problem. It also entails
analyses of casual observations and opinions related to the planned research. A researcher
should develop a thorough understanding of, and insight into, previous works and trends that
have been recorded pertaining to the research problem.
Why Review Literature?
A good literature review:
1. Defines the research problem and classifies and refines it. Literature review isolates key
issues pertinent to a study and provides the knowledge needed to convert a tentative
problem into a detailed and concise plan of action. It provides the dimensions and the
limits of the problem area and the extent to which the answer is already known, thus
delimiting the problem.
2. Provides insight into methods, measures, subjects and techniques already used, or proven
useful or otherwise by other researchers, and thus leads to improvement of design
selection.
3. Prevents unintended duplication of previous studies by identifying what has already been
done that relates to the research problem. Literature review tells the researcher what has
been done and what needs to be done. Studies that have been done provide the researcher
with reliable information on what should be done.
4. Provides the means of getting into the frontiers of a particular field of knowledge. Until
one has learnt what has been done and what remains to be done, it is not possible to
develop a study that will advance knowledge in that particular field. It is the literature
review that forms the basis upon which a significant research should be built. Without an
effective literature review, the rest of the research work is likely to be shallow and naïve.

Sources of Information for Literature Review
There are three main sources of information for a literature review: the preliminary, the primary
and the secondary sources.
Preliminary Sources
 Preliminary or general sources refer to materials which a researcher consults first to help him
or her locate other sources related to the research problem. The preliminary sources are in
themselves not information that the researcher is seeking for literature review, but are just
pointers to that information; they direct the researcher on where to get that information. A
table of contents is an example of a preliminary source.
Primary Sources
 Primary sources are direct descriptions of an occurrence by individuals who actually
experienced the occurrence. In research, this generally means description of a study by
persons who actually carried it out. Primary sources include journals, reports, dissertations
and theses, conference papers, etc. primary sources are preferred over other sources because
they provide detailed accounts of events in specialized fields. But they have a narrow scope
because they provide a lot of details in a small area.
Secondary Sources
 Secondary sources are materials where authors discuss or describe the works of others. They
are works presented by people who were not direct observers or participants in the events
being described, but are merely reporting on the work of someone else. The most popular
secondary sources are textbooks, and Encyclopaedia. In a textbook on Management for
example, an author may describe several studies that have been done on education as a way
of illustrating an idea or a concept. But the author did not personally conduct the studies
referred to.
 Secondary sources are preferred over other sources because they combine knowledge from
many primary sources into single publications. They also eliminate and simplify much of the
technical materials that may not be of interest to the general readers, and provide a quick and
relatively easy method of obtaining a good overall understanding of a field. However, with a
secondary source, one cannot be sure of the changes that have been from the original source
by the secondary author. In the process of combining and simplifying many primary sources,
a secondary source may leave out information that the reviewer may need to know. Therefore
literature review should, whenever possible, be based on primary source.

5. Research methodology
The term methodology refers to the overall approaches & perspectives to the research process
as a whole.
You do not have to describe the methodology to be used in great detail, but you should justify its
use over other methodologies. For example, you could explain the reasons for using:
 A certain paradigm or theory
 Qualitative or quantitative research
 A case study of a specific kind
 Surveys, correlation experiments, field studies, specific statistical measurements, etc.
 Certain dependent or independent or moderating variables a particular sampling frame
and the size of a sample
 You could also explain how you are proposing to: have access to the data and analyze the
data.
6. Analysis
This refers to examining what has been collected in the research and then make deductions.
The researcher must indicate how they intend to analyze and interpret the data collected.
This involves data collation and how it will be studied and documented.
7. Budgeting
The researcher should be able to plan on how to utilize the financial resources he or she may
have. This is a list of items and activities that will be involved in the research project and the
respective cost.
8. Timing
The proposal should indicate the activities to be done and the order and time for them to be done.
A timetable can be drawn to assist in guiding the researcher.
Note that:
• The timetable is approximate only, and things always take longer than you think!
• Extra time needs to be allowed for the start and finish of the project
• The timetable does not commit you to anything (though obviously it helps if you can follow it).
List of references
This must be provided in the usual scholarly fashion. It helps to convince your reader that your
proposal is worth pursuing if you can identify literature in the field and demonstrate that you

understand it. It makes a very strong impact if you can identify where there is a research gap in
the literature that your proposal hopes to fill. This is your contribution to the scholarly
conversation.
In-text references should be provided for all sections of the proposal with the exception of the
research plan and timetable.
Bias and Prejudice in research
Biases are human tendencies that lead us to follow a particular quasi-logical path, or form a
certain perspective based on predetermined mental notions and beliefs.
Research bias
Bias exists to some degree in every study, but the presence of bias is not always a signal that the
study should be totally discredited. Readers of research should know how bias can creep into a
study, and identify whether and where bias has occurred. Readers then determine whether the
researchers have accounted for bias, and to decide if it is a major concern.
Selection Bias
Selection bias occurs when individuals or groups being compared are different. Two
main factors that can contribute to selection bias are self selection, when the sample
selects itself, and convenience sampling, when individuals are selected because they are
easy to obtain. To help insure external validity, subjects in the study should be very
similar to the population in which study results will be applied.
Measurement Bias
The research design should accurately and truthfully measure the research question.
Measurement bias occurs when the research design does not match the research question;
for example, a questionnaire aims to assess the learning objectives of a training session
but measures only the learner’s satisfaction with the session. A measurement tool that is
not accurate could cause instrument bias. For example, an unbalanced weight scale would
skew the results of a study.
Interviewer Bias
The interviewer’s opinions, prejudices, and even non-verbal cues, when displayed during
the interview process, can bias or influence study results.
Response Bias
Subjects may shape their responses in order to please the interviewer. Subjects may also
believe they know the expected findings and change behaviours to match. Finally,
subjects may believe they are the control or experimental group which is often called
the placebo effect.

Prejudice:
 Prejudice refers to beliefs, thoughts, feelings, and attitudes that someone holds about a
group. A prejudice is not based on experience; instead, it is a prejudgment, originating
outside of actual experience
 Prejudice is a baseless and usually negative attitude toward members of a group.
Common features of prejudice include negative feelings, stereotyped beliefs, and a
tendency to discriminate against members of the group. While specific definitions of
prejudice given by social scientists often differ, most agree that it involves prejudgments
(usually negative) about members of a group.
Types of Prejudice
Prejudice can be based upon a number of factors including sex, race, age, sexual orientations,
nationality, socioeconomic status and religion. Some of the most well-known types of prejudice
include:
 Racism
 Sexism
 Classicism
 Homophobia
 Nationalism
 Religious prejudice
 Ageism
All this as affects the process and the results of the research project as the research must not
succumb to the tendency to be prejudiced or biased.
It is important that the research has none of this because then the research can be rejected as
being unfair.

