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From www.pharm.chula.ac.th/research_design/sld002.htm
Qualitative
and quantitative research
are the two major approaches used in scientific inquiry. A comparison of the
distinguishing features of each of these approaches is presented in the
following table.
|
Qualitative |
Quantitative |
Purpose |
Gain insight into a problem through the interpretation
of narrative data |
Explain a problem or predict an outcome through the
interpretation of numerical data |
Approach to inquiry |
Inductive, subjective, interested in participants |
Deductive, objective, detached from participants |
Hypothesis |
Tentative, evolving |
Specific, testable |
Research Setting |
As natural as possible |
Controlled to the degree possible |
Sampling |
Selective, small sample to facilitate in-depth
understanding |
Random, large samples used from which generalizations
are made |
Measurement |
Non-standardized, is on-going |
Standardized, performed at the end |
Design and Methodology |
Flexible, specified in general terms in advance |
Structured, specified in detail in advance |
Data Collection |
Participant observation, taking detailed extensive
notes |
Non-participant; administration of tests, instruments,
surveys and questionnaires |
Data Analysis |
Ongoing, involves information synthesis |
Performed at the end; involves statistics, graphics
and measurement tools |
Data Interpretation |
Generalizations, speculations |
Formulated with a degree of certainty at the end |
Reporting |
Raw data are words, interpretive reports |
Raw data are numbers, impersonal objective reports |
From
http://www.dtfire.com/introduction_to_educational_research.htm |
Articles
THE SCIENTIFIC METHOD
Dr. Robert N. Tyzzer
From
http://www.humboldt.edu/~rnt7001/scientific_method_dr.htm
The Scientific Method
Validity and Confidence Levels
Hypotheses, Theories, Laws, and Scientific "Proof"
Scientific Observation and
"Counter-intuitive" Conclusions
Science and its methods result from human curiosity and from our attempt to
understand ourselves and the world around us. Science assumes that we can
learn how the universe “works” – that there are consistent laws of nature and
that we can discover them. The scientific method has proven to be a powerful
and reliable tool for doing so. Science also has limitations: It cannot
directly address subjects that are not part of the natural world, are natural
but beyond our observational abilities, or events that occur too rarely to
observe systematically. (However, technology such as microscopes, telescopes,
and many other scientific instruments can make what was once beyond observation
observable, thus increasing the reach of science. This apparently disturbs some
people.)
The
scientific method is essentially an organized,
systematic way to state and answer questions, and to solve problems. There is
no one single “official” scientific method, and the “steps” below usually blend
into a continuous process. The process also inevitably differs somewhat from
one discipline to another. However, outlines like the one below do help to
describe how science is done. There is also a review in the text.
-
STATE THE PROBLEM OR QUESTION
The problem is stated clearly and
specifically, based on initial observations, curiosity, or a recognized
problem. A precisely-stated problem increases the odds of eventually gaining
new knowledge.
-
OBSERVATION
(COLLECTION OF FURTHER
INFORMATION OR DATA)
Gathering of all available information
that is already known about the problem. May involve some preliminary
experiments. (There is obvious feedback between steps 1 and 2.)
-
STATE THE HYPOTHESIS
(A "BEST GUESS" ANSWER TO THE PROBLEM)
A good hypothesis relates and explains the known
facts. It should also predict new facts. It must be stated in
such a way that we can test it by experimentation or further
observation, or it is of no scientific value. Also, it must stated in a way
that would allow us to show if it is incorrect, i.e., it must be
"falsifiable." A scientist must be willing to accept the
possibility that his or her hypothesis is incorrect, and this point often
separates true science from pseudoscience. (In fact, most scientists work
hard to develop good hypotheses, and then spend a great deal of effort trying
to disprove them. Pseudoscientists tend to settle on a hypothesis that
suits their needs or expectations, and then spend a great deal of effort
trying to prove that they are "true". See the discussion of
scientific proof below.)
-
TEST THE HYPOTHESIS
(EXPERIMENTATION)
This is ideally done by carrying out a
controlled experiment, in which all variables except the one being
investigated (the variable factor) are controlled (do not vary in unknown
ways). However, in the life sciences, and especially in the social sciences,
controlling all of the variables is often impossible, and the test may be a
series of field observations under controlled conditions, etc. Many of the
differences between various sciences reflect differing ways in which they can
or do apply the scientific method.
