Research Methodology
Research Methods versus Methodology
It
seems appropriate at this juncture to explain the difference between research
methods and research methodology.
Research methods may be understood as all those methods/techniques that
are used for
conduction of research. Research methods or techniques, thus, refer
to the methods the researchers
use in performing research operations. In other words, all those
methods which are used by the researcher during the course of studying his
research problem are termed as research methods. Since the object of research,
particularly the applied research, it to arrive at a solution for a given
problem, the available data and the unknown aspects of the problem have to be
related to each other to make a solution possible. Keeping this in view,
research methods can be put into the following three groups:
1.
In the first group we include
those methods which are concerned with the collection of data. These methods
will be used where the data already available are not sufficient to arrive at
the required solution;
2.
The second group consists of
those statistical techniques which are used for establishing relationships
between the data and the unknowns;
3.
The third group consists of those
methods which are used to evaluate the accuracy of the results obtained.
It
may be understood as a science of studying how research is done scientifically.
In it we study the various steps that are generally adopted by a researcher in
studying his research problem along with the logic behind them. It is necessary
for the researcher to know not only the research methods/techniques but also
the methodology. Researchers not only need to know how to develop certain
indices or tests, how to calculate the mean, the mode, the median or the standard
deviation or chi-square, how to apply particular research techniques, but they
also need to know which of these methods or techniques, are relevant and which
are not, and what would they mean and indicate and why. Researchers also need
to understand the assumptions underlying various techniques and they need to
know the criteria by which they can decide that certain techniques and
procedures will be applicable to certain problems and others will not. All this
means that it is necessary for the researcher to design his methodology for his
problem as the same may differ from problem to problem. For example, an
architect, who designs a building, has to consciously evaluate the basis of his
decisions, i.e., he has to evaluate why and on what basis he selects particular
size, number and location of doors, windows and ventilators, uses particular
materials and not others and the like. Similarly, in research the scientist has
to expose the research decisions to evaluation before they are implemented. He
has to specify very clearly and precisely what decisions he selects and why he
selects them so that they can be evaluated by others also.
From
what has been stated above, we can say that research methodology has many
dimensions and research methods do constitute a part of the research
methodology. The scope of research methodology is wider than that of research
methods. Thus, when we talk of research methodology we not only talk
of the research methods but also consider the logic behind the methods we use
in the context of our research study and explain why we are using a
particular method or technique and why we are not using others so that
research results are capable of being evaluated either by the researcher
himself or by others. Why a research study has been undertaken, how the
research problem has been defined, in what way and why the hypothesis has been
formulated, what data have been collected and what particular method has been
adopted, why particular technique
of
analysing data has been used and a host of similar other questions are usually
answered when we talk of research methodology concerning a research problem or
study.
The
chart indicates that the research process consists of a number of closely
related activities,
As
shown through I to VII. But such activities overlap
continuously rather than following a strictly prescribed sequence. At times,
the first step determines the nature of the last step to be undertaken. If
subsequent procedures have not been taken into account in the early stages, serious
difficulties may arise which may even prevent the completion of the study. One
should remember that the various steps involved in a research process are not
mutually exclusive; nor they are separate and distinct. They do not necessarily
follow each other in any specific order and the researcher has to be constantly
anticipating at each step in the research process the requirements of the
subsequent steps. However, the following order concerning various steps
provides a useful procedural guideline regarding the research process: (1)
formulating the research problem; (2) extensive literature survey; (3)
developing the hypothesis; (4) preparing the research design; (5) determining
sample design; (6) collecting the data; (7) execution of the project; (8) analysis
of data; (9) hypothesis testing; (10) generalisations and interpretation, and
(11) preparation of the report or presentation of the results, i.e., formal
write-up of conclusions reached. A brief description of the above stated steps
will be helpful.
1.
Formulating the research problem:
There are two types of research problems, viz., those which relate
to states of nature and those which relate to relationships between variables.