CHAPTER THREE
METHODLOGIES
The term methodology refers to the overall approaches & perspectives to the research process
as a whole and is concerned with the following main issues:
 Why you collected certain data
 What data you collected
 Where you collected it
 How you collected it
 How you analyzed it
(A research method refers only to the various specific tools or ways data can be collected and
analyzed, e.g. a questionnaire; interview checklist; data analysis software etc.).
SAMPLING
Sampling is the process of selecting a “few cases” from a target population in order to provide
information that can be used to make judgments about a much larger number of cases. The “few
cases” is called the sample, and the whole group from which the “few” has been drawn is the
population or universe.
Aims of Sampling
The aim of sampling is to enable the estimation of a population from a part of it. Sampling is
necessary to:
1. Shorten the time that would otherwise be spent studying the whole population.
2. Reduce costs since fewer cases and resources are required than if the whole population is
used.
3. Gain greater accuracy in data collection and analysis, since the few cases involved are easily
amenable to a verity of data collection and analysis tools and techniques.
4. Eliminate the need to spend excessive resources to study a whole population when the same
information can be obtained from a part of the population. Just as a doctor does not need a
litter of blood from a patient to test for malaria. The information contained in a litter of blood
can be obtained from just a blood smear.
Qualities of a Good Sample
A good sample is:
1. Representative: It should resemble the population closely on all characteristics on which
judgment is to be based.
2. Accuracy of sample Size. A sample must attain a certain minimum size relative to the
population based on a particular level of precision. Too small a sample may not capture all
the major characteristics of the population, while too large a sample is wasteful.
3. Error free: A sample should be free from errors due to bias or distortion.

Sampling strategies are divided into two main groups: probability and non-probability
sampling. Sampling methods allow for representative cross-sections, or particular groups to be
identified or targeted.
Probability Sampling
This is where the researcher has a significant measure of control over who is selected and on
the selection methods for choosing them.
Main Methods:
 Simple Random Sampling: (Selection at random by the researchers from a choice of
subjects)
 Systematic Sampling: (Selecting by the researchers at numbered intervals, e.g. every
one person in five in the target group)
 Stratified Sampling: (Sampling within particular sections of the target groups, e.g. you
target a specific number of people based on the percentage of the total group that share
the same characteristics.
So, for example, in a study of an organization that had 50 supervisors & 800 laborers, a
10% representative sample of this population would target 5 supervisors & 80 laborers to
interview.
 Cluster Sampling: (Surveying a particular cluster of the subject group)
Simple Random Sampling
In simple random sampling, each member of the population has an “equal” and “an independent”
chance of being included in the sample.
 The chances are independent if the selection of one member does not, in any way, affect the
chances of another member being selected. The fact that a member, A, has been selected does
not in any way prevent a member, B, from being selected.
 The chances are equal if the selection of a member is not influenced by, or is not dependent
on, other factors other than being a member of the population. Since all members are part of
the population, they all have equal chances on this basis. And because of the equal chance,
those individuals that are finally included in the sample are selected only by chance.
 The chances are known if the probability of each member can be determined with certainty
prior top selection.
Area (Cluster) Sampling
 A cluster or an area is any group (geographical or otherwise) where an intact group with
similar characteristics can be found. Cluster or area sampling is a random selection of
clusters from the larger population of clusters. Situations may sometimes arise where it is not
possible or cost effective to obtain an exhaustive, comprehensive, correct, reliable and
appropriate list of all the members of the population, like when the population is large, or
widely dispersed. In such a case, selecting a simple random sample poses administrative
problems. So under such and similar conditions, a researcher may divide the population into
subgroups (as in the case of stratified sampling), then the subgroups as the sampling frame.
Some of the groups are then selected at random. Once a subgroup is selected through a
random procedure, all the members of that group are studied. This means that the random

sampling is at the group rather than at the individual level. Groups or areas or clusters are
selected through simple random procedure and once a group or a cluster is selected, all the
members of the selected groups or clusters constitute the sample.
 The major advantage of cluster sampling is that it is cheap, fast and easy to administer. But is
rather inaccurate as it involves more than one sampling error, especially if multistage
sampling is used. Moreover, it produces a larger sampling error than a simple random sample
of the same size; because the clusters tend to be similar within the cluster, thus reducing
representativeness of the sample. Analysis of data collected from cluster samples also
requires non-conventional analysis methods which are rather subjective.
Systematic Sampling
Systematic sampling is usually regarded as a simplified version of simple random sampling. In
systematic sampling, the first number (n) of the sample is randomly selected from a randomized
list and from that point on, every other nth
member on the list is picked in equal fractions of n.
Suppose a researcher wants to select a sample of 10 from a population of 30 respondents using
the systematic sampling technique, the researcher should first obtain the sampling interval or
sampling ratio (fraction). A sampling interval is the distance (in the list) between each of the
individuals selected for the sample, and rounded off to the nearest whole number. For the case
here, it is:
The sampling frame is then divided into groups of three (sampling interval) starting from the first
member in the list. The total number of groups produced by this procedure should be equal to the
sample size (in this case 10) as demonstrated below.
 The first member (n) is randomly selected from the first group on the list. After the first
member of the first group is selected, every other nth
member of each group is picked for the
sample. Suppose the second member (n = 2) from the first group has been selected through a
simple random procedure, then every second member of each group should be picked for the
sample. The units 2, 5, 8, 11, 14, 17, 20, 23, 26 and 29 are systematically selected for the
sample.
Sampling Interval = Population = 30 = 3
Sample Size 10
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Stratified Sampling
 Stratified sampling is a sampling technique that identifies the major and significant sub-
groups within a population and then selects elements from each sub-group to form a sample
with a view of reproducing the population.
 The purpose of stratified random sampling is to divide a population of study into
homogenous sub-groups and represent each sub-group in the sample in proportions
equivalent to its size in the population. This ensures that each subgroup characteristics are
taken into account, thus raising the validity of the study.
A population is heterogeneous if it has distinct and mutually exclusive subgroups within the
main population (i.e. when it is not possible for one member to belong to more than one sub-
group at the same time). When faced with such a situation, researcher instead of selecting the
sample randomly from the target population, first divides the population into homogenous strata
or layers, and then select cases from each stratum by random sampling procedure. This is
stratified sampling.
Types of Stratified Sampling
 In proportionate stratified sampling, a sample is randomly selected from each stratum in
proportions to the size of the stratum to the population. In this case, the size of each stratum
in the sample is a simple fraction (or percentage) of its size in the total population.
 Sometimes researchers do not wish to get involved with complex mathematics. So a
researcher may just decide and assign sizes to sub groups at his or her discretion, and based
on other criteria without mathematical rations. This is disproportionate stratified sampling.
In disproportionate stratified sampling, the sizes of subgroups in the sample are not direct
rations of their sizes in the population. The researcher simply assigns the largest percentage
in the sample to the stratum with the largest size in the population without using
mathematical equations.
 Disproportionate stratified sampling is most appropriate when:
i. A researcher doe not attach much significance to the results of a study, as in the case of
pilot and exploratory studies.
ii. When a researcher has a strong conviction that particular group has the relevant
information or is more affected by the issue under investigation, and therefore require
more representation, while at the same time, there is a strong conviction that the views of
other groups are equally important.