-
EVALUATE RESULTS AND DRAW CONCLUSIONS
The validity
of the hypothesis is evaluated by examining the test results, to determine how
well the hypothesis predicted the experimental/observational results. There
are three general possibilities. The results may:
-
completely support the hypothesis (relatively rare except in instructional
settings, or perhaps confirmation of established points in new ways).
-
partly or incompletely support the hypothesis (common).
-
completely fail to support the hypothesis (not very common, except when
working in very new areas of science when several alternate and incompatible
hypotheses are undergoing initial testing)
Typically, the new experimental data are used to improve a hypothesis that has
been supported in some ways, or to refine the experimental procedure, and the
entire "hypothesize-test-evaluate" process is then repeated.
Are Our Conclusions Valid? – A Brief Look at
Confidence Levels
As the process outlined above proceeds,
a steadily more accurate description of what is being investigated emerges – and
in some cases earlier conclusions may be abandoned as new evidence accumulates.
Science is thus a “work in progress.” How confident can we be of the
conclusions? When are our conclusions “good enough?” A detailed discussion of
the statistics of confidence levels isn’t necessary here, but informally there
are a couple of important points to be made.
First, you can think of confidence levels as an estimate of
the odds of being right and/or wrong. If we decide that a certain conclusion is
valid at a 95% confidence level, perhaps based on a statistical analysis of the
experimental outcomes, it means we accept that there is a 5% chance that the
conclusion is actually incorrect.
Second, you have to consider the consequences of being wrong.
In most essentially academic research, a 95% confidence level is typical.
Usually the consequences of being wrong might be embarrassing, but not
dangerous. Similarly, we might be satisfied with explaining 95% of the
variation in a phenomenon we are investigating. However, in medical research,
where lives are a stake in our conclusions about the effectiveness and/or safety
of a new medication, a 99.9% confidence level might be far too low!
And in the social and behavioral sciences, sometimes being confident that you’ve
explained 75% of what is going on might be pretty good.
Hypotheses, Theories, Laws, and “Scientific Proof”
Usually the
scientific method results in steadily improving hypotheses, which do a better
and better job of predicting the outcome of experiments, observations, and
events in the world around us. If a major hypothesis (or set of related
hypotheses) survives the “test of time,” with a long pattern of repeated
verification and accurate prediction by a number of scientists, it may
eventually become accepted as a theory. Good theories not only
explain things – they also tend to generate new hypotheses that enable us to
learn even more.
Thus, if a scientific explanation is
considered to be a theory rather than a hypothesis, it indicates
a very high level of confidence. Unfortunately, most of the
public has it backwards, assuming that “theory” means “just a guess,” whereas
for most scientists the term implies a very high level of confidence that the
theory is valid.
There are several important related points involved here, some of which are
widely misunderstood by non-scientists. Ironically, science cannot
“prove” beyond any doubt that something is absolutely true.
We can't see the future, which could hold extremely rare but real exceptions to
well-supported theories. The best we can do is “fail to disprove.”
If a theory has never been shown to be false after repeated testing, our
confidence that it is probably true increases.
On the other hand, it
is possible to disprove a hypothesis or theory with a
single valid example that refutes it. However, in this case, we must
remember that (1) failing to support (or even disproving) one view does
NOT automatically mean that any given alternative or conflicting view is
automatically correct. The other view must also be adequately tested
before being accepted. (2) It is possible to refute one part of a complex
theory without affecting the confidence in other parts of it. Case in point:
Some earlier ideas in evolutionary biology that were widely held, such as the
assumption that it is always “slow and steady,” have now been rejected or
modified. This does not somehow “validate” creationism, or even shake the
overall confidence that evolution is a basic natural process. It just means we
learned more and cleared up some misconceptions.
What about “laws?”
In the simplest terms, a natural law is a theory or set of theories,
which have stood the test of time so well that we think that in this instance we
actually do have a basically complete and accurate understanding of some
particular aspect of how the universe works. Unfortunately, the term is often
used pretty loosely, even by scientists. Many of the “laws of physics”
certainly qualify, but (in my opinion) there is still too much we don’t know to
really talk about “laws of genetics.”
Scientific Observation And
Counter-Intuitive Conclusions
Finally,
one of the strengths of science, and a point that many people don't appreciate,
is that science can uncover patterns of nature that may be "counter-intuitive."