At the very outset the researcher must single out the problem he wants to
study, i.e., he must decide the general area of interest or aspect of a
subject-matter that he would like to inquire into. Initially the problem may be
stated in a broad general way and then the ambiguities, if any, relating to the
problem be resolved. Then, the feasibility of a particular solution has to be
considered before a working formulation of the problem can be set up. The
formulation of a general topic into a specific research problem, thus,
constitutes the first step in a scientific enquiry. Essentially two steps are
involved in formulating the research problem, viz., understanding the problem
thoroughly, and rephrasing the same into meaningful terms from an analytical
point of view. The best way of understanding the problem is to discuss it with
one’s own colleagues or with those having some expertise in the matter. In an
academic institution the researcher can seek the help from a guide who is
usually an experienced man and has several research problems in mind. Often,
the guide puts forth the problem in general terms and it is up to the
researcher to narrow it down and phrase the problem in operational terms. In
private business units or in governmental organisations, the problem is usually
earmarked by the administrative agencies with whom the researcher can discuss
as to how the problem originally came about and what considerations are involved
in its possible solutions.
The researcher must at the same time examine all available
literature to get himself acquainted with the selected problem. He may review
two types of literature—the conceptual literature concerning the concepts and
theories, and the empirical literature consisting of studies made earlier which
are similar to the one proposed. The basic outcome of this review will be the
knowledge as to what data and other materials are available for operational
purposes which will enable the researcher to specify his own research problem
in a meaningful context. After this the researcher rephrases the problem into
analytical or operational terms i.e., to put the problem in as specific terms
as possible. This task of formulating, or defining, a research problem is a
step of greatest importance in the entire research process. The problem to be
investigated must be defined unambiguously for that will help discriminating
relevant data from irrelevant ones. Care must, however, be taken to verify the
objectivity and validity of the background facts concerning the problem.
Professor W.A. Neiswanger correctly states that the statement of the objective is
of basic importance because it determines the data which are to be collected,
the characteristics of the data which are relevant, relations which are to be
explored, the choice of techniques to be used in these explorations and the
form of the final report. If there are certain pertinent terms, the same should
be clearly defined along with the task of formulating the problem. In fact,
formulation of the problem often follows a sequential pattern where a number of
formulations are set up, each formulation more specific than the preceeding
one, each one phrased in more analytical terms, and each more realistic in
terms of the available data and resources.
2.
Extensive literature survey:
Once the problem is formulated, a brief summary of it should be
written down. It is compulsory for a research worker writing a thesis for a
Ph.D. degree to write a synopsis of the topic and submit it to the necessary
Committee or the Research Board for approval. At this juncture the researcher
should undertake extensive literature survey connected with the problem. For
this purpose, the abstracting and indexing journals and published or
unpublished bibliographies are the first place to go to. Academic journals,
conference proceedings, government reports, books etc., must be tapped
depending on the nature of the problem. In this process, it should be
remembered that one source will lead to another. The earlier studies, if any,
which are similar to
the study in hand should be carefully studied. A good library will
be a great help to the researcher at this stage.
3.
Development of working hypotheses:
After extensive literature survey, researcher should state in
clear terms the working hypothesis or hypotheses. Working hypothesis is
tentative assumption made in order to draw out and test its logical or
empirical consequences. As such the manner in which research hypotheses are
developed is particularly important since they provide the focal point for
research. They also affect the manner in which tests must be conducted in the analysis
of data and indirectly the quality of data which is required for the analysis.
