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INTRODUCTION TO RESEARCH IN WRITING
Basturi Hasan
Fakultas keguruan dan Ilmu Pendidikan Universitas Lampung
Abstract: Research is a systematic approach to finding answers to
questions . It is a continuing endeavor that takes many forms in
many different domains. At one level writing research does not differ
from research in other fields. It is true that writing instruction has
been long established, research to understand or explain the writing
process began on a large scale during the past decade. The early
focus of writing research was more meaning based and holistic in
scope. Only recently have writing researchers begun to examine the
sub-processes in writing. In this article, we will discuss and illustrate
the techniques, content, and forms of research in writing, Also wewill see how some general research principles apply to studies in
writing.
Key words: evaluative manipulations, meta analyses, miscue analysis
INTRODUCTION
The surest avenue to improvement of educational practice will occur
through the application of knowledge derived from careful research. That is to
say, research helps us understand the key elements of successful learning and
teaching, so educational applications can accomplish the widest possible effects
(Kamil, et al, 1985).
By the same token, this paper will try to help reader understand writing
research. Research in writing examines a wide variety of problems with a broad
range of techniques from many different perspectives. Hopefully, knowledge in
this area will help practitioners come to terms with many of the techniques and
perspectives of writing research, so they can recognize and evaluate the relevance
and validity of findings and apply them accordingly in their educational situation.
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It is said that many educators find it difficult to conduct the large-scale
research necessary for implementation and instructional change program, but
there is usually a large body of research literature on most educational methods
and practices, and it is useful to consult this literature so trial-and-error can be
minimized or eliminated from decision making. There are no guarantees, though,
that the answers drawn from available research will match the problems in any
specific situation or that the application of available answers will produce perfect
results. This is because research is a continuing endeavor, answers are obtained in
slow, methodical, and often unpredictable ways. Hence, this article will try to
open insight of educators so that they can locate, read and understand the
possibilities and limitations of writing research particularly.
To benefit from this article, it will be useful to have had an introduction to
statistics. Should anyone needs or desires to learn more about any of the statistical
topics, a list of more detailed and advanced sources is provided in sources of
educational research books written by representative experts. In the next parts,
how some general research principles in terms of techniques, content and forms of
research in writing will be illustrated.
WHAT IS WRITING RESEARCH?
The early focus of writing research was more meaning based and holistic
in scope. Only recently have writing researchers begun to examine the sub-
processes in writing skills (Hays and Flower, 1980; Shaunessy, 1977; Britton,
1970). At one level writing research does not differ very much from research in
other fields. At another level, however, it can be seen that the research questions
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posed, as well as methodologies used to answer these questions, reflect the special
characteristics of the domain themselves (Kamil at al, 1985).
Contemporary research in writing is rich mixture of influences from
cognitive and physiological psychology, linguistics, anthropology, computer
science, social psychology, learning theory, and educational practice. These
influence range from the most abstract theoretical points of view to the most
practical and applied knowledge. Some writing researches are aimed at
understanding the basic nature of writing process. Such efforts include the
generation of models and theories of process (Breiter and Scardamalia, 1982).
Another goal of writing research is to improve educational practices in
classroom and other instructional settings. These efforts include studies that
unobtrusively observe behaviors in natural instructional settings and those that
conduct highly controlled manipulations of variables affecting writing instruction.
Major efforts have been mounted at the institutes, laboratories, etc, to accomplish
this task in a systematic manner (Kamil et al, 1985).
RELATING GOALS TO RESEARCH QUESTIONS
When we read research, a primary task is to determine what the research
questions will be (Hatch and Farhady, 1982; Kamil et al, 1985). Whatever we will
need to answer every question depends on the purpose for which we prepare the
proposal. Research proposal will answer the questions that any critic might ask
when we first say that we have a question or questions that we want to address
(Hatch and Lazaraton, 1991). These questions can be at the level of attempting to
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determine basic facts about cognitive processes, or they can be about instructional
decisions.
Before researchers can begin to deal with a problem, they must limit their
effort by stating specific questions they will attempt to answer (Kamil et al, 1985;
Hatch and Lazaraton, 1991). These questions serve to guide the research and keep
it focused on the topic at hand. A good research question is precise, unambiguous,
and limited in scope. Without such limits, the research might never be resolved.