Non-Probability Sampling:
This is where the researcher has little initial control over the choice of who is presented for
selection. The sample selected is not influenced or determined by the researcher.
Convenience Sampling
 Convenience sampling is also referred to as accidental or as man-on-the-street sampling
technique. In this technique the sample is selected from those who happen to be available at
the time of data collection, a first-come-first-served basis, until the desired number is
attained. The researcher simply picks from those who happen to be available at the time of
data collection, without any conscious effort to select particular case or cases, and without
attempting to construct a sampling frame. Those who happen to be available at the time of
data collection constitute the accessible population, and whoever is available and willing can
be selected for the study.
 The problem with convenience sampling technique is that but cannot produce a
representative sample.
Purposive Sampling
 Purposive (or judgmental) sampling is a selection technique where a researcher uses personal
judgment regarding the cases from which information is to be collected, and deliberately
picks cases that are typical of the population being studied. The researcher uses personal
judgment and logic to select only those cases that best suit the purposes of the study, or those
believed to have the information sought. The researcher hand-picks the individual cases on
the basis of their typicality - and builds up a sample that is satisfactory to the specific needs
of the study. Just like convenience sampling, purposive sampling cannot produce a random
sample.
Networking Sampling (Snowball)
 This technique is usually employed to locate cases that are difficult or impossible to locate
through other means. Networking sampling strategy takes advantage of social networks and
the fact that friends tend to have some similar characteristics. In the first stage, a case, or few
cases, having the requisite characteristic(s) are identified and studied. Once the case(s) with
the requisite characteristics are identified, they are then asked for assistance in locating more
cases with characteristics similar to theirs. This process is continued until the desired sample
is attained. The main weakness of snowball sampling is the time it takes to builds the
requisite sample size. Furthermore, the sample produced by this method cannot be
representative. If people are given a chance to invite others, they will always have a reason to
invite one and not the other, and such prejudices will definitely be reflected in the sample.

Voluntary Sampling: This occurs when the selected sample is self-selecting; they come forward
to participate in the research in response to an appeal. The researcher does not choose them as
they come themselves.
Event Sampling: This simply means the researcher using the opportunity presented by a
particular event, e.g. a conference, to make contacts. Say for example a school closing ceremony
or a public function.
Time Sampling: The researcher recognizing that different times or days of the week or year
may be significant and decides to do sampling at these times or days. The resultant sample will
be according to the number of individuals available at that time or day.
The major features of the common sampling techniques are summarized in table 3.1 below.

Table 3.1
Sampling Technique Main Features Strengths Weaknesses Purpose Justification
Probability
Simple
Random
Selects
individuals
without bias
from a
target/accessible
population in
such a way that
each unit has a
known, equal
and independent
chance of being
selected in the
sample.
- Ideal
procedure for
selecting a
representativ
e sample.
- Results are
generalizable
.
- High
population
validity.
- Easily
affected by
attrition.
- Tedious to
construct an
exhaustive
sampling
frame in some
situations.
- No guarantee
of
representative
ness
especially if
the population
is
heterogonous.
- Low
precision.
- Can be
expensive in
some studies.
To select a
random and
representative
sample.
- Gives each
member of
the
population
known,
equal and
independe
nt chance
of being
selected.
- Produces a
random
sample.
Stratified
Identifies
subgroups in a
population and
their
proportions and
selects cases
randomly from
each sub group
to form a
sample.
- Subgroups
are
proportionate
ly
represented.
- Accounts for
the
difference in
subgroup
characteristic
s.
- High
precision.
- Cumbersome
because sub-
group
characteristics
must be
known, and
logistics of
selection
complex.
- More
expensive
than simple
random.
- Difficult to
identify
appropriate
identification
variables.
- Unfeasible or
expensive on
many
To group a
population
into
homogenous
subgroups.
- To ensure
equitable
representa
tion of
each
subgroup
ion the
sample.
- Ensures
proportiona
te
representati
on of
subgroups
in the
sample,
and
accounts
for
differences
in
subgroup
characterist
ics.

stratification
variables.
Cluster
1-Stage: Selects
group rather
than individual
members. Once
a group is
selected, all the
cases in then
group are
studied.
- Cheaper and
easier to
implement
than simple
random.
- Less accurate
because there
is more than
one sampling
error.
- Data analysis
requires
unconvention
al means,
hence
subjective.
To select
groups
instead of
individuals
when an
exhaustive v
sampling
frame cannot
be
constructed.
- Cheaper
and faster
than simple
random.
- Suitable if a
sampling
frame
cannot be
obtained.
2-Stage: Selects
group rather
than individual
members. Once
a group is
selected,
individual
members are
selected at
random from
the group.
- Slightly more
accurate than 1-
stage because of
random selection.
Multistage:
selects
progressively
smaller groups
until the
individual
members of the
sample are
selected through
a random
procedure.
- Cheaper and
faster than
simple
random.
- Substitutes
for simple
random.
Cannot claim to
produce a
representative
sample.
Used when it
is either
impossible or
impractical to
compile an
exhaustive
sampling
frame.
- Cheaper
and faster
than simple
random.
- Substitutes
for simple
random.
Systematic
Select every nth
member of a
population from
- Easy and
cheaper to
implement
- Suffers from
periodicity.
- List must be
- Substitutes
from
simple
- Easy and
cheaper to
implement

a randomized
list of the
population.
than simple
and stratified
sampling.
randomized to
avoid
periodicity.
- Low
generalizabilit
y.
and
stratified
sampling
techniques
.
than simple
and
stratified
sampling.
Non-
Probability
Purposive or
Judgmental
The researcher
deliberately
determines
which cases to
include in the
sample.
- Selects
typical and
useful cases
only.
- May produce
biased
sample.
- Low
generalizabilit
y.
- To collect
focused
informatio
n.
- Selects
typical and
useful
cases only.
- Saves time
and
reduces
costs.
Convenience
or
Accidental
Selects, on-
first-come-first-
served basis,
those who
happen to be
available, and
appropriate at
the spur of the
moment.
- Collects data
on the spur
of the
moment to
take
advantage of
unexpected
events.
- Easy to
implement.
- Cannot
produce a
representative
sample.
- Not useful in
descriptive
and causal
studies.
- Suitable
for pilot
and
explorator
y studies.
- Suitable
for
infinite
population
s when it
is not
possible
to
construct
an
exhaustive
sampling
frame.
- Collects
data on the
spur of the
moment
without
rigidity of
procedure.
- Takes
advantage
of those
who
happen to
be there, or
of
unexpected
events.
Snowball
Selects a
sample on the
basis of social
networks on the
premise that
cases with
similar
characteristics
tend to belong
together.
- The only
way to locate
cases that are
difficult to
trace.
- Time
consuming,
and cannot
produce a
representative
sample.
- To locate
cases that
are
difficult to
trace.
- Locates
cases that
are difficult
to trace.