Common sense or intuition are NOT always reliable. For example, science has
demonstrated that the sun only seems to move and “come up in the
east,” because it is the earth itself that is rotating. Similarly, intuition
and even common sense seem to suggest that heavier objects will fall more
rapidly, but centuries ago Galileo showed that in fact all objects fall at the
same rate regardless of mass; it is air-resistance that makes light objects
seem to fall more slowly.
In my opinion, one problem that many people have with evolutionary biology is
that evolution is indeed a slow process observable only when you know what to
look for and how to look. Some of evolution may indeed be
counter-intuitive, but the scientific method enables us to discover what is
actually going on.
Some notes on the research process
Notes taken, with some modifications, from:
http://www.i-m-c.org/imcass/VUs/IMC/content.asp?id=1585
- Introduction
- The reality of research
- The research process
- Levels of research
- Research methods
- Experiment
- Survey/Field (or case) study
|
- Techniques of Research
- Observation
- Interviews
- Questionnaires
- Other
techniques
- Research
organizations
|
-
Introduction
It has been the experience of a good number of those working towards a
higher degree which involves a major research element that little or no
guidance is given on the research process itself. Frequently it seems to be
expected that knowledge of research is something to be ''picked up'' as one
progresses through the activity. While this is no doubt an important part of
the learning that takes place it is an approach which can lead to frustrations
and unnecessary failures along the way.
In the absence of any specific instruction, the higher degree researcher
may turn to the textbooks. A number now exist but many are quite detailed and
very specific. Few give even a brief introduction. This chapter is intended to
do that, and provide a basis for further reading and development. It looks at
the meaning of research and the processes involved, and briefly describes the
main methods and techniques employed. A brief glossary of basic terms helps
sort out some of the semantics. Finally, some guided reading is given with a
few comments on the contents.
The reality of research
It may seem irrelevant to ask what research is all about; since so many are
doing it, then most people (at least those carrying it out) must know what it
is all about. Some people consider it to be a cozy and personal activity that
could be indulged in from time to time from the safety of an armchair - and
certainly not stretching beyond a pile of books resting on the coffee-table.
To others, research is a vigorous and rigorous activity aimed at developing
new bodies of knowledge and is normally ''acceptable'' only in a physical
laboratory situation and is seen as ''the discovery of fact through a
systematic process of survey, hypothesis and experiment''.
This is somewhat closer to the more scientific approach than the ''cozy,
personal activity''. For many people research is a ''careful inquiry or
examination to discover new information or relationships and to expand and to
verify existing knowledge''. This immediately implies a vital role for
research - one of helping researchers to underline the effectiveness of their
approaches. It thus seems that research is an inevitable element of the total
professional process - its absence leading to obsolescence, reduced
effectiveness and dissatisfaction.
The possible range of research philosophies and approaches has grown
extensively over recent years. Each research organization and institution in
this field of development has different ideas and your understanding of these
variable dynamics can be an important input in determining the design of your
research process; establishing your "best research practice".
But research is not a ''careful enquiry'' for its own sake - it always
starts with some sort of problem, or at least should do if it is to be of use
to anyone. Whether the research is carried out for personal or practical
purposes, some reason exists for it. The problem may be that little is known
about some phenomenon and it would be good to have more knowledge about it
(sometimes known as ''pure'' or ''fundamental'' research). On the other hand,
the problem may have much more practical significance in that the research may
help us to do something we could not do before (often referred to as ''applied
research''). This is the essence of the American school of ''pragmatic
philosophers'' for whom any theorizing or research is a waste of time unless
it has ''cash value'', i.e. helps us to solve problems or understand things
better than we did before. Some forms of research can be much more practical
than others. But, if the problem is theoretical, then academic research is
necessary. The danger of falling between two stools lies in confusing academic
research with practical, i.e. operational, problems.
We have more concepts currently than we can adequately cope with. This is
certainly true of the behavioral sciences. Notions such as motivation,
perception and learning are highly developed and researched (if not agreed
upon) at the conceptual level yet lag far behind when it comes to applying
them to organizational situations. This point seems to be missed because so
much literature exists. What is now required is a greater emphasis on ensuring
that these concepts can be usefully employed. This is not to suggest that
highly sophisticated academic research is no longer required - it is, but at a
considerably reduced level. The poor image that research so often appears to
have is largely the result of inappropriate approaches based on academic
requirements - it would be more fruitful to adopt problem-centered approaches
based on situational requirements.
