Contextualizing Scientific Research Methodologies

IOSR Journal of Research & Method in Education (IOSR-JRME)
e-ISSN: 2320–7388,p-ISSN: 2320–737X Volume 5, Issue 6 Ver. I (Nov. - Dec. 2015), PP 52-57
www.iosrjournals.org
DOI: 10.9790/7388-05615257 www.iosrjournals.org 52 | Page
Contextualizing Scientific Research Methodologies
Stanley Moffatt
School of Informatics, Engineering and Technology Regent University College of Science and Technology,
P.O. Box DS 1636, Dansoman, Accra, Ghana.
Abstract: This article dissects the various research instruments currently employed, against the backdrop of
the research design, methodology, population, sampling, and sample size. It highlights quantitative and
qualitative research, data collection methods, as well as the validity and reliability of the investigations. The
article adopted a qualitative research design that utilized documentation analyses to evaluate conventional
approaches to research methods. The study concludes by recommending both qualitative and quantitative
analyses in adding depth to an empirical scientific study.
Keywords: scientific research, research methodology, qualitative, quantitative
I. Introduction
Research, research reports, and technical report writing have accumulated so many perspectives among
researchers over the years, that views on technical scientific writing have become more and more divergent.
Given these variations, decisions bordering on the best kind of investigative methodology to adopt have come to
occupy the thoughts of many researchers [1] (Bowen, 2005). The primary aim of science is to discover and
collect facts (data) and to understand the order that exists amongst the various facts, through scientific research.
Scientific research is an intellectual, systematic, organized and empirical activity that is designed to
discover information about the natural world, as well as ways in which this information can be applied
meaningfully. Approaches to conducting scientific research therefore refer to the different protocols used in
research to gather and compile data, which is then used as a basis for inference, interpretation, explanation and
prediction [2, 3] (Miles and Huberman, 1994; Mouly, 1978).
According to Robertson [4] (1987), research methodology is a system of rules, guidelines and
principles that govern scientific investigation, provide a format and style for gathering evidence about what
takes place and why it takes place, and accomplishes it in a way that enables other researchers to verify the
outcome. It is hence the most important tool for advancing knowledge.
II. Procedures
In this study, a qualitative research method was used to evaluate various approaches to research
methods. This approach was used because it not only facilitated the collection and interpretation of information,
but also assigned appropriate meaning from a broad standpoint. Documented materials to evaluate approaches to
the different research methodologies were utilized.
The study employed documents from both primary sources (reports and publications that have first-
hand information on the theme of this study) and secondary sources (textbooks, journals, and reports of
research carried out by other investigators, relevant to this study). These two main sources of documents are less
likely to be affected by distortions since they are often generated alongside the events they refer to [5] (Bowen,
2009). In assessing these documents for relevance, emphasis was placed on validity and value to this research.
Validation of materials was done using Scott’s [6] (1990) overlapping validity criteria of authenticity,
representativeness and relevance.
III. Conceptualization
3.1 Research Design
One important goal of science is description [7] (Hale, 2012). Descriptive research according to Best
[8] (1970) often analyses the existing relationships; prevailing practices; beliefs, views, or attitudes; on-going
processes; or developing trends. According to Hale [7] (2012) and Jackson, [9] (2009), descriptive research
methods fundamentally describe situations. They do not make accurate predictions, neither do they determine
cause and effect. It is not technically a research method, because it utilizes several individual approaches to data
collection, each depicting a current position of any given situation [10, 9] (Verma and Beard, 1981; Jackson,
2009).
The process of descriptive research design does not only involve collecting and tabulating data, it is
also an attempt to obtain facts about the current state of things, which involves elements of cross - comparisons

and relationships. Descriptive research is geared towards assigning meaning to, and providing useful data for
further research [11] (Ololube, 2006).
Researches in general attempt to design studies that will yield evidence to either support or refute a
claim. The research design therefore becomes a logical sequence that connects the study’s research questions to
the data and ultimately to its conclusions [12] (Yin, 1994). It is thus imperative and logical to include design
features from broad theoretical perspectives in order to assess the quality of the research study.
Research design lays down the basis and foundation for assessing the inter-relationships between
variables. The selection of a good research design is even more critical and relevant because it guides the plan,
structure and strategic build up to obtain answers to the research questions, and affects the overall significance
of the research findings. The type of statistical analysis to use and possible conclusions to be drawn is indicative
of the particular research design adopted.