In other words, if the question is not precise and unambiguous, researchers might
study one problem while thinking they are studying something else. Thus,
removing ambiguity assures that different researchers will be able to agree that
they are working on the same problem.
Research questions may be quite broad in scope such as What are the
student-teacher interactions during instruction? or they may be more narrow
like What is the effect of sentence combining practice on students writing ability
in terms of language use? .As a study progress, these questions are often refined.
Many reports describe several studies or experiments that grew out of a single,
original question (Christopherson, 1978).
When one reads a research report, the first task should be to determine the
research question. One completing problem arises in experimental studies that
have null hypotheses, which are different from research questions. A null
hypothesis is a device used for statistical reasons; it states, as a hypothesis, that
there will be no observed differences in the experiment. In comparison, a research
question generally poses the problem without taking a stance about the outcome
of the study (Kamil et al, 1985).
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RESEARCH IS INFLUENCED BY THEORIES AND MODELS
Basically, three theoretical orientations characterize or dominate most of
language skills research. The first of these is bottom-up or skillsposition. That is,
writing process begins with the organization of words, the construction of
sentences, and the parsing of sentences. This is because writing is assumed to be
initiated from within and between sentence information. In writing, such models
are implicit in widely used instructional materials. Research conducted from this
orientation emphasizes skills, sub-skills, decoding, spelling, mechanics, and the
like (Warriner and Griffith, 1977).
A second position is referred to as top-down or holistic. According to this
position, writing is assumed to be meaning generated from and focused on what
the writer is saying, has said, and is going to say. Research conducted from this
holistic position emphasizes the global nature of language and the centrality of
meaning (Britton, 1970; Kamil et al, 1985).
A final approach is called interactive or balanced. When research is
conducted from this orientation emphasis is divided appropriately between skills
and holistic variables. Hayes and Flower (1980) have a related view of writing as
a recursive activity involving planning, translating, and reviewing with an editing
sub-process that can interrupt any other sub-process.
These are certainly not the only theoretical positions, since much research
tends to be highly eclectic. Nonetheless, it can be noted that these positions may
not be found in pure forms in research studies. More likely, they will represent
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general dispositions, rather than ironclad foundations for theories, as different
theorist focus on different aspects of writing process. Hence, one should be wary
of labels. When used with caution, however, these descriptions provide the proper
framework to interpret research by indicating where the theoretical emphasis has
been placed (Kamil et al, 1985).
RESEARCH IS SHAPED BY THE TYPES OF EXPERIMENTAL
DESIGNS USED
The design used in our research will be determined by our research
question. Some designs are fairly simple and others are extremely complicated.
However, for most studies in Applied Linguistics, particularly those related to
classroom research, the design must be complex. If we then wish to be able to
generalize from the results of our classroom experiment to other classrooms, from
our students to other students, we will need to choose a design that allows us to
share our findings as being relevant to other teachers and other classrooms (Hatch
and Farhady, 1985).
In classroom experimentation, for instance, we must be sensitive to the
internal and external validity. The internal validity is the extent to which the
outcome is a function of the factor we have selected rather than other factors we
have not controlled. In the example of writing improvement, this would be the
extent to which your special new method of instruction can count for the progress
the student made rather than factors other than your instruction method.
The external validity refers to the extent that the outcome of any research
study would apply to other similar situation in the real world. Suppose we are
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investigating the effectiveness of a particular method of teaching /r/ vs. /l/ sounds.
If we conduct the study in a language laboratory with highly sophisticated
equipment and tightly controlled procedures, we will not be able to interpret the
results our study in terms of teaching those items in an ordinary classroom (Hatch
and Farhady, 1985).
Therefore, we must be sure that whenever we make a claim about the
effectiveness of any instruction, that the students not only would not have the
same gain without the instruction but also that they are really random
representative of language learners. A careful choice of design will help us avoid
these problems.
One way of avoiding problems is to use a control group in our experiment.
Not all research should be designed to yield explanatory information. Some effort
must be expended to collect descriptive data. Often, descriptive or observational
data are needed to identify or clarify instructional questions (Kamil et al, 1985).