In most types of research, the development of working hypothesis plays an
important role. Hypothesis should be very specific and limited to the piece of
research in hand because it has to be tested. The role of the hypothesis is to
guide the researcher by delimiting the area of research and to keep him on the
right track. It sharpens
his thinking and focuses attention on the more important facets of
the problem. It also indicates the type of data required and the type of
methods of data analysis to be used. How does one go about developing working
hypotheses? The answer is by using the following approach: (a) Discussions with
colleagues and experts about the problem, its origin and the objectives in
seeking a solution; (b) Examination of data and records, if available,
concerning the problem for possible trends, peculiarities and other clues; (c)
Review of similar studies in the area or of the studies on similar problems; and
(d) Exploratory personal investigation which involves original field interviews
on a limited scale with interested parties and individuals with a view to
secure greater insight into the practical aspects of the problem. Thus, working
hypotheses arise as a result of a-priori thinking about the subject,
examination of the available data and material including related studies and
the counsel of experts and interested parties. Working hypotheses are more
useful when stated in precise and clearly defined terms. It may as well be
remembered that occasionally we may encounter a problem where we do not need
working hypotheses, specially in the case of exploratory or formulative
researches which do not aim at testing the hypothesis. But as a general rule,
specification of working hypotheses in another basic step of the research
process in most research problems.
4.
Preparing the research design:
The research problem having been formulated in clear cut terms,
the researcher will be required to prepare a research design, i.e., he will
have to state the conceptual structure within which research would be
conducted. The preparation of such a design facilitates research to be as
efficient as possible yielding maximal information. In other words, the
function of research design is to provide for the collection of relevant
evidence with minimal expenditure of effort, time and money. But how all these
can be achieved depends mainly on the research purpose. Research purposes may
be grouped into four categories, viz., (i) Exploration, (ii) Description,
(iii) Diagnosis, and (iv) Experimentation. A flexible research
design which provides opportunity for considering many different aspects of a
problem is considered appropriate if the purpose of the research study is that
of exploration. But when the purpose happens to be an accurate description of a
situation or of an association between variables, the suitable design will be
one that minimises bias and maximises the reliability of the data collected and
analysed. There are several research designs, such as, experimental and
non-experimental hypothesis testing. Experimental designs can be either
informal designs (such as before-and-after without control, after-only with
control, before-and-after with control) or formal designs (such as completely
randomized design, randomized block design, Latin square design, simple and
complex factorial designs), out of which the researcher must select one for his
own project. The preparation of the research design, appropriate for a
particular research problem, involves usually the consideration of the
following: (i) the means of obtaining the information; (ii) the availability
and skills of the researcher and his staff (if any); (iii) explanation of the
way in which selected means of obtaining information will be organized and the
reasoning leading to the selection; (iv) the time available for research; and
(v) the cost factor relating to research, i.e., the finance available for the
purpose.
5.
Determining sample design:
SAMPLING
What is a sample?
A sample is a finite part of
a statistical population whose properties are studied to gain information about
the whole (Webster, 1985). When dealing with people, it can be defined as a set
of respondents (people) selected from a
larger population for the purpose of a survey.
What is a population?
A population is a group of
individual persons, objects, or items from which samples are taken for
measurement for example a population of students, teachers, trainees,
examination papers, textbooks, etc..
What is sampling?
Sampling is the act,
process, or technique of selecting a suitable sample, or a representative part
of a population for the purpose of determining parameters (things that decide
or limit the way in which something can be done) or characteristics of the
whole population.
What is the purpose of
sampling?
To draw conclusions about
populations from samples, we must use inferential statistics which enables us
to determine a population`s characteristics by directly observing only a
portion (or sample) of the population.
We obtain a sample rather
than a complete enumeration (a census) of the population for many reasons.
Obviously, it is cheaper to observe a part rather than the whole, but we should
prepare ourselves to cope with the dangers of using samples.
Types of samples
There are three primary
kinds of samples: the convenience sample, the judgement sample, and the random
sample. They differ in the manner in which the elementary units are chosen.
The convenience sample
A convenience sample results
when the more convenient elementary units are chosen from a population for
observation.
The judgement sample
A judgement sample is
obtained according to the discretion of someone who is familiar with the
relevant characteristics of the population.
The random sample
This may be the most
important type of sample. A random sample allows a known probability that each
elementary unit will be chosen. For this reason, it is sometimes referred to as
a probability sample. This is the type of sampling that is used in
lotteries and raffles. For example, if you want to select 10 teachers randomly
from a population of 100, you can write their names, fold them up, mix them
thoroughly then pick ten. In this case, every name had any equal chance of
being picked. Random numbers can also be used.