Quota
Identifies
subgroups in
the population
and their
proportions and
selects from
each subgroup
(but not
randomly) to
form a sample.
Uses only non-
probability
techniques to
select individual
cases from each
quota.
- Proportionate
representatio
n of each
subgroup.
- Easier to
implement
than
stratified
sampling.
- Sample can
be controlled
for certain
characteristic
s.
- Cumbersome
because
subgroups
characteristics
must be
known.
- Low
reliability
- To group a
population
into
homogeno
us
subgroups
.
- To
provide
equitable
representa
tion of
each
subgroup
ion the
sample.
- To plan a
major
study.
- Ensures
proportiona
te
representati
on of
subgroups
in the
sample.
- Accounts
for
differences
in
subgroup
characterist
ics.
- Useful in
large scale
surveys.
The Sample Size
 A sample size is the number of cases or elements that should be studied and from which
reliable conclusion can be made about the population. It is represented by an s or by an n,
and the population or universe by an N, or µ. A researcher must determine the least size of a
sample that will provide sufficient data to answer the research questions.
 Drawing conclusions about a population based on a sample is never totally satisfactory since
a researcher can never be sure that the sample is representative of the population. Some
differences between the sample and the population are bound to exist. However, if the sample
is randomly selected and is of a sufficient size, then such differences are likely to be
insignificant and incidental.
Factors influencing Sample Size
Generally, a sample size will depend on:
1. Homogeneity or heterogeneity of the population: The more heterogeneous the population, the
larger the sample should be so as to capture all the diverse characteristics of the population.
2. The breakdown planned in tabulation: if a complex tabulation is planned, then a large sample
is required to ensure that there is reasonable number of subjects in each category.
3. Types of sampling techniques to be used or the research design itself (Quantitative or
Qualitative).

4. Resources available: scarcity of resources may necessitate the use of a smaller sample than
recommended.
Terms Related to Sampling
The following terms are useful in understanding sampling.
Census A complete enumeration of the population. In census, each individual
member of the population is used in the study.
Target Population The larger population (universe) from which a sample has been
drawn and to which the researcher intends to generalize his or her
findings. It is an aggregation of study elements and refers to all
members of a real or hypothetical set of people, events, or objects to
which we wish to generalize the findings. Remember that a
population refers to whatever entity being studied and not necessarily
to people. The target population can be finite like in the case of
students in a school; or infinite like in the case of people in a market.
Accessible Population An accessible population is part or a subset of the target population
that a researcher can actually reach, and from which the researcher
actually draws a sample. It is an aggregation for which a sample is
selected. In order to generalize conclusions from an accessible to a
target population, the accessible population should closely resemble
the target population in respect to those variables relevant to the
study. This is called population validity. The relationship between a
target, accessible, and the sample populations can be visualized as
depicted in Figure 3.1.
Figure. 3.1. Relationship between target, accessible and sample.
Stratum Refers to a layer, or a subgroup or a sub-population within a
population when a set of specifications divide the population into
Target Population
Accessible Population
Sample

mutually exclusive entities. Males constitute a stratum when gender
is used to categorize human population.
Sample A small group of subjects or participants selected procedurally from
the target or accessible population to represent the latter. It is a
portion of the target or accessible population which the researcher
will actually study.
Sampling Frame An exhaustive, comprehensive, correct, reliable and appropriate list
of members of the defined population from which the sample is to be
selected. It is a list of members of the target/accessible
population from which a researcher draws a sample.
Sampling Unit A single member of a population, which must be non-overlapping. A
student is a sampling unit when a sample is to be selected from a
population of university students.
Element The unit of analysis about which data is collected, and that forms the
basis of analysis. It is an individual member of a sample.
Random Selection The process of picking cases from the target population without any
bias (or by chance) to represent the population.
Random Assignment The placement of cases to different groups without bias (by chance)
for information-gathering. This is usually done when a researcher has
more than one condition to investigate in a study.
RESEARCH VARIABLES
 A variable is a characteristic (or an attribute) that can take a variety of forms (a number,
amount or situation which can change) at different times, or in different people, or in
different places, or in different circumstances. Some observable fact can be measured or
observed in two or more categories. These different forms or categories are called attributes.
Because the phenomenon varies (or exists in two or more categories), it is called a variable.
So variable is any characteristic with a variance.
 Examples of variables include educational status, marital status, gender, religion, ethnic
group, ability, temper, among others. If the values of a variable are expressed in numbers to
indicate the amount, degree, quantity or magnitude of the attribute, it is called a quantitative
variable. If a variable is expressed in terms of qualities, then it is called a qualitative variable.
But it is possible for one variable to be expressed in qualitative and in quantitative forms at
the same time

 A variable can be active or inactive. An inactive variable cannot be manipulated (e.g.
gender). Active variables can be manipulated (e.g. teaching method). A variable is said to be
manipulate able if it can be made to assume different forms by the researcher.
Types of Variables
The Independent Variable
An independent variable refers to the conditions that a researcher controls (or changes) in order
to test its effect on some outcome. It is the variable which the researcher chooses to study and
manipulates in terms of amount or level, in order to assess its effect another variable.
Dependent (or Criterion) Variable
 An independent variable is usually presumed to affect another variable. That other variable
the independent variable is presumed to affect is called the dependent variable. Generally, the
nature of the dependant variable depends on what the independent variable does to it. Thus, a
dependent variable manifests observable changes attributable to the influence of an
independent variable.
 Since a dependent variable depends on an independent variable, a dependent variable must
change accordingly whenever an independent variable changes. In other words, a dependent
variable has no control over its behaviour as it is dictated by the behaviour of the independent
variable. Because it wholly dependent on an independent variable, it is called a dependent
variable. Further comparisons between the dependent and independent variables are
summarized in Table 3.2.
Table 3.2
Relationship between the Independent and the Dependent Variables
Factor Independent Variable Dependent Variable
Cause-effect Presumed cause Presumed effect
Timing Antecedent - happens before Outcome - happens after
Prediction Variable predicted from Variable predicted to
Experiment Manipulated in experiments Measured or observed in experiments
Change What the researcher changes What is supposed to change as a result