3.2 Survey Research
Survey research is a systematic method of data collection [13] (Borg and Gall, 1989). The purpose is to
describe specific characteristics of the elements in a group. This method is not just concerned with
characteristics of individuals as individuals, but it is concerned with providing information about population
variables [10] (Verma and Beard, 1981). In surveys, researchers normally use a “flow chart” to outline the
design and implementation of the survey. Using surveys, it is possible to collect data from large and small
populations.
In survey research, the researcher or author selects a sample of respondents from a population, and
administers a standardized questionnaire for analysis. The questionnaire can be a written document to be
completed by the respondent, an online questionnaire, telephone interview, or a face-to-face interview.
The most important contribution of survey research has perhaps been the rigorous sampling methods,
the design selection and implementation, the unambiguous research problem statements, and the data analysis. It
allows for standardization in the type of questions asked and in the method of approaching subjects, thus
ensuring higher reliability than some other techniques.
3.3 Case Study Research
It is a form of qualitative descriptive research focusing on a small group of participants, or the group as
a whole. Data is collected using participant and direct observations, surveys, interviews, tests, protocols,
examinations of past records, and collections of samples.
In a case study, the researcher cannot control the situation. Case study approach however does not
necessarily require procedural data analysis and this allows for various interpretations of the research data. This
interpretation could therefore introduce bias and affect the outcome of the research. Nevertheless, the case study
approach allows for the deployment of multiple data collection methods such as questionnaires, interviews,
documentary reviews, and direct participant observations [14, 12] (Okunoye, 2003; Yin, 1994).
According to Professor Paul Lawrence, a good case study is: “the vehicle by which a chunk of reality is
brought into the classroom to be worked on by the entire class and the instructor. A good case keeps the class
discussion grounded upon some of the challenging facts that must be confronted and addressed in real life
situations.” [15] (Christensen, 1981).
The case study research is considered as drawing on the interplay of the prevailing variables in order to
provide a thorough understanding of a situation or an event [16] (Palmquist (1993). Unlike quantitative
methods, case studies are the preferred approach when “how” or “why” questions are asked. Likewise, when the
researcher has little control over the events, this method becomes the preferred approach. Further, case studies
are best suited to using inductive logic - reasoning from specific to more general terms.
IV. Research Population
A population can be defined as the total of all the selected individuals with peculiar characteristics and
which are of interest to a researcher. In a general sense, a research population includes all the elements of a
well-defined group. It defines the scope by which the research is applicable. A research population is classified
into target and accessible populations. A target population describes all the members in the group to whom the
investigation is related, whereas accessible population represents those elements within the target population
that are within the reach and manipulation by the researcher.
4.1. Sampling
A sample is a subset of the population, and can be considered as the smaller group of elements selected
through a rigorous and definite procedure from a particular population; i.e. the elements that constitute the
sample are those that are actually studied. Kerlinger [17] (1986) has offered a comprehensive definition of

random sampling as the method of drawing a portion (sample) of a population so that all possible samples of
fixed size n, have the same probability of being selected. This is a generalized definition and thus satisfactory.
Simple random sampling is perhaps the oldest, easiest and simplest sampling technique in terms of
application and conceptualization [18] (Ololube and Egbezor, 2012). It does not necessarily require knowledge
of the exact composition of the population, only that we can reach all the members of the population. It is
important to note that, simple random sampling has a demerit in extrapolating the result to characterize the
general population, because it is unlikely to be representative of the population. Consequently, sampling error is
likely to occur with this kind of sampling. Other probability sampling techniques include:
 Quota sample: the author sets a requirement to ensure a particular group is selected and represented.
 Stratified sample: where the population is divided into sub-groups based on characteristics, and
thereafter selects from each group based on its size.
 Convenience sample: selection of the sample is based on ease of accessibility.
 Purposive sample: the researcher purposefully focuses on a particular subset or group of a population.
V. Data Collection Techniques
Interviews, questionnaires, and observations are three of the major ways to gather data. While data
from interviews is intended to provide information for qualitative analysis, data from questionnaires is expected
to provide information for inferential and quantitative analyses. Inferential statistics are concerned with making
inferences about a population’s characteristics based on information derived or collected from a random sample
of the population. This type of statistics lend themselves to making conclusions beyond the samples studied, to
cover the entire referenced population. Relevant statistics demand that conclusions are applicable and
generalizable to an extended number of elements in a population instead of results that are applicable only to the
actual elements under study.