TYPES OF RANDOM SAMPLES
A simple random sample
A simple random sample is
obtained by choosing elementary units in search a way that each unit in the
population has an equal chance of being selected. A simple random sample is
free from sampling bias. However, using
a random number table to choose the elementary units can be cumbersome. If the
sample is to be collected by a person untrained in statistics, then
instructions may be misinterpreted and selections may be made improperly.
Instead of using a list of random numbers, data collection can be simplified by
selecting say every 10th or 100th unit after the first unit has been chosen
randomly. Such a procedure is called systematic random sampling.
A systematic random sample
A systematic random sample
is obtained by selecting one unit on a random basis and choosing additional
elementary units at evenly spaced intervals until the desired number of units
is obtained. For example, there are 100 students in your class. You want a
sample of 20 from these 100 and you have their names listed on a piece of paper
may be in an alphabetical order. If you choose to use systematic random
sampling, divide 100 by 20, you will get 5. Randomly select any number between
1 and five. Suppose the number you have
picked is 4, that will be your starting number. So student number 4 has been
selected. From there you will select every 5th name until you reach the last
one, number one hundred. You will end up
with 20 selected students
A stratified sample
A stratified sample is
obtained by independently selecting a separate simple random sample from each
population stratum. A population can be divided into different groups may be
based on some characteristic or variable like income or education. Like anybody
with ten years of education will be in
group A, between 10 and 20 group B and between 20 and 30 group C. These
groups are referred to as strata. You can then randomly select from each
stratum a given number of units which may be based on proportion like if group
A has 100 persons while group B has 50, and C has 30 you may decide you will
take 10% of each. So you end up with 10 from group A, 5 from group B and 3 from
group C.
A cluster sample
A cluster sample is obtained
by selecting clusters from the population on the basis of simple random
sampling. The sample comprises a census of each random cluster selected. For
example, a cluster may be something like a village or a school, a state. So you
decide all the elementary schools in Khartoum State are clusters. You want 20
schools selected. You can use simple or systematic random sampling to select
the schools, then every school selected becomes a cluster. If your interest is
to interview teachers on their opinion of some new textbook which has been
introduced, then all the teachers in a cluster must be interviewed. Though very
economical, cluster sampling is very susceptible to sampling bias. Like for the
above case, you are likely to get similar responses from teachers in one school
due to the fact that they interact with one another.
Purposeful sampling
Purposeful sampling selects
information-rich cases for in-depth study. Size and specific cases depend on
the study purpose. There are different types of purposeful sampling. Some of
these are:
1. Intensity: This method
selects excellent examples of the phenomenon of interest (but not extreme
examples), and allows the researcher to select a small number of cases—but it
requires prior knowledge to know what to look for.
2. Maximum Variation: This
type of sampling purposely incorporates participants that exhibit wide
variability on the phenomenon of interest, which allows for investigation of
variables across a variety of people and situations
3. Homogenous: This selects a small,
homogenous group of participants. This is useful for investigating a group or
groups in depth.
4. Typical
Case: This is
exactly what it sounds like: a sample is drawn from a group that is considered
typical (average) for your variables of interest. This is useful for
understanding phenomena in ordinary situations.
5. Stratified
Purposeful: For
this method, samples are drawn from subgroups. For example, if you wanted to
sample university students you could stratify the sample by class and then
select the appropriate number of sophomores, freshmen, juniors, and seniors
(Babbie, 2007). This method results in a more credible study that is
representative of your population of interest.
6. Criterion: For this
method, the researcher sets some criteria (i.e., students in 3rd grade). This
is useful to investigate phenomena in a specific set of people.
7. Convenience: This is
exactly what it sounds like: obtaining a sample that is easy to find. On
college campuses, a convenience sample would be college undergraduates.
8. Combination/ Mixed Purposeful:
This method combines one or more sampling techniques discussed
above to allow for the best sample possible
6.