Extraneous Variables
 In any situation, there are always some unwelcome things or issues. In a family, or in a
school, or in any organization, there may be unwanted persons, behaviour circumstances.
Because they are not wanted, every effort is made to keep them away or to neutralize their
effects. In a research situation also, there are always some unwanted variables. These
unwanted variables are what are referred to as extraneous variables, or intervening, or
nuisance variables.
 In an ideal study, only the independent variable should influence the dependent variable. But
this is not usually the case because there are always other variables that could also influence
the dependent variable, and hence the outcome of a study. However at any one time, a
researcher can only study a few of these variables in one study. Those other variables that
can also influence the results of the study, but which the researcher does not wish to study at
the moment are called extraneous, or intervening, or nuisance variables.
 The illustration between independent, dependent and extraneous variables can be visualized
as shown in Figure 3.2.
Fig. 3.2: Relationship between independent, dependent, and extraneous variables.
 All other routes or effects other than the route of the effect of alcohol on memory ( ) are
extraneous variables. Extraneous variables are actually independent variables, which the
Age
Gender
Level of education
Health of the students.
IQ
Learning environment.
The teacher
Teaching method
Extraneous Factors
Extraneous Factors
Alcohol - IV Memory – DV (Ideal Path)

researcher does not wish to investigate at the moment. They must be controlled so that they
do not influence the outcome of the study.
Control Variables
 Extraneous variables must be controlled. If they are not controlled, then they will also
influence the dependent variables and confound the results of the study. To control an
extraneous variable is to reduce its effect on the dependent variable to a bare minimum so
that it does not significantly influence the outcome of the study. Once an effect of the
independent on the dependent variable has been reduced to a bare minimum, it is then said to
have been controlled, and it becomes a control variable.
 A control variable is an extraneous variable whose effects on the dependent variable has been
held constant, or reduced to a bare minimum, or removed statistically (or by some other
means) so that it does not have a significant influence on the dependent variable of the study.
In other words, it is an extraneous variable that has been manipulated so as not to have a
significant effect on the dependent variable.
Moderator Variable
A moderator variable affects the relationship between the independent variable and the
dependent variable, but does not have a direct role in the cause and effect relationship. An
example is a catalyst in a chemical reaction. A moderator or mediator variable modifies the
length of time the independent variable takes to influence the dependent variable, but it does not
alter, in any way, the overall effect of the independent variable on the dependent variable. For
example, people get drunk faster when they drink in a bright light than when they drink under a
dim light. Thus while a person may take three hours to get drunk with two bottle of beer in dim
light, the same person may take only 45 minutes to get drunk to the same intensity with two
bottles of beer when taken in bright light. But light alone does not make the person drunk. So
light is a moderator or a mediator variable.
Continuous Variable
A continuous variable is a variable that can take unlimited number of values between any two
points. It is a variable whose values vary along a scale, and which can assume any value within a
specific range. An example of a continuous variable is weight. Between 4 kg and 6 kg, there are
infinite numbers of possible weights because weight can be expressed as a fraction.
Discrete Variable
A discrete or a categorical variable can assume only definite whole numbers, not fractions,
between any two points. It is a variable whose individual values fall on a scale with distinct gaps,
and defined sets of categories. An example of a discrete variable is the number of people.
Between 4 and 6 people, there can only be one value - 5 people and not 5.5, or any other number.
Other examples of discrete variable are gender, occupation, teaching method, and eye colour.

ETHICAL ISSUES IN RESEARCH
Decision to undertake a research must rest upon a considered judgment about how best to
contribute to educational, science and human welfare. Researchers are concerned not just with
the benefits of the research findings, but also with the rights of the subjects or participants in the
research process. Because research helps people to improve their lives and themselves – it
remains an integral part of human endeavour. However its value cannot be stretched beyond the
dignity of human society. The balance between search for knowledge and respect for the
researched community of people (or things) is what is called ethics.
Major Ethical Issues in Research
Informed Consent in Research
 Informed consent, as an ethical principle in research, demands that research subjects and
participants be fully informed of all aspects of the research that might reasonably be expected
to influence their willingness to participate in a study in which they have been asked to
participate; and that the researcher fully explains all aspects of the research about which the
participants may inquire. In the end, people should accept to participate in a study based on
the information provided.
 Prospective participants should be provided with information on:
i. The purpose of the research so that they can understand the nature of the study and its likely
impact on them.
ii. The expected duration of participation in the study.
iii. The procedure to be followed in the study.

iv. Any unforeseen risks or discomforts to the participants that may arise from the study so that
participants can realistically expect what to anticipate in the study.
v. Any benefits to the subjects or participants that may arise from the study.
vi. Alternative procedures or treatments, if any, that may be available to the participants.
vii. The extent of privacy and confidentiality.
viii. That they can participate voluntarily and withdraw at any time.
Privacy and Confidentiality in Research
Privacy
Privacy refers to persons and defines the rights of the participants to keep from the public certain
information about themselves. Privacy is maintained when people can control who has
information about them or who may intrude in their lives. Privacy, as an ethical principle in
research is the requirement that participants’ territories be respected and entry to participants’
territories can only be their permission. A territory can be as a small as an individual, or as large
as an institution.
Confidentiality
Confidentiality has to do with data (or information) rather than with the participants. It is an
agreement between individuals that limits others access to privileged information, by defining
who will have access to data. Confidentiality as an ethical principle in research is the
requirement that information provided by a participant, or that data collected from a study unit is
not passed to a third party unless with their express permission.
Anonymity in Research
Researchers are generally concerned with information provided rather that person who provided
it (though the source of information is also important). Researchers accept information without
bothering so much about personal details, or insisting the respondents provide their personal
details as well. In other words, respondents can provide information without giving personal
details about themselves, unless they wish to provide such details. This is the idea of anonymity.
Anonymity, as an ethical principle in research is the requirement that participants in any research
undertaking have a right that their individual identities are not made major features of the
research.