5.1 Interview
The interview is a method in which the interviewer, asks a person being interviewed (the respondent) a
set of questions designed to elicit answers pertinent to a particular research problem. Interviews may be used to
evaluate a person for some characteristics, for assessing an employee for promotion, for evaluating the efficacy
of a well defined therapeutic regime, (as occurs in psychiatric interviews), for gathering data, for testing
hypotheses, for sampling respondents’ opinions on a particular selection etc.
When the interview is completed, the first step for the researcher is to listen to the tape(s) in order to
transcribe them. After the transcription, the researcher should write copious observational notes to be able to
contextualize the strategies. It is imperative for the researcher to keep strict observations and memos throughout
the entire analyses, as they not only capture analytical thinking about the data, but facilitate one’s analytical
insight.
The method adopted in the categorization will help researchers to generate relevant themes and titles
for their data. The objective here is to organize the data into categories that will facilitate cross-comparisons.
This can be followed by the contextualization strategy. Rather than segmenting the data, contextualization links
the data, or looks for methods to identify peculiar relationships between can organize relationships that connect
various variables like events, statements, and opinions within a context into a coherent whole.
5.2 Questionnaire
Questionnaire design is an approach involving any instrument that has questions or items to which
individuals respond. Arguably, the questionnaire is the most frequently used instrument in social science
research. Its popularity is demonstrated by the number of published studies and student projects that rely on this
instrument for data collection. There are two main types of questionnaires:
(1) Fixed response or Structured questionnaires
(2) Open-ended or Unstructured questionnaires.
There is a lot of well-designed research on how questionnaires should be structured to minimise
external influences on the process [19] (Braun et al., 2012). Nworgu’s [20] (1991) characteristics for designing a
good questionnaire is usually applied. These characteristics are: relevance, usability, consistency, quantifiability
and legibility. If you are choosing respondents from a number of different categories of people, it is usually
important to collect information on the demographics of the respondents. It is also important that a section of the
questionnaire is dedicated to collecting information on the demographics of the respondents.
5.3 Observation
Arguably, observation is perhaps the most challenging of all research methodologies, necessitating a
great deal of analyses, inferences, experience and practice. Observation can generally be classified into

participant and non-participant observation. The type of observation used should however reflect the scope and
aim of the research. Descriptive observation involves concentrating on observing the physical set-up, the key
participants and their activities, sequence of activities, particular events and their sequence, and the consequent
processes and emotions involved [21] (Anyamele, 2004).
VI. Data Analysis Techniques
Data analyses involves methods of distilling and interpreting qualitative or quantitative data which
requires a principal choice by the researcher [22] (Coffey and Atkinson, 1996). This should nevertheless involve
a process of systematically organizing the materials collected, and assigning meaning to them so that they tell a
story (applicable to the elements described or analysed), and presenting the results in a way that will enable
other researchers buy into or relate positively to the findings.
6.1 Qualitative Analysis
In qualitative analysis, less structured research instruments are used in gathering data, and the findings
are more in-depth since they employ mostly open-ended questions. Since the research is more flexible, it allows
the researcher to probe because he/she has greater latitude. Qualitative research for the most part uses participant
observation and in-depth interviews of the subjects, systematically recording their behaviors and perceptions,
analyzing the verbal and non-verbal information offered, and then supplementing it with other materials, such as
memoranda, journals, records, articles and photographs. Results emanating from such inquiries provide many
more details about behaviour, motivation and attitudes. However, since the results are usually based on small
sample sizes, they are often not representative of the population. Further, because of its low reliability owing to
its subjectiveness, the results cannot easily be replicated.