It is important at this juncture to refer briefly to a form of research,
known as action research. This form of research is essentially ''applied'' in
nature, even more so when it is realized that in action research the
researcher actually gets involved in what he is researching. It developed
primarily from the need of organizational analysts to explore thoroughly the
organization and at the same time to ''change'' and ''develop'' it. The
researcher acts as a ''catalyst'', a ''facilitator'', or even a ''mirror'' for
the organization - a very far cry from the ''objective impartiality'' of
traditional research. Action research therefore requires a joint approach - a
definite and agreed collaboration between organization and researcher.
The research process
Understanding research starts with knowing what, in essence, it is all
about. As we have seen, the process of research starts, usually, with some
form of problem or question. The problem/question may be the researcher's - he
may wish to know which learning theory of several is most relevant in
explaining certain levels of performance in different situations. The problem
may, of course, be initiated by a manager or someone else; perhaps wanting to
decide on the best technique for developing greater participation. In either
case, the requirement is for some information that will shed light on the
problem and help make a decision to solve it. It may be that solutions are not
the end result of the research, but rather the development of a new theory or
body of knowledge. Whatever the end result, the starting-point is represented
by an urge to find out, to explore, to evaluate - in short, to do research. In
between these end points exist a number of other steps.
Having defined, or at least acknowledged, the problem or area of interest,
researchers may carry out a preliminary study. This will enable them to set
out the parameters of the problem and to gain some idea of the essential
information to be sought. Such exploratory studies, free from too much bias or
preconceived ideas, can be of great value in setting the research in the right
direction. For example, the problem being looked at may have been concerned
with inadequate bonus earnings related to immediate post-training periods. The
temptation here is to blame the training. An exploratory study (usually much
less costly than the full treatment) might uncover poor supervision during the
first weeks on the job, or lack of understanding of the bonus scheme, as
possible alternative explanations. If this preliminary work is reasonably
thorough, the next stages can be less embracing than might otherwise be the
case. From this work the researcher may well set up a hypothesis, or a series
of hypotheses, which can then be tested against reality. In simple terms a
hypothesis is an imagined answer to a real question. In the example just
given, the question would be ''What causes low levels of bonus earnings in
immediate post-training periods?'' The answer, as we have seen, might be based
on guesswork, theoretical inspiration, or an appreciation of the factors
involved, or indeed a combination of all three. In our case, the hypothesis
might be that, in immediate post-training periods, operators will earn low
levels of bonus if inadequate supervision persists.
Having framed this hypothesis, researchers then seek information, or data,
which will allow them to test its validity. They might decide to check records
for low earnings, and see what situations led to this; or they could monitor
earnings and performance levels in two sections, one of which had a high ratio
of supervision, the other a low ratio. The data collected would then be
analyzed and subjected, possibly, to several statistical tests to determine
whether the proposed ''answer'' holds true or not and with what degree of
confidence or faith it can be accepted. The results of this analysis and
deliberation would be interpreted and communicated - via reports, seminars,
planning groups or whatever - to the ''client''. This phase can be a difficult
one, but need not be so inconclusive as so often is the case.
It should be stressed that the research process may not necessarily be
geared to the testing of hypotheses. Often a researcher will be more
interested in the exploratory stage, with a view to developing a number of
alternative hypotheses for later testing. If this proves successful, a useful
contribution will have been made to knowledge.
Levels of research
Not all research takes place at the same level of scientific
sophistication. The reason for this hinges on the state of knowledge of the
subject under investigation and the hoped-for outcomes (and uses) of the
research. In general, most sciences follow a similar pattern of development
and progression, and the social and behavioral sciences are no exception. In
some disciplines - such as, perhaps, biology and botany - the emphasis is on
the one level rather than another.
Perhaps the most basic level of research is that connected with describing
what exists around us. For example, we may not have enough knowledge about the
different types of training procedures in use - the first step in knowing
about them must be to describe them. Thus, job descriptions are quite useful
in telling us something about the work of managers. Having obtained a
description of these phenomena, the researcher may be interested in comparing
them for differences or similarities, as we would with job descriptions, in
order to establish some form of job evaluation framework, or training
characteristics. This process of comparing and grouping is known as
classification (or categorization).