Researcher’s Responsibility in Research
The conduct of a researcher prior to, during and after the research undertaking is a major ethical
issue. Participants in a study have the right to expect that a researcher be sensitive to human
dignity and well meaning in his or her intentions throughout the investigation. Further,
researchers are not expected to allow their personal judgments to prejudice the collection,
analysis and interpretation of data; nor to give into fudging effect by directing results to conform
to some preconceived notions. Their integrity is foremost. Other responsibilities of a researcher
include:
 Accuracy of information. Results must be based on data.
 Giving feedback to be researched.
 Admitting shortcomings and not reporting issues that are not based on the findings of the
study.
 Respect for the researched and the research sites. A research cite should be left as
undisturbed as possible at the end of the study.
Other major issues in each of these stages are summarized in Table 3.3
Table 3.3
Ethical Issues associated with Different aspects of Research Process
Stage of Research Ethical Concerns
Problem identification The problem must be beneficial to the individual cases being studied.
The problem should not marginalize or dis-empower the people being
investigated.
Purpose
statement/Research
questions
The problem must be clearly specified and understood by the
researcher and the participants in the same way. Deception occurs
when the researcher and the participants have different purposes in
mind.
Data Collection Participants should not be put at risk. Vulnerable groups and research
cites must also be respected. Informed consent is very crucial at this
stage as well gaining permissions to research cites and cases.
Data Analysis and The major ethical concerns at this stage are anonymity of

Stage of Research Ethical Concerns
Interpretation respondents, keeping the data for some time (5-10 years) after the
study, ownership of the data, and accuracy of information.
Reporting The major concern includes use of unbiased and non-sensitive
language in any form. It is unethical to invent or to bend findings in
any way or for any purpose. This is regarded as a scientific
misconduct.
RESEARCH DESIGNS
 A research design is the plan or the overall strategy for conducting the research. It refers to
the procedures used by a researcher to explore relationships between variables, to form
subjects into groups, to administer treatments and analyze data. It is a means of ensuring that
a research process is sufficiently systematic and scientific, and that the results obtained are
applicable in real life.
 There are two overall research methodologies (or designs): qualitative and quantitative.
Generally, quantitative research designs are characterized by data (or findings) which are
expressed in numerical forms, and are analyzed using statistical methods.
 Qualitative research designs are characterized by data (or information) that is described
verbally or non-numerically.
Table 3.4 below shows the major differences between Qualitative and Quantitative Research
Designs

Table 3.4
Major Differences between Qualitative and Quantitative Research Designs
Source of Difference Quantitative Designs Qualitative Designs
1. Approach to
research
Scientific and formal. Scientific and neutral.
2. Research Data Reduced to scores. Presented in a narrative
description.
3. Knowledge View Concrete, conceptual and precise.
Can be tested. Seeks proof.
Experiential, contextual and
best expressed by the owners.
4. Process of Inquiry Linear, from stage to stage. Recurring and complicated.
5. Mode of Inquiry Experimental, manipulates
conditions.
Multimodal, multi stranded.
6. Use of
Hypotheses
Manipulates variables to prove
hypothesis.
Understands patterns of
occurrences in order to identify
variables.
Generates Hypothesis.
7. Main Questions Asks how much, how many. Asks why, who, when, etc.

8. Types of Samples Uses a random sample. Uses theoretical samples and
bounded cases.
9. Mode of Analysis Statistical. Interpretative.
10. View of Reality Objective, singular and independent
of the researcher.
Subjective and multiple.
As seen by the researcher.
11. Relationship of
the Researcher
Withdrawn and independent of that
being researched.
Interacts with that being
researched.
12. Role of Value Value free and unbiased. Value laden and biased.
13. Purpose of
Research
Deductive: cause-effect.
Generalizations leading to
explanations, understanding, etc.
Inductive: mutual, simultaneous
studying of factors. Generation
of theories.
Particularization of cases
(Ideographic).
Choosing a Research Design
 In planning to conduct a study, a researcher may develop a liking for one design. However,
it would be unwise to use one approach exclusively. A mixed method approach is
recommended.
 Chronological mixed designs are procedures where a researcher seeks to elaborate or expand
the findings of one method with another. A researcher may begin with a qualitative method
to identify the key or main or major issues important to the study and then plan a detailed
study to investigate the issues so isolated.
 Concurrent mixed designs combine quantitative and qualitative data in order to provide a
comprehensive analysis of a research problem. In such a case, both quantitative and
qualitative data are collected at the same time and then integrated in the interpretation of the
overall results.

Table 3.5
Guide to Choosing a Researcher Design
Criteria Quantitative Design Qualitative Design
1. Researcher’s
World View
-The world is objective and
measurable in specific terms.
Reality is single.
-The world is subjective with
multiple realities.
-Reality is contextual.(depends on
the individual)
2. Training and
Experience
-Technical writing skills,
computer, statistical skills, library
skills.
-Literally writing skills, computer
text analysis skills.
3. Psychological
Attributes
-Comfort with rules and
regulations for conducting
research.
-Low tolerance for ambiguity.
-Time short.
-Comfort with lack of specific rules
and procedures for conducting
research.
-High tolerance for ambiguity.
-Time for study lengthy.
4. Nature of the
Problem
-Previously studied by other
researchers.
-A body of literature exists.
Known variables.
-Existing theories.
-Exploratory research,
-Variables unknown,
-Context important.
-Lacks theory base for the study.

Criteria Quantitative Design Qualitative Design
5. Type of
Audience
-Individuals accustomed to, or
supportive of quantitative research
studies.
-Individuals accustomed to, or
supportive of qualitative studies.
6. Level of Control -Full or sufficient control -Limited control
Characteristics of a Good Research Design
A good research design must be:
1. Free from Bias: The data and the statistical methods used should not vary in any systematic
way except as would be expected from random fluctuations. Any differences must be
attributable to the independent variable. Systematic errors occur in given directions and
cannot be estimated statistically.
2. Free from confusing effects: A good research design removes confusing of variables, or
keeps it to minimum so that effects can be separated and results interpreted without
confusion. Controlling extraneous variables also ensures internal validity.
3. Collect precise data for statistical hypothesis tests: A good research design should produce
adequate data with sufficient accuracy to adequately test those hypotheses that require
statistical testing.
Quantitative Research Designs
 Quantitative research designs are broadly divided into experimental and non-experimental
designs.
 Experimental designs generally involve control and manipulation of variables in order to
establish cause-effects relationships, the knowledge of which is used to predict and control
events. Experimental designs are carefully designed to control all variables except the
independent variables.
 Non-experimental designs do not manipulate variables, and they do not establish cause-effect
relationships. They are basically used to:
1. Describe and explain events, situations, phenomena, etc as they exist or as they once existed.
2. Evaluate products, events, concepts, etc.
3. Develop new innovations.