To be clearer, suppose we want to investigate the effect of grammar correction on
the writing skills ofEFL students. Our independent variable will be the amount of
correction and the way correction is given on composition errors. The dependent
variable is the degree of grammatical accuracy in our students writing samples. If,
at the end of semester or other time period we select, we might be willing to
conclude that the improvement was related to correction (Hatch and Farhady,
1982).
. Thus, our conclusion may be wrong. To deal with this problem, we need
to have a control group for comparison purposes. A control group refers to a
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group of students whose selection and experiences are exactly the same as the
experimental group except that they do not receive the experimental treatment.
If we selected two similar groups of EFL students and corrected the errors
of one group but did not correct those of control group, we still found
improvement in our experimental group that far outweighed the improvement in
the control group, then our conclusion would be much more defensible. If it is
really only a matter of time, there should be no difference between the two
groups. Ultimately, having a control group contributes to the external validity of
the research lets us interpret our findings with more confidence. But until it is
certain that there are measurable and stable differences in those variables
mentioned previously, research manipulating them is futile.
Causal explanations, the ability to specify what variables produce specific
outcomes under all conditions are the seldom-attained goal of much educational
research. There are, however, many correlational or factor-analytic studies found
language skills research, even though no causal inferences can be drawn. Cause-
and-effect relationships require experimental designs that allow attribution of
effects to the manipulated variables. Correlational studies can be very useful when
variables cannot be manipulated for dealing with tests or when there are large
numbers of measurements involved.
In this type of study, the purpose of writing research is to determine
relationship between variables, such as, amount of instruction, type of practice in
writing, and outcomes or events, such as richness of written work, etc. In some
situations, we want to know what causes something we have observed. One
efficient method of doing this is to systematically manipulate parts of the
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situation, under vary carefully controlled conditions, and see what the effects are.
Such manipulations involve selecting different values for the variables, such as
writing journal versus structured composition practice. The effects on situation
can then be attributed to the changes in the variables. Correlations are expressed
as numbers between 1.0 and + 1.0. A correlation of + 1.0 means that one
variable can be predicted without from values of the other. The plus ( +) sign
means that the variables are positively related as one goes up (or down), so does
the other.
On the other hand, a minus () sign means that the variables are
negatively or reciprocally related, i.e., when one goes up, the other goes down.
For example, the correlation between recognition of sentence structure errors and
composition skill scores is negative: The greater the frequency of errors, the lower
the composition score (Kamil et al, 1985)
THE ENVIRONMENT OF RESEARCH
Different research methods are used in different settings. Research may be
conducted in the field (a classroom) or in the laboratory (a clinic). Experimental is
easiest to conduct in a laboratory, where there is precise control over conditions.
However, controlling all conditions may lead to results that are not directly usable
in other settings. On the other hand, descriptive data are difficult but not
impossible to collect in a laboratory ( Carnine and Carnine, 1978). Consequently,
there are many research techniques that have been developed for use in
educational settings, including descriptive and ethnographic methods, i.e., one of
the major naturalistic inquiry alternative to experimental methodologies that
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considers how experience of an individual, group, or society is influenced by and,
in turn, influences its surroundings context. It is field based rather than laboratory
based; that is, it requires that behavior be examined in natural settings.
The term ethnography refers to the anthropological process of studying a
whole culture. So it is a description of what culture is, what being a member of
that culture means, and how that culture differs from other cultures. An
ethnographic is a the product of systematic observations, interviews, and case
histories. This is because emphasis is on obtaining detailed descriptions of
processes and interaction that occur as people engage in everyday activities within
and across variety of settings, i.e., on describing natural interrelationships among
people, among events, and between people and events. A major aspect of
naturalistic inquiry suggests that behavior should be studied in its regularly
occurring time, place, and situation (Kamil et al, 1985). This permits the natural
balance of intervening variables to be maintained (Bronfenbrenner, 1976).
In short, educational ethnography seeks to understand the culture of
educational learning process: (1) what occurring, (2) how it is occurring, (3) how
participants perceive the event, (4) what is required to participate as a member of
that educational group (writing group, class, etc), and what social and academic
learning takes place (Kamil et al, 1985).