The next level of research, that of explanation, then becomes possible. We
can start to ask questions such as why? and how? Our interest is in
understanding what is happening and seeking ways of representing this through
theoretical development, models, propositions and so on. You may want to know,
for example, why one student progresses more quickly under the same conditions
as someone else. Hopefully, all this knowledge will lead to a stage of
development where prediction of events, circumstances, behavior, etc. is
possible. In the physical and advanced sciences, this is the level at which
most researchers are now operating. None of the space programs would have been
possible if this were not so. In those disciplines concerned with human
behavior, it is exceptional to find some truly predictive theory based on
adequate research. While the testing of hypotheses may take on this predictive
form, we are still very much concerned with understanding and explaining human
behavior. In the field of training and education, this must be so - with
exceptions - until the disciplines associated with our efforts (psychology,
sociology, neurology and so on) become more precise and predictive themselves.
Research methods
A number of quite different methods can be employed in establishing the
acceptability or otherwise of a hypothesis, or helping solve a problem, and in
some cases these can be used to complement each other. Each has its advantages
and drawbacks, knowledge of which can aid you in assessing the feasibility of
achieving your objectives.
Experiment
The classical method, used in the physical sciences for many years, is the
experiment. In most physical sciences, if not all, the researcher aims to set
up a situation in which all variables can be controlled or varied at will. The
usual approach is to hold all variables constant except one. By varying this
one and monitoring changes in the ''output'', the relationship between
variables can be carefully studied and documented. In essence, the researcher
seeks to vary one of several independent (or input) variables while measuring
the effects on the dependent (or output) variable(s), keeping intervening
variables constant. For example, it would be possible to vary the petrol
mixture fed to an internal combustion engine and note the difference in speed
or power achieved but, at the same time, keeping (say) pressure or load
constant and controlling room temperature in the laboratory. When dealing with
human behavior, it is not possible strictly to adhere to this approach,
although sometimes one can get reasonably close. It might be possible to vary
the instructional techniques used for training managers and to measure their
achievements. Here, however, control over intervening variables such as
ability, intelligence, attitude and the like would be complex but the use of
matched groups (e.g. different groups of managers who had roughly the same IQ,
etc.) undergoing different approaches would take us a step nearer to the
''scientific'' method. We must not delude ourselves, however, into thinking
that this approach is ''foolproof'' - it is not. We can not control, for
example, the activities of people outside work - their love-lives, drinking
habits, arguments with spouses - which may well affect their performance. We
can, nonetheless, attempt to recognize and account for these factors.
Experiments can broadly be considered to be of two types - the laboratory
experiment, where the problem to be studied is divorced from the other facets
of the real world surrounding it, but not connected to it; and the field
experiment, where attempts are made to study the problem in its real setting
and to minimize the influences of seemingly unconnected factors or variables.
Most experiments in training and education are likely to be field experiments,
although the existence of training schools, simulators and so on, make
laboratory experiments quite attractive - even though the results may not have
much significance in the ''real'' setting.
Survey
This is almost certainly the most widely adopted method in the social
sciences - and most aspects of training and education are of a virtually
''social scientific'' nature. Surveys are usually cheaper, quicker and broader
in coverage than any experiment can hope to be but, on the other hand, very
often lack the control and in-depth exploration of the experiment. Relying in
the main on the techniques of sampling, interviewing and/or the questionnaire,
a survey can provide useful information on many problems or issues faced by
the trainer or educator. For example, you may have wondered how people feel
about the training provided; what subject-matters people think should be given
priority treatment on courses; if members of your organization think
participation is a good thing; or maybe what young managers think about their
career prospects. These and other issues can be explored using survey research
methods involving research instruments (e.g. questionnaires, checklists)
which, if constructed and tested adequately, can produce useful information.
By their very nature, surveys produce a lot of information - or data, as
researchers tend to call the basic responses to questions. Thought must
therefore be given to how it can be analyzed, preferably before the data are
collected. If this is not done, severe problems can arise causing frustration,
and even the abandonment of the project. Many excellent techniques of analysis
exist - from slogging it out by hand to computer processing, and can be found
described in a number of sources.