Collecting the data:
In dealing with any real life problem it is often found that data
at hand are inadequate, and hence, it becomes necessary to collect data that
are appropriate. There are several ways of collecting the appropriate data
which differ considerably in context of money costs, time and other resources
at the disposal of the researcher. Primary data can be collected either through
experiment or through survey. If the researcher conducts an experiment, he
observes some quantitative measurements, or the data, with the help of which he
examines the truth contained in his hypothesis. But in the case of a survey,
data can be collected by any one or more of the following ways:
(i) By observation: This method implies the collection of
information by way of investigator’s own observation, without interviewing the
respondents. The information obtained relates to what is currently happening
and is not complicated by either the past behaviour or future intentions or
attitudes of respondents. This method is no doubt an expensive method and the
information provided by this method is also very limited. As such this method
is not suitable in inquiries where large samples are concerned.
(ii) Through personal interview: The investigator follows a
rigid procedure and seeks answers to a set of pre-conceived questions through
personal interviews. This method of collecting data is usually carried out in a
structured way where output depends upon the ability of the interviewer to a
large extent.
(iii) Through telephone interviews: This method of
collecting information involves contacting the respondents on telephone itself.
This is not a very widely used method but it plays an important role in
industrial surveys in developed regions, particularly, when the survey has to
be accomplished in a very limited time.
(iv) By mailing of questionnaires: The researcher and the
respondents do come in contact with each other if this method of survey is
adopted. Questionnaires are mailed to the respondents with a request to return
after completing the same. It is the most extensively used method in various
economic and business surveys. Before applying this method, usually a Pilot
Study for testing the questionnaire is conduced which reveals the weaknesses,
if any, of the questionnaire. Questionnaire to be used must be prepared very
carefully so that it may prove to be effective in collecting the relevant
information.
(v) Through schedules: Under this method the enumerators
are appointed and given training. They are provided with schedules containing
relevant questions. These enumerators go to respondents with these schedules.
Data are collected by filling up the schedules by enumerators on the basis of
replies given by respondents. Much depends upon the capability of enumerators
so far as this method is concerned. Some occasional field checks on the work of
the enumerators may ensure sincere work.
The researcher should select one of these methods of collecting
the data taking into consideration the nature of investigation, objective and
scope of the inquiry, finanical resources, available time and the desired
degree of accuracy. Though he should pay attention to all these factors but
much depends upon the ability and experience of the researcher. In this context
Dr A.L. Bowley very aptly remarks that in collection of statistical data
commonsense is the chief requisite and experience the chief teacher.
7. Execution of
the project:
Execution of the project is a very important step in the research
process. If the execution of the project proceeds on correct lines, the data to
be collected would be adequate and dependable. The researcher should see that
the project is executed in a systematic manner and in time. If the survey is to
be conducted by means of structured questionnaires, data can be readily
machine-processed. In such a situation, questions as well as the possible
answers may be coded. If the data are to be collected through interviewers,
arrangements should be made for proper selection and training of the
interviewers. The training may be given with the help of instruction manuals
which explain clearly the job of the interviewers at each step. Occasional
field checks should be made to ensure that the interviewers are doing their
assigned job sincerely and efficiently. A careful watch should be kept for
unanticipated factors in order to keep the survey as much realistic as possible.
This, in other words, means that steps should be taken to ensure that the
survey is under statistical control so that the collected information is in
accordance with the pre-defined standard of accuracy. If some of the
respondents do not cooperate, some suitable methods should be designed to
tackle this problem. One method of dealing with the non-response problem is to
make a list of the non-respondents and take a small sub-sample of them, and
then with the help of experts vigorous efforts can be made for securing
response.