RESEARCH METHODOLOGIES: AN OVERVIEW
The introduction tells us whatthe study is about. While the method section
tells us how the study will be carried out. Typically, it begins with a section
describing the data source, i.e., the unit of observation, e.g., the students and their
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characteristics, or the classes and their characteristics, or the composition
classifications and characteristics, or the classes and characteristics of objects
from which the data are drawn (Hatch and Lazaraton, 1991).
In experimental research, one manipulates variables and observes changes
in performance. However, many problems in writing cannot be studied this way.
For example, it would be unethical to induce writing disability to study the
effectiveness of various methods of remediation. Instead, case history methods,
ethnographic, as well as descriptive techniques, can effectively be used to study
these sorts of problems. This is so since in a case history study, an attempt is made
to observe an individual or a group for an extended period of time and, if
necessary to depend on other record for supporting or supplementary data. This
value allows one to study in depth the specific implementations of programs or
methods based on other research data.
So, if, for instance, we find that a method does not work when we use it in
a real situation, we have probably missed an important variable in the other
studies. It is then a check on the transferability or generalizability of our research
results. The potential flaw in this design is that the history is not under the
investigators control. Full and accurate records may not be available; the
necessary information may never have been recorded. Despite this potential
problem, case histories are often useful in studying a problem or proposed
solutions to the problems. That is, case histories often provide an accurate view of
how an individual, or a group of individuals reacts in a realistic situation, without
intervention by researchers.
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Descriptive research and ethnographic research both describe, but they
stem from different philosophies. In descriptive studies, the investigator decides
the questions to be answered and the categories in which to distribute observations
prior to data collection. The characteristics of interest are defined a priori. In
contrast, pre-data collection decisions are studiously avoided in ethnographic
studies, as it assumed that such preconceptions will lead the investigator to ignore
important features of the phenomena being observed. Also, descriptive research
will always have a quantitative outcome, even if the results are only reported as
frequencies or percentages. On the other hand, ethnographic investigations may
report quantitative outcomes, but this is not necessary. Often, ethnographies reject
the apparent objectivity of quantitative results in favor of a more subjective
qualitative analysis by the observer (Kamil et al, 1985).
No important manipulation of conditions is appropriate in descriptive
research, while experiments manipulate or change the situation in order to reveal
causal connections. The act of data collection itself is not considered to be a
manipulation, unless it appears that this has influenced the results in some way
(Hatch and Lazaration, 1991). For example, if an experimenter wanted to find out
the incidence of some behavior during writing, it would be necessary to have
subjects do some writing practices. Having subjects do such writing would only
be considered to be a manipulation if in the data collection conditions were so
different from typical writing conditions that the outcomes were influenced.
Descriptive and experimental research are similar in both theory based rather than
data based. In other words, the data collection, instruments and categories of
analysis in descriptive and experiment research are based upon previous research
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and theory, rather than being an outgrowth of the data collected for that particular
study (Kamil et al, 1985).
Another common method is correlational study (Sullivan, 1972; Popham,
1972).This technique is common when the variables of interest are not directly
manipulable . For instance, the use of good and poor writers as an independent
variable produces many correlational studies; the observed differences in
performances are correlated with differences in writing ability
Underscore the notion that correlational studies do not strictly allow causal
conclusion. However, strong correlation suggest causal relationships, even though
correlation does not imply causation. As with case histories, such suggestions
have to be verified by other techniques. When regression analyses are used,
prediction is possible, but explanation still does not result. This is true for
multivariate analyses: What changes is the number of variables that can be
accounted for in prediction and the precision of the prediction.
The term multivariate analysis refers to a collection of statistical
techniques used to examine the relationship between three or more variables.
These techniques are being used in place of more traditional ANOVA techniques
because multivariate analysis offers the researcher a greater amount of flexibility
in the design of studies and requires fewer arbitrary decisions, that is., in the case
of, for example: How do I differentiate good and poor writer?, and the like. In
addition, multivariate analysis has become easier to do because of the availability
of computer programs capable of carrying out complex multivariate calculations
inexpensively and efficiently. Thus, this type of analysis is relatively easy to
perform and can be used to analyze many types of data to answer a variety of
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research questions. In other words, multivariate analysis allows the researcher to
examine a wide spectrum of categorical, such as, sex, race, group, and so forth,
and continuous variables, e.g., IQ, writing scores, etc. In addition, the statistical
techniques can be employed to analyze data from descriptive or experimental
studies in equally appropriate ways (Kamil et al, 1985).