Qualitative research has been identified as an inquiry process of understanding a social or human
problem that is conducted in a natural setting and that is based on building a holistic picture from the words and
views of informants, [23, 24, 25] Creswell (1994, 1998, 2003). Much like Creswell, Gay and Airasian [26]
(2000) see qualitative research as the collection of exhaustive data on many and varying variables over an
extended period of time, in a naturalistic setting, in order to gain insights not possible using other types of
research. Gall, Gall and Borg [27] (1999), however, define qualitative research as “making sparring use of
numbers or statistical analyses, but instead, relying heavily on verbal data and subjective analysis”. Collectively,
for qualitative studies, the concern rather shifts to a consideration of how dependably and thoughtfully the
researcher conducted the study, rather than if the results can be replicated. This standard of practice assesses
another researcher’s agreement with the results of the study given the data assembled [28] (Rossman and Rallis,
1998).
Apart from the debatable issue of replication, critics have identified the following as what they perceive
to be weaknesses of the qualitative method:
 The claim that qualitative research is unscientific;
 The claim that qualitative research is subjective, and therefore full of bias;
 The claim that qualitative research lacks the rigors of quantitative studies;
 The claim that qualitative research lacks inherent internal controls; and
 The claim that qualitative research lacks measures of validity and reliability (Silverman, 2001).
It has overly been argued that qualitative research is full of unquantifiable data that are not subjected to
a statistical analysis, and that, without statistical analysis, a study loses its scientific appeal. However, it is worth
mentioning that figures alone do not make much sense unless they are explained qualitatively. Indeed, it has
been reported that mere figures do not render a study scientific [29] (Bogdan and Biklen, 1992). Further doubts
about the reliability of qualitative research are based on the idea applicability or generalizability of the findings.
However, not all studies are concerned with applicability or generalization. It is possible to employ other
specific methods in order to have the findings of research replicated, verified, or even falsified [30] (Kamwendo,
2004).
6.2 Quantitative Analysis
Quantitative research has been described as a collection of numerical data in order to explain, control,
or predict phenomena of interest [26] (Gay and Airasian, 2000). It has also been described as empirical research
involving numerical data [31] (Punch, 1998). A more thorough definition is however offered by Creswell [25]
(1994) who explains quantitative research as “an inquiry into a social or human problem, based on testing a
theory composed of variables, measured with numbers, and analyzed with statistical procedures, in order to
determine whether the predictive generalizations of the theory hold true”. Quantitative research is therefore
viewed as relying very heavily on numerical data and statistical analysis. The analysis is built upon statistical
methods relating to samples and populations, and data from either primary or secondary sources. The entire

process involves data-manipulation and decision making, guided by a mixture of intelligent ideas, insight,
experience of the analyst and the complexity or otherwise of the data itself.
In summary, quantitative research provides less detail on behaviour, style and motivation, and are
based on larger sample sizes that tend to be more reliable and representative of the population. This type of
research is also amenable to replication, and the analysis of the results is more reliable, valid and objective. To
further increase the accuracy, the sample sizes would have to increase to 500-2000 or more, depending upon the
subject matter and complexity of questioning [26] (Gay and Airasian, 2000).
Finally, Bowen [1] (2005) proposes seven cardinal lessons for effectively conducting research using
contextualized scientific tools, instruments and methods. These seven lessons have been modified to suit the
purposes of the study under review as follows:
1. Read, Read, and Read
2. Consult Experts
3. Stick to Scientific Regulations
4. Pay Attention to Rigor and Reliability
5. Give Accurate Details of the Methodology
6. Dont Hesitate to Include Numerical Data
7. Publish
VII. Conclusion
This article provides, discusses, and analyses some of the key methods of qualitative/quantitative
research. It discusses the usefulness and applicability of the research methodologies. It has contextualized the
research methodologies, and further explained how they work and why a particular approach is selected during a
research endeaviour.
Any scientific research should endeavour to deploy an appropriate method aimed at improving quality
and implementation. The arguments presented in this paper can serve as guidelines for both experienced,
inexperienced, as well as would-be researchers who are likely to avoid some of the recurring mistakes and
difficulties, while writing academic papers for international audiences.
It is recommended that authors are mindful of the Journal guidelines when submitting papers for
publication. It is also helpful to browse articles and abstracts in order to know the types of articles the journals
typically publish. Contacting the appropriate editor to determine the fit between the proposed article and the
journal to which it is being submitted is also essential because this can save a great deal of time and resources.
Choosing a research approach that suites the purposes of a research study is entirely the prerogative of the
researcher. What actually matters in choosing a particular research approach is the ability to logically represent
the idea in a sequence that tells the whole story [32] (Maxwell, 2005).
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