8. Analysis of
data:
After the data have been collected, the researcher turns to the
task of analyzing them. The analysis of data requires a number of closely
related operations such as establishment of categories, the application of
these categories to raw data through coding, tabulation and then drawing
statistical inferences. The unwieldy data should necessarily be condensed into
a few manageable groups and tables for further analysis. Thus, researcher
should classify the raw data into some purposeful and usable categories. Coding
operation is usually done at this stage through which the categories of
data are transformed into symbols that may be tabulated and counted. Editing
is the procedure that improves the quality of the data for coding. With
coding the stage is ready for tabulation. Tabulation is a part of the
technical procedure wherein the classified data are put in the form of tables.
The mechanical devices can be made use of at this juncture. A great deal of
data, specially in large inquiries, is tabulated by computers. Computers not
only save time but also make it possible to study large number of variables
affecting a problem simultaneously. Analysis work after tabulation is generally
based on the computation of various percentages, coefficients, etc., by
applying various well defined statistical formulae. In the process of analysis,
relationships or differences supporting or conflicting with original or new
hypotheses should be subjected to tests of significance to determine with what
validity data can be said to indicate any conclusion(s). For instance, if there
are two samples of weekly wages, each sample being drawn from factories in
different parts of the same city, giving two different mean values, then our problem
may be whether the two mean values are significantly different or the
difference is just a matter of chance. Through the use of statistical tests we
can establish whether such a difference is a real one or is the result of
random fluctuations. If the difference happens to be real, the inference will
be that the two samples come from different universes and if the difference is
due to chance, the conclusion would be that the two samples belong to the same
universe. Similarly, the technique of analysis of variance can help us in
analysing whether three or more varieties of seeds grown on certain fields
yield significantly different results or not. In brief, the researcher can
analyse the collected data with the help of various statistical measures.
9.
Hypothesis-testing:
After analysing the data as stated above, the researcher is in a
position to test the hypotheses, if any, he had formulated earlier. Do the
facts support the hypotheses or they happen to be contrary? This is the usual
question which should be answered while testing hypotheses. Various tests, such
as Chi square test, t-test, F-test, have been developed by
statisticians for the purpose. The hypotheses may be tested through the use of
one or more of such tests, depending upon the nature and object of research
inquiry. Hypothesis-testing will result in either accepting the hypothesis
or in rejecting it. If the researcher had no hypotheses to start
with, generalisations established on the basis of data may be stated as
hypotheses to be tested by subsequent researches in times to come.
10.
Generalisations and interpretation:
If a hypothesis is tested and upheld several times, it may be
possible for the researcher to arrive at generalisation, i.e., to build a
theory. As a matter of fact, the real value of research lies in its ability to
arrive at certain generalisations. If the researcher had no hypothesis to start
with, he might seek to explain his findings on the basis of some theory. It is
known as interpretation. The process of interpretation may quite often trigger
off new questions which in turn may lead to further researches.
Research
Instruments
Questionnaires
What is a questionnaire?
Questionnaires are one of
the most common and popular tools to gather data from a large number of people.
A good questionnaire can be
a powerful tool to inform your evaluation, and a poorly designed questionnaire
can make life difficult for both those that have to complete it, and those that
have to analyse the data.
Questionnaire layout and
design
Questionnaire layout
•
Making sure the
layout does not look cluttered. Use adequate spacing between questions.
•
Ensuring the
questions are numbered and presented in a logical sequence. Group questions by
topics or themes.
•
Starting with easier
or less controversial questions and finishing with more personal questions,
including demographic details such as age and income.
•
Using larger or bold
font to attract
•
The shorter the
better.
•
Most people are
time-poor, and a long questionnaire risks limiting your response rate.
•
A well-designed
questionnaire should not take more than 10 minutes to complete.
•
Remember to only ask
the questions that you NEED to have answers for.
Invitation and instructions
•
The questionnaire
should clearly outline why you want people to take part, and the importance of
their participation.
•
A strong invitation
that provides respondents with a sense that their answers and opinions are
valued and respected should increase the response rate.
•
It is important that
you have clear instructions at the start of the questionnaire that explains:
•
the purpose of the
questions
•
who the information
is for and how it will be used
•
the confidentiality
of the answers
•
deadlines for
completion
•
It is also important
to have clear instructions as to how to answer questions.