Factor-analytic studies are another way of dealing with descriptive data. It
is said that factor analysis enjoyed greater popularity in the past than it does today
(Davis, 1971). In the previous section of this article, it is suggested that we need
to narrow the scope of our research so that it would be feasible. Often this means
looking at the relation between two variables. When we do this, we inevitably
think of a third variable that may play a role or may influence the relation between
the original two variables. That is, our expertise in the field of language learning
tells us in the real world the picture is much more complex, hence, we must add
more pieces to thepuzzle if we want to capture the essence of language learning.
As we add more variables, the research becomes increasingly complex even so
complex that we need to reduce large numbers of variables in some meaningful
way. The picture of the real world may also suggest that those variables
discovered to be important in language learning should be arranged in a particular
way. And so, models are proposed for some reasons, these untested models are
called theories for the learning process Obviously, the statistical procedures are
important because they give us a way of discovering factors that underlie
language proficiency, and hopefully language learning, and ways of testing
relationships among them (Hatch and Larazation, 1991; Kamil et al, 1985).
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Apparently, many problems can still be studied by using factor analysis.
For instance, attitudes are particularly amenable to study by this method according
to Kamil et all, while factor analysis does not allow causal inferences, it is, at this
rate, valuable for work in difficult problem areas. For example, these techniques
can show which of many variables acting on situation are most important and
which may be largely irrelevant (Hatch and Farhady, 1981; Kamil et all, 1985).
Historically, the two-group study has been the most common experimental
design. It operates quite simply: One group is given a treatment, and the other
function as a control group, receiving either nothing or some irrelevant condition
for comparison. Perhaps, this basic has been extended to produce the factorial
design in use today, i.e., two or more variables or factors are manipulated at the
same time, in the same study. All values of each variables are combined with all
values of the other variables to produce treatment combinations to be
administered. In other words, the use of factorial designs allows the effect of
several variables to be studied simultaneously. In addition, we can study the
interaction among factors, those conditions that occur when variables act
differently in combination than when they are observed in isolation. The greater
number of variables manipulated at once in a given setting, the more natural the
situation will be. This kind of research design leads us to view what
Bronfenbrenner (1976) used in his study called the desirability to find the so
called ecological validity of the research design.
Psychological researchers have recognized the difficulties inherent in
using group data in analyses. Some researchers in learning have advocated
intensively studying single or small number of subjects across an extended range
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of time and behavior (Kamil et al, 1985). Perhaps the most prevalent paradigm in
language skills research using this single/small number of subjects (N)
methodology is due to miscue analysis (Goodman, 1965). Most of miscue studies
do analysis of extensive data collected in individual sessions with a few readers. A
primary argument for this methodology is that the relationships among responses
are often as important as their content (Kamil et al, 1985). In writing, conducting
extensive small small-Nresearch, tracing the writing development of learners, the
collected data can be intensively analyzed because only a few subjects are
involved (Graves, 1975).
There are unavoidably potential risks involved in doing research with
single-N/small-N samples. Among these, as Kamil et al assert, is the potential for
studying non-representative individuals. Consequently, conclusions based on non-
representative data are inappropriate for general applications. The smaller the
sample will produce the greater the risk of error. Interpretations based on the such
data then have to be viewed with care. Thus, the researcher is especially obligated
to describe the subjects as carefully and thoroughly as possible.
Furthermore, small-sample paradigms necessitate repeated measures, and
therefore, both benefits and disadvantages of collecting repeated measures are
involved. For example, repeated measures allow individuals to serve as their own
controls, reducing the variance and increasing the precision of analysis. However,
when repeated measures are used, contrast effects may arise. That is, subjects may
react differently to the various treatments only because they realize the treatments
are different. In addition, repeated measures are subject to practice and fatigue
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effects, further limiting the generalizability of repeated measures data (Hatch and
Lazaration, 1991; Kamil et al, 1985).
A variant of single-/N designs is the time series. In this type of study,
measurements are made many times, before and after administration of a
treatment. In other words, changes in performance can be observed over time and
as a function of the application of the treatment. Needless to say, that it is not
necessary to have a small or single N to use a time series design. However, the
extensive data collection required by this design makes it less practical to use
large group.