Experimental Research Designs
 An experimental research is a study conducted to examine and establish cause-effect
relationships between variables in a controlled setting. An experimental research determines
the relationship between a dependant variable of interest and an independent variable that the
researcher has hypothesized to be causally related. The independent variable is then
manipulated by the researcher under carefully controlled conditions to determine if it is
producing a change in the dependent variable.
 The basic characteristic of an experimental research design that distinguishes it from the
other research designs is the manipulation of the independent variable. Manipulation means
that the researcher determines (directly or indirectly) the various forms (or levels, amounts,
etc) that the independent variable may take and which groups will get which kinds of
treatment.
Characteristics of Experimental Research Designs
An experimental research has three basic characteristics:
1. The researcher manipulates the independent variable. This is to say that the researcher
deliberately determines (directly or indirectly) what forms the independent variable takes,
and which groups receive which forms of treatment.
2. There are at least two groups (one experimental and one control group) included in the study.
The experimental group receives treatment while the control group does not (but it may
receive a routine treatment).
3. There is randomization of subjects. Subjects in the study are first randomly selected from the
target population and then randomly assigned to experimental and control groups, or groups
(E and C) are randomly assigned to subjects.
4. Experimental research designs have advantage over other designs because they can achieve
higher internal validity as well as establish causal claims. Only experiments can test precise
predictions because they are controlled and the researcher can manipulate the independent
variables as he or she wishes.
Other Terms in Experimental Research
1. Pre-test: Since experiments are usually concerned with measuring changes, there should
always exist two values from which the magnitude of change can be determined. Before a
researcher can introduce an intervention, he or she should first determine the initial level of
the variable of interest. The determination of the initial value of the variable before the
intervention is called a pre-test
2. Treatment: This is the intervention or the change that a researcher introduces in the
independent variable to see its effects on the dependent variable.
3. Post-test: After the intervention, a researcher would want to know if the treatment (or
induced change) has caused a change in the dependent variable. To do this, a researcher has
to determine the level of the dependent variable after treatment. This is called posttest. It is
the determination of the final value of the dependent variable after treatment.

Ex-Post Facto Research Design
Ex-post facto or casual comparative research design refers to an “experiment” in which a
researcher, rather than administer a treatment, examines the effects of a naturalistically occurring
treatment after that treatment has occurred. It is a pseudo (or false) experimental research design
where a researcher, rather than administer a treatment, substitutes for the treatment with a
naturally occurring condition after the condition has occurred. The researcher attempts to relate
this after-the-fact-treatment to an outcome, by looking for a natural cause without having to
directly manipulate the independent variable. Ex-post facto research designs are suitable if:
1. The variables being investigated cannot be manipulated (e.g. gender).
2. The variables or should not be manipulated (e.g. brain damage, HIV infection),
3. The variables are simply not manipulated though they could be manipulated (e.g. teaching
method, broken homes, intelligence).
Suppose a researcher wants to study the effect of broken homes on the performance of students
at school, the researcher would, in an ideal situation, randomly select a sample of students, break
their homes and then measure their performance. But it is not ethically right break up homes. The
researcher would select students whose homes are already broken and administer a performance
test on them. This is ex-post facto design, where a researcher rather than administer a treatment,
looks for an already naturalistically existing condition without having to administer the
treatment.
Survey Research Design
 Survey studies, or as they are also called, normative or status studies, are present oriented
studies designed to investigate populations by selecting samples to analyze and discover
occurrences, and provide quantitative descriptions of some part of a population within a slice
of time. Surveys basically explore, describe and explain opinions, attitudes, preferences and
perceptions of groups of people of interest to a researcher.
 Surveys involve a researcher asking (usually) a large group of people questions related to the
issue at hand. Survey research uses mainly questionnaires to collect basic descriptive
information from a broad sample, and interviews to gather in depth responses usually from
small samples or on sensitive topics, and to elicit deeper responses that cannot be adequately
captured by questionnaires.
 Surveys gather facts (rather than manipulate variables) to discover, clarify and describe
incidences, distribution, or interrelationship among variables to fully explain the
phenomenon involved.
Cross-Sectional Survey
A cross-sectional survey is a kind of survey that collects data from a target population at one
point in time. The data is collected from various cases at the same time - although the time taken
to collect this data may vary between a day and a few weeks. The researcher goes to the

population and collects data from a cross-section of the population at one point in time, and then
makes a report based on the data collected at once. The researcher has no intention of going back
to the same population to collect the same data for the dame study. Cross-sectional survey
designs are preferred over other designs because they save time and cost which may be incurred
in repeated data collections. And since it collects data from several cases at the same time, it
ensures that variety of views are over the same issue are captured in a short time.
Longitudinal Survey
 Longitudinal (also called developmental) survey collects data from the same target
population at different points in time in order to study changes over time. Data is collected
over time and at specified points in time. The cases in a longitudinal study are followed over
a long period to track changes on the some issue of interest through collecting same data
from the same cases (or case) over extended period of time.
 The major problem with longitudinal surveys is that it takes a long time to collect data. Since
the same data is collected from the same case(s) over an extended time, there is a danger of
losing some cases, or the case(s) may become fatigued due to repeated treatment or
observation. Nevertheless, it is a very effective way to study changes and trends of behavior
over time.
Panel Longitudinal Survey
In a panel longitudinal survey, a sample is selected from a target population at the beginning of a
study, and the same sample is surveyed at different times in the course of the study. The same
sample is used every time data is collected.
Cohort Longitudinal Survey
Cohorts are longitudinal survey designs that study a specific target population over time through
sampling. A population of study is defined and data is collected from fresh samples of the same
size drawn from the defined population which does not change through time. A population
remains the same if members who may have joined it after the first sample was drawn are
purposely excluded from the study.
Trend Longitudinal Survey
In a trend survey design, data is collected over time and at specified points in time by drawing
new samples at each observation point from a target population which keeps changing. The
target population keeps changing as new members join and other leave.
Table 3.6 below gives the differences between the Longitudinal Survey Designs:

Table 3.6
Differences between the Longitudinal Survey Designs
Design Main Features Population Sample Weaknesses Strengths
Panel Studies the
same sample
over time.
Remains the
same.
Remains the
same.
Easily affected
by attrition.
Puts strain on
the researcher
to trace
particular
cases.
Easy to note
changes and
offer
explanations.
Cohort Studies
different
sample of the
same size from
the same target
population.
Remains the
same.
Changes. May not
generate new
information.
Easy to
recognize
stability and
changes in
behaviour.
Trend Studies
different
samples of the
same size from
a dynamic
population.
Changes. Changes. It is difficult to
attain
saturation.
Keeps tracks of
changes in the
target
population.