A survey, of course, is not the answer to all research requirements. Used
widely, it can produce useful information in a short time, but may suffer from
problems associated with people not wanting or bothering to respond to
questions; giving false answers where they do; treating it as a joke;
misunderstanding its purpose; and a host of others. Many of these problems can
be avoided or certainly reduced in terms of their impact on the results, but
only if care and attention are applied throughout. Carrying out a survey is
not so simple as some people would have us believe, nor is it so difficult and
scientifically immoral as others obviously do believe. As with all things in
life, it has its place - as a planned collection of information: no more, no
less!
Field (or case) study
Probably falling between the experiment and the survey in terms of
scientific acceptability, usefulness to the practitioner, and capacity to
produce theoretical advances, the field study (of which the case study is a
particular example) has considerable utility. While the techniques adopted
(e.g. interviews, observations, questionnaires) are similar to survey research
techniques, breadth of coverage is sacrificed for depth of probing and
understanding. Unlike the experiment, a field study does not normally involve
manipulating independent (or input, or causal) variables, except possibly
through statistical means. Rather, the study involves measuring, looking at -
studying! - what is there, and how it got there, i.e. it is historical. Two
types of study can be carried out. Exploratory studies seek to establish
''what is''; to discover significant variables and relations between them and
to lay the foundations for perhaps more scientific work aimed at testing
hypotheses. For example, you may have wondered what variables have the
greatest influence in on-the-job learning: a field study, probing through
discussions with, and observations of, the people involved, might throw some
light on this question. You might then be in a position to predict how the
variables would be related to each other in certain situations, and set out to
test this prediction. This would be a different form of field study:
hypothesis testing rather than hypothesis generating. The point to note about
field studies is that they do not attempt rigorous control - both a strength
and a weakness. The strength is that we obtain greater realism in the
research; the weakness is that things may get out of hand (sudden incidents
erupting) destroying the validity of the research. Field studies are often
costly and time-consuming, and may, of course, not produce much in the way of
earth-shattering conclusions. For most of our requirements, however, the
results can be rewarding. In a more specific sense, studies can be confined to
particular persons or units or organizations, and such case studies can
produce illuminating information. It must be recognized, though, that single
cases may have little value in explaining events outside the confines of the
case itself - it thus lacks ''generalizability''.
Techniques of research
While many texts refer to instrumentation, measurement devices, methods of
data collection and the like to mean the way in which the researcher goes
about acquiring information within one of the frameworks just described, it is
best to use the term ''technique''. This is because some of the other terms
are too precise (such as ''instrumentation'') or involve the use of terms
applied elsewhere (such as in ''data collection method''). In essence, we are
talking about ''how'' we do it as opposed to ''what'' we do or ''why'' we do
it. Only a brief description of the most general techniques is given here -
most are well discussed (if not always jargon-free) in texts on research
methods.
Observation
This is the most classical and natural of techniques. It simply involves
looking at what is going on - watching and listening. We all do it, most of us
badly because we do not know what to look for or how to record it. Work study
practitioners are probably the most competent of observers - after all, they
have been trained to do it. So, too, are most researchers and teachers.
Important in being a good observer is to have a wide scope, great capacity for
being alert, and the ability to pick up significant events. Here, technology
can aid us, offering services ranging from simple pen and paper through tape
recorders and cameras to videotapes. If carried out quietly, unobtrusively,
and shrewdly, observation can be a useful, if not powerful, technique. It does
not allow much scope for probing, exploring relationships further, unless used
in conjunction with other techniques. The combinational use of techniques is
now quite widespread and has much to commend it. Since, however, observation
is ''simple'' (if time-consuming) and opportunities for using it often present
themselves, it can be used quite effectively for its purpose - enabling a
general picture to be built up.
Interviews
It is quite tempting to suppose that the interview was first ''created'' by
the early observers who could not resist asking people why they were doing
what they were doing. Whatever its origin, the interview has a fundamental
role in social and behavioral research. It allows for exploration and probing
in depth and, if you have got the money and the time, in breadth as well. The
questions asked might stem from periods of general observation - and this is
to be preferred to just dreaming up questions in the bath! Interviews can be
unstructured and free-ranging: a general discussion, picking up points and
issues as they emerge and pursuing them in some depth; or they can be
structured around questions and issues determined in advance: based on a
literature search, preconceived ideas or prior investigation. If the
questioning is non-directive and free from biased or loaded questions; if the
interviewer is a good, attentive listener (and adept recorder); and if the
interviewee is of a mind to ''tell it like it is'', the results can be very
effective. However, problems of time, cost and sampling related to your
research objectives may mean that a full-scale interview program is not
possible or necessary. For example, you may wish to gain ideas for the
development of a job appraisal form - for this, a small number of ''pilot''
interviews would be quite effective.