More sophisticated designs for experimental and quasi-experimental
studies in language skills are available. It is true that the ultimate goal of any
investigation is to conduct research that will allow us to show the relationship
between the variables we have selected. However, in social sciences in general,
and our field in particular, it is not realistic to limit our research to true
experimental designs only, that is, they have basically three characteristics: (1) a
control group or groups is present, (2) the subjects are randomly selected to the
groups, and (3) a pretest is administered to capture the initial differences between
the groups. The reason is that we are dealing with the most complicated of human
behaviors, language learning behavior (Hatch and Farhady, 1981).
The need for these more complex designs has derived from two sources.
On the one hand, researchers have realized the inadequacies of some conventional
methods of collecting data. For example, notions of ecological validity issued by
Bronfenbrenner (1976) have necessitated collection of much more data than was
traditionally required. Moreover, contemporary experiments require greater effort
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in data reduction than in actual data analysis as any glance at writing journal will
indicate.
TYPES OF VARIABLES IN WRITING RESEARCH
We can expect variability in anything we observe. An EFL students
language skill may vary from week to week. We may be able to count for this
variation in individual performance by considering amount of construction. Skill
does not remain the same. The ability of a group of Indonesian students learning
English to recognize and reproduce the tone system may vary, We may be able to
account for this variability by determining whether the students have learned other
tone languages, young or old, male or female, etc. By analogy, different pieces of
text may vary in frequency of hedges. This is because, academic science text
may include many more lexical hedges, e.g., it appears, it seems, to certainty
of claims than other types of text materials. Variability and explanations of that
variability are central to research ( Hatch and Lazaration, 1991).
In general, three major classes of variables can be identified. The first is
the class ofinstructionalvariables, including, among others, instructional format,
amount of time on task, and type of materials. Topic, knowledge, and purpose of
materials have become predominant in current research. This class of variable is a
mixture of traditional types, like amount of time on task, and instructional
presentation, as well as less traditional types, like teacher, beliefs or other aspects
of teacher competence (Duffy and Metheny, 1979).
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The second group is the writer/learner variables. In turn, this group is
divided into individual variables, like language and language development,
cognitive processes, and cognitive development, along with more global variables,
like self-concept or socioeconomic and cultural factors.
The final of variables may be classified as environmental, which includes
such factors as classroom design and organization. Also involved are a number of
naturalistic variables dealing with student/teacher interaction (Kamil et al, 1985).
In short, a variable can be defined as an attribute of a person or of an
object which varies from person to person or from object to object, or from time
to time.
RESEARCH CAN BE SHAPED BY THE MANIPULATIONS OF THE
VARIABLES
Research often can be characterized by the number of factors manipulated.
Much language skill research has involved manipulating only a single variable
However, researchers increasingly use designs that manipulate several variables
simultaneously. This reflects the realization that clusters of variables have to be
studied to arrive at a thorough description or explanation of the process. A
complete description is, by definition, ecologically valid (Bronfenbrenner, 1976).
Other researches perform the so called evaluative manipulations, and
meta-analysis. In the cases of evaluative manipulations, a single value of a
variable is to determine whether there is some effect on behavior. Examples might
be in the test development or in testing a single teaching method or technique.
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Finally, there are studies of studies, or meta-analyses. In meta-analyses,
studies that have manipulated the same or similar variables are examined to
determine the amount of agreement among the studies and to estimate the size of
effects that can be expected. These meta-analyses are not primary manipulations
of variables. Instead, they are attempts to analyze the results of other studies to see
what it is that can be assumed to be true about, e.g., writing and writing process
(Kamil et al, 1985).
IN SUMMARY
In this article, there have a brief overview of the goals and constraints
posed in certain kinds of research in writing been provided. This paper has tried
to explain a good deal about writing skill, much of which is; hopefully, useful for
educational decision making. Apparently, to interpret research report, one must
understand research methodology, its advantages and limitations. The
methodology used to conduct a language skill study, e.g., writing research, has a
logic of its own, an internal logic so strong that it affects the design of experiment,
the procedures used, the data gathered, the analysis undertaken, and the way in
which the research is reported. Finally, an understanding of research methodology
will help readers know what information to look for and how to avoid
misinterpretations.
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