•
Instructions need to
be provided at the start of each new section that uses a different answering
format or response scale.
Things to consider in
instructions include whether you want respondents to:
•
one answer only
•
select all that apply
•
rate the answers
•
provide a written
answer.
Wording of questions
•
The wording of
questions is critical in ensuring you obtain the information required to answer
your evaluation questions.
•
This includes:
1.
using language that
is appropriate to the audience
2.
using clear, simple
questions that avoid ambiguity, double meanings, and jargon,
3.
avoiding leading
questions that can lead to bias.
Questions can fall into the
following categories:
•
In relation to the
content of the question:
•
Factual questions
•
Factual questions are
those that can be verified in some way.
•
Non-factual questions
•
Non-factual questions
refer to gauging the knowledge, beliefs, attitudes, and opinions.
•
In relation to the
form of the question
•
Open-ended question
•
A question where the
respondent writes their own answer. This allows respondents to think about the
question, provide suggestions, or test their knowledge, but it is harder to
analyse.
•
Close-ended question
•
A question where the
respondent has to select their answer from the range of responses provided.
•
The range of
responses can vary from two-option answers, to ratings, ranking, or statements.
Tips on Wording Questions
•
Avoid
double-barrelled questions for example. “Do you take action to correct errors
and mistakes?”
•
This should be broken down into two questions.
•
Be specific about the
subject of questions, for example “Do you take action to correct errors?”
•
This can be broken
down to specific actions, such as supplying the correct from, rewording the
error etc.
•
The same applies for
attitudes and opinions - be as specific as possible in order to obtain the
information you want.
•
It is also important
to be specific about time frames.
•
Be specific about
timeframes in questions, for example inn a questions such as “Have you taken
action to correct errors in recent months?”, ‘recent months’ may not be
specific enough for your evaluation.
•
It may be best to use more specific
timeframes, such as “Since the training workshop held in July, have you taken
action to correct errors by supplying the correct from\/
•
Avoid leading or
loaded questions, for example “Have you stopped correcting errors by supplying
the correct from?”
•
This is likely to
lead to most respondents answering “yes”.
•
Further, a “yes”
answer also does not differentiate between those who used to correct errors by
supplying the correct from were taking long showers, and have stopped doing so since the training workshop
, and those who have never used this technique in their life.
Likert (/ˈlɪkərt/) scale is a psychometric scale commonly
involved in research that employs questionnaires. It is the most widely used
approach to scaling responses in survey research. This scale us named after its
inventor, psychologist Rensis Likert. When responding to a Likert questionnaire item, respondents
specify their level of agreement or disagreement on a symmetric agree-disagree
scale for a series of statements. Thus, the range captures the intensity of
their feelings for a given item.
•
It is
considered symmetric or "balanced" because there are equal amounts of
positive and negative positions.
•
Often five ordered
response levels are used, hence is the ‘5-point Likert Scale’
•
Strongly disagree
•
Disagree
•
Neutral (undecided)
•
Agree
•
Strongly agree
COMMON VERBS IN TECHNICAL
RESEARCH REPORTING
You will find below some
examples of verbs which appear to be commonly used in writing up research:
In English, there is a tendency to PERSONIFY the study:
The present study
focuses on the impact of new technologies
used in e-learning on the learning
outcomes of EFL students.
|
This study investigates
the significance of using visual/audio aids in the teaching of
vocabulary for young learners.
|
This research attempts to establish a correlation between learning
styles and learning strategies within the framework of Bloom’s taxonomy.
|
We do, however, also find examples of the pattern “the aim is to
(verb)…..”:
The objective of this study is to investigate the potentiality of supplementary
readers on developing the writing skills of the students.
|
The purpose of this study is to explore the influence of classroom language
on the fluency of the students.
|
Publications in
the recent literature indicate that both traditional and
non-traditional techniques are widely used in the teaching of pronunciation.
|
John and Jack (1997) have
shown that accurate values can
be obtained by carrying out cross-sectional studies..