If you wanted detailed views on the attitudes of people on your courses, a
wider program of in-depth interviews could be of use. Remember, too, that for
some purposes (e.g. where a ''testing of views'' is required), group
interviews have a role to play. While they can be a bit more difficult to
handle, the overall end results may provide more insights than would the same
people interviewed separately. Whatever sort of interview is relevant, the
means of recording information must be thought through in advance: whether to
tape record unstructured group interviews or take notes; how to design an
interview schedule (a ''questionnaire'' completed by the interviewer) for
structured interviews with maximum ease of recording and information capture
but minimum effect on interviewees - e.g. a feeling of ''not being listened
to'' as you write copious notes. As with all research matters, a little
advance thinking and planning can save a lot of later difficulties.
Questionnaires
While undoubtedly the most used technique - or, more correctly, instrument
- of researchers in the behavioral and social sciences, questionnaires do pose
problems. The major difficulties are associated with response rates, bias and
flexibility. Since questionnaires are important to the survey researcher (as
are interviews) the effect on the results of someone not responding must be
considered. Who are they, what are their characteristics, would they share the
views of those who did respond? are questions that have to be faced. Even when
reasonable response rates are achieved (more than 40 per cent) those problems
still exist, and in any case the resulting data may be biased. Bias might be
due to respondents anticipating the answers they think the researcher wants,
or putting down ''socially expected'' answers (on the basis of what is
''good'', or would be the ''right sort of thing to say''), or simply as a
result of finding some form of pattern to, say, the first ten questions and
assuming the pattern must be repeated. These and other difficulties can be
minimized, if not overcome, by careful design and piloting of the
questionnaire. Flexibility, however, is not so much a design problem (although
it can be considerably reduced by poor design) - it is much more a function of
the nature of the research questions being asked. Answers might range from
factual information (e.g. date of birth) - through simple ''yes''/''no''
replies (e.g. do you smoke?), to scale-type responses of the agree/disagree
form (e.g. training is a waste of time!) with a number of possible responses
in between. Often, however, the person filling in the questionnaire would like
to say ''yes - but!'' and has no opportunity to do so. It is the qualifying
''but'' that may be important and an interview would allow it to be explored.
For information of a somewhat broad and superficial nature (detail can be
obtained, of course, but mostly factual), involving large numbers of people,
the questionnaire is a useful technique and is relatively easy and cheap to
use. If thought is given to the major drawbacks and to the way in which the
data are to be analyzed, there is every reason to expect fairly reliable and
valid results. If preceded or backed-up by interviews or observations, many
additional benefits can be derived as well as difficulties minimized.
Other techniques
Many other techniques exist, some of them variations on those briefly
described here, others developed for specific purposes. They will not be
discussed here since most of them require considerable experience in their
design and use. They can be found in many of the early texts, for example
Helmstadter (1970), from which special references (e.g. to sociometry;
testing; scaling and projective techniques in psychology) can be obtained.
Often such techniques are limited
- Model: A
pictorial representation of concepts and relations between concepts, e.g.
graph or flow diagram. Not to be confused with the use of ''model'' which
implies ''perfect'' - as in ''a model job''!
- Paradigm: Another
word for model, but without the latter's value connotations.
- Proposition: A
statement or assertion concerning the problem or topic being researched:
origins and use mainly in philosophy, logic and mathematics.
- Reliability: A
term used mainly in connection with measurements (as via a questionnaire, or
test) and refers to repeatability, i.e. getting the same results on
different occasions when measuring the same entity which has not changed in
dimensions since it was first measured.
- Sample: A number
of people, objects or events chosen from a larger ''population'' on the
basis of representing (or being representative of) that population.
Sampling, and sampling theory, are important facets of survey research.
- Theory: A set of
general laws (interrelated concepts) that specifies relations among
variables. A theory thus represents, in a systematic way, the phenomena in
the world around us, explaining them and allowing predictions to be made or,
to borrow a phrase, ''there's nothing so practical as a good theory''!