Correlation Research Designs
Correlation studies are typical associational studies which determine whether, and to what extent
an association exists between two or more paired and quantifiable variables. Correlation studies
establish relationships (or lack of them) and use such relationships to make predictions between
two or more characteristics from the same group. In its simplest form, a correlation research
design involves collecting data on two or more quantifiable variables from the same group and
then computing a correlation coefficient (Ґ). Correlation studies describe the (i) direction, (ii)
nature and (iii) strength of an association between two or more variables.
Exploratory Research Designs
An exploratory research is more of a pilot study, and is commonly conducted when a researcher
has little knowledge of the variables of interest. It is more of a preliminary research effort in
planning a further rigorous research. In exploratory research, a researcher explores the field to
establish which variables are involved. The researcher freely follows through any new leads and
moves the study to a new area. Exploratory studies employ the following techniques either singly
or in a combination.
 Literature review. This is the secondary analysis of information already available, to focus
the structure, process and relationship of the research already done.
 Expert survey interviews with experts in the field of research area.
 Case study technique as a method of exploration.
Qualitative Research Designs
Qualitative research designs are ideal when:
i. The concept being investigated is ‘immature’ due to conspicuous lack of relevant theories
and previous research.
ii. The available theories are inaccurate, inappropriate, incorrect or biased.
iii. There is need to explore and describe the phenomenon and develop a theory.
iv. The nature of the phenomenon is suited to qualitative measures.
Characteristics of Qualitative Research
Research, whether qualitative or quantitative, is intended to generate valid, reliable and
generalizable knowledge. But qualitative research, unlike quantitative research, focuses more on
the process, meanings, instruments and fieldwork.
i. Qualitative research is concerned more with the process rather than the product. It is
particularly interested in how things occur rather than what exactly occurs, though it does not
ignore what occurs.
ii. Qualitative research derives meaning out of experiences and in context. It is concerned with
how people make sense out of their lives, experiences and the structures of the world.
Qualitative researchers want to know what people think and why they think the way they do.

They attempt to capture the thinking of a people from the people’s perspective as opposed to
merely reporting what the researcher thinks.
iii. The primary instrument of data collection in qualitative research is the researcher rather than
some animate inventory. Qualitative research data is mediated through human experiences
rather than through inventories, questionnaires or machines.
iv. Fieldwork is usually available if not inevitable in qualitative research. A qualitative
researcher physically goes to the people, settings and sites to observe and or record behaviour
as it occurs in its natural setting.
v. Qualitative research is inductive and builds abstractions and theories rather than test theories.
Qualitative researchers do not form hypotheses before hand and then try to test them. Rather
they tend to play-it-as it-goes. Unlike quantitative research that puts together puzzles whose
pictures are already known, qualitative research constructs pictures that take shape as they
collect and examine parts.

Table 3.7
Differences between Qualitative and Quantitative Research Processes
Quantitative Qualitative
- Problem identification and
definition.
- Problem identification and definition.
- Development of hypotheses. - Identification of study participants.
- Design of data collection tolls. - Data collection: the researcher is the primary
data collection tool.
- Data collection. - Generation of hypotheses.
- Data analysis and
interpretation.
- Data analysis and interpretation.
- Conclusion - Conclusion
Triangulation
 Triangulation (or convergence, or integration, or synthesis, or qualitative and quantitative
method, or multi-method, or combined method or mixed methods), refers to combination of
two or more data sources or methods of investigation into one study to converge on a single
construct.
 Triangulation generally entails collecting same data from a variety of sources using a verity
of techniques then comparing the similarities between the data obtained from various sources
and techniques. There are various approaches to triangulation, but all about examine different
perspectives of the same thing to notice the differences and similarities between the
perspectives.
Qualitative Research Designs
Case Study Research Designs
 Case studies are similar to survey studies except they use relatively smaller samples and have
greater depths. Case studies are descriptive studies that provide detailed information about
the characteristics or attributes of interest through intensive and holistic descriptions and
analyses of single entities. They explore single entities or phenomena (the case) bounded by
time and activity through collecting detailed information from a verity of data collection
procedures for a specified period of time. The case is a particular phenomenon (or a bounded
system), an instance of some concern or an intrinsically interesting scenarios that would lead
to achieve full understanding of the phenomenon as much as possible.
 A case is a specified entity (e.g. person, region, situation, etc) taken as an example through
which an issue is to be better understood. A case is a specific entity singled out several others
for detailed investigation or analysis. The entity is selected because:

i. It is unique and seams to offer insight than other would be cases because it is succeeding
where others have failed, or it is failing where others have succeeded, or it is just out of
ordinary.
ii. It is an instance of concern.
iii. It is intrinsically interesting.
iv. Selected through a random procedure.
Ethnography Research Designs
 Ethnography is the design used to learn about what is actually happening as it is seen and
lived by a people rather than what would happen given some specified conditions.
Ethnographers study intact cultural groups in natural settings during for long period of time
by collecting, primarily, observational data in order to learn about culture of the people who
actually live in that culture.
 Ethnographers learn about a people by letting them describe or portray their lives themselves
in a flexible process that evolves contextually in response to the lived realities encountered in
the field. Ethnographic research is thus an intensive, ongoing, face to face involvement with
participants of the culture being studied in their natural social setting over a long time. It is a
long time investigation of a group (often a culture).
Historical Research Design
 Historical research makes people aware of what happened in the past and enables them to
learn from past failures and successes. It enables people to learn what happened in the past
and see if the past experiences are still relevant to the present day problems and concerns.
Historical research is also useful as an aid to prediction. If an idea had been tried before, even
in different circumstances, the past results may offer insights into how the present result may
turn out. Historical research facilitates understanding the present from the past.
Phenomenological Research Designs
 Phenomenology research is based on the principle that people are active creators of their
world and that they have the consciousness that communicate to them everyday experiences
and knowledge. The purpose of phenomenological research is to accurately describe the lived
experiences of a people, rather than generation of theories or models of the phenomenon
being investigated.
 Phenomenology does not support the view that knowledge can be created through positivist
research. Rather, it seeks to understand group behaviour from the group’s point of view
without the researcher’s own assumptions and biases by examining human experiences
through detailed descriptions of the people being studied.
 Phenomenology involves studying a small number of subjects through extensive and
prolonged engagements to develop pattern and relationships of meaning.
 Phenomenologist’s examine phenomena without presuppositions and describe the deep
structures of a phenomenon based on observed internal themes.

Grounded Theory Research Designs
 Grounded theory is a research design which rather than prove theories, generates theories that
are grounded in the empirical data from which they are generated. In grounded theory, a
theory is developed from data rather than use data to prove a theory. It derives theories from
the immediate collected data rather than from prior research theories.
 In grounded theory designs;
i. The researcher enters the field without prescriptions, strict designs, tale games, sample
determination, firm scripts, hypotheses or knowledge about the research object and
without theoretical definitions.
ii. The researcher carries out case studies and compares them with other studies to establish
a pattern or trend of events that could be similar, in order to generate tentative or
provisional hypotheses.

Research Methodology

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