|
John et al
[2000] presented the most thorough and complete
review of recent innovations in the field.
|
Jack [2010] observed that the third model performed best
in large crowded classes.
|
John [1998] investigated the phenomenon using a series of
experiments involving different types of teacher training.
|
Discussing Methods
Samples were taken simultaneously from early starters
and late starters .
|
Data was obtained by taking hool leaving examinations.
|
For each case, a
flow chart of activity was
developed.
|
A large amount of
data was collected over a range of conditions.
|
Pre- and post-tests
were carried out in multi-lingual
classes in order to determine the effect
of different languages on learning English.
|
Fig. (1.5) shows the pattern within mixed ability
groups.
|
Figure (2.5) shows the relationship between the
teaching techniques and the learning outcomes.
|
Table(5. 4) lists the scores recorded during
successive tests.
|
The experimental
findings are summarized in the table below.
|
Figure (5.10) suggests that recycling of vocabulary in this
book does not flow a systematic manner.
|
Presenting Results
The results show that the trend that emerged from the
experiment accurately describes the IQ-achievment elationship.
|
These results show that the effect magnitude can be
attributed to a large extent to the environmental factors.
|
Using the
modified approach resulted in improved performance compared to the
traditional approach.
|
It was found that the highest values were obtained
from the weaker samples.
|
The results suggest that the higher achievement can largely be due to clarity of objectives in
the teacher’s mind.
|
The data demonstrate that the pre-task activities prior
to writing enhance performance quality.
|
The reduced quality
of performance may be attributed to the poorly constructed test items.
|
However, it can be deduced that the improvement in
comprehension is a result of focusing more on high order thinking skills.
|
The results
obtained from the field studies were generally consistent with previous studies.
|
The technique
presented is limited in its effectiveness by the
fact that it improves on earlier techniques along one dimension only.
|
From the
experimental results, it can be concluded that
corporal punishment is the main reason
behind absenteeism.
|
Harvard Style
Proposal
Template
Sudan University of Science and
Technology
Faculty of Graduate Studies
MA Programme in ELT
A Proposal for Research
************************************************************************
Title
of the research:
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Student’s
Name:
------------------------------------------------------------------------------------------------------------
************************************************************************
1.0 Introduction
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
2.0 Statement of the problem
The problem which the present study attempts to
investigate is
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
--------------------------------------------------------------------------------------------------------------------------
3.0 Significance of the study
This study is considered significant for the
following reasons:
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
4.0 Objectives of the study
The study tries to realize the following objectives:
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
5.0 Research questions
The study will provide answers for the following
questions:
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
6.0 Research hypotheses
The study has the following as its hypotheses:
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
7.0 Methodology
The study will be
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
The following instruments will be used
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
The data will be analyized
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
8.0 Limitations of the study
Limitations are influences that the researcher cannot control.
They are the shortcomings, conditions or influences that cannot be controlled
by the researcher that place restrictions on your methodology and conclusions.
Any limitations that might influence the results should be mentioned.
- the instruments you utilized.
- the sample.
- time constraints.
9.0 Delimitations of the study
Delimitations are
choices made by the researcher which should be
mentioned. They describe the boundaries that you have set for the
study. This is the place to explain:
- the things that you are not doing (and why you have chosen not to do them).
- the literature you will not review (and why not).
- the population you are not studying (and why not).
- the methodological procedures you will not use (and why you will not use them).
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
10.0
Research
Outline
Chapter One: Introduction
1.0 Background
2.0 Statement of the problem
3.0 Significance of the study
4.0 Objectives of the study
5.0 Research questions
6.0 Hypotheses of the study
7.0 Methodology of the study
8.0 Limitations of the stuck
9.0 Delimitations
of the study
10.0
Summary
Chapter Two:
Theoretical Framework and Previous Studies
Chapter Three:
Methodology
Chapter Four: Data
Analysis and Discussion
Chapter Five:
Conclusion and Recommendation
11.0
References
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
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