- Validity: A
partner of ''reliability'', expressing the extent to which a test, say,
actually measures what it is supposed to measure, i.e. does it do the job
for which it was designed? Various types of validity are looked for as
evidence of this.
- Variable: In the
strictest sense, a variable is a symbol to which a number is assigned.
Constructs such as intelligence are also referred to as variables. The terms
''factor'' and ''variables'' are sometimes used interchangeably. Variables
may be continuous (time, age) or dichotomous (sex, marital status).
Sources of
information for researchers
Introduction
In all research a most important requirement, even before the research
proposals are developed, is to find out what other relevant research has been
(or is being) carried out by others. To search for and review the research in
the field effectively is often a time-consuming, if not tedious and
frustrating, activity - largely because no one central and comprehensive
source is available. There exist a number of reports, registers,
bibliographies and other sources which provide useful information on what is
happening but not all research gets reported anyway. While it is impossible to
be sure that every piece of relevant research has been uncovered, a very large
proportion can be identified through the sources listed here.
Personal contact
An important channel of communication is with other researchers,
supervisors (if you are doing research for a higher degree) and others in the
research field who may be known to you. Get in touch with them and ask for
their help/advice - at worst they will say ''sorry, can't help''. You may find
some researchers reluctant to give out too much information, especially if the
research is in its early stages. Obviously, such privacy/secrecy has to be
respected, although it can hold back general development of the field of
study.
Journals,
reports, bibliographies
These represent a good source of information on completed or partially
completed research. Unfortunately, not all research gets written up at the
results stage, although some eminent researchers hold the view that there is
at least a moral obligation to let the scientific/academic community know what
has been achieved. Information contained in these sources is usually quite
up-to-date but it must be remembered that many articles may have been waiting
for up to two years before getting published in the journals. Most bodies that
fund research expect a written report on completion of the work. Lists of
reports available are usually obtainable from the funding body. It is a good
idea to spend time in the library.
Ask what services they have - such as indexes, abstracts, bibliographies
and the like, and go through these. Of considerable use are sources such as
our Electronic Library Service, Contents Pages in Management, etc. Look
through recent and past issues of journals, and at the bookshelves - and take
a note of what you find. Further personal contacts can be developed with
authors of highly relevant articles and/or reports. They may even be able to
send you copies of working papers - usually very up-to-date.
Research reports
and registers
Very good sources of information are the reports/registers published (often
on an annual basis) by research councils, government departments/agencies,
foundations and other grant-awarding bodies. These sources usually list and
describe projects recently completed, under way or about to be started, and
provide names/addresses of research workers and their institutions.
Science Citation
Index
Most scientific and scholarly writings include references to earlier papers
on the same subject. The references listed in this way are cited references,
or citations; and the paper which cites them is a citing paper. Through these
references an author identifies subject relationships between his or her
current article and the cited documents. In addition newer articles that cite
the same older documents usually have subject relationships with each other.
The Science Citation Index comprises three parts which are: the Citation
Index, the Source Index, and the Permuterm Subject Index
Keyword searching
Due to the sophistication of traditional libraries and other information
bases, the availability of courseware resources and the opportunity to access
international data sources through the internet, it is essential to be able to
capture the critical mass of related knowledge in training and development
cleanly and efficiently. Keyword searching has proved to be an important
device in achieving this.
The importance of a particular 'keyword' varies over time due to the
rapidly changing business environment and the resource state within
organizations. The keyword groups shown below indicate what are considered to
be the main search trajectories for training and development at this time. The
development and maintenance of these lists is an important part of operating
an effective research process.
Research Methods
Action research
Field research
Libraries
Literature
Market research
Methodology
Multidisciplinary research
Operational research
Project management
Time management |
Learning
Action learning
Career development
Group work
Learning organization
Learning sets
Learning styles
Mentoring
Success
Self-managed learning
Workplace learning |
Management of
Change
Attitudes
Behavioral change
BPR
Change agents
Change management
Communications
Corporate Culture
Employee involvement
Empowerment
Human resource management
Information technology
Leadership
Learning organizations
Management Styles
Organizational change
Organizational development
Organizational structure
Resistance
Strategy
Technological change
Training |
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