INTRODUCTION
Unlike a descriptive study, an experiment
is a study in which a treatment, procedure, or program is intentionally
introduced and a result or outcome is observed. The American Heritage
Dictionary of the English Language defines an experiment as “A test under
controlled conditions that is made to demonstrate a known truth, to examine the
validity of a hypothesis, or to determine the efficacy of something previously
untried.”
True experiments have four elements: manipulation, control, random, assignments,
and random selection. The most important of these elements are
manipulation and control. Manipulation means that something is purposefully
changed by the researcher in the environment. Control is used to prevent
outside factors from influencing the study outcome. When something is
manipulated and controlled and then the outcome happens, it makes us more
confident that the manipulation “caused” the outcome. In addition, experiments
involve highly controlled and systematic procedures in an effort to minimize
error and bias which also increases our confidence that the manipulation
“caused” the outcome.
DISCUSSION
A.
Definition
of True Experiment
A true experimental design is one
in which the researcher manipulates the Independent Variable (or variables) to
observe its effect on some behavior or cognitive process (the dependent
variable) while using random assignment of participants to groups in order to
control external factors from influencing the results. Without both manipulation
of the IV and random assignment of participants, you do not have a true
experimental design and, as a result, cannot establish cause and effect.
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True experimental design makes up
for the shortcomings of the two designs previously discussed. They
employ both a control group and a means to measure the change that occurs in
both groups. In this sense, we attempt to control for all
confounding variables, or at least consider their impact, while attempting to
determine if the treatment is what truly caused the change. The
true experiment is often thought of as the only research method that can
adequately measure the cause and effect relationship.
True
experiments are considered the most accurate form of experimental research.
They are commonly used in the physical sciences, such as chemistry, geology
and physics, to prove or disprove a hypothesis, or theory, but are more
difficult to apply to social sciences, such as biology or psychology. The
characteristic feature of a true experiment is that subjects are randomly
assigned. This means that any difference between them is purely due to
chance. For simplicity, just one variable is manipulated and tested.
B.
Characteristic
of True Experiment
1.
Time order of variable
2.
Manipulation of the independent variable
3.
Relationships between variable
4.
Control of rival (alternative) hypothesis
5.
Use of a control group
6.
Random sampling and random assignment
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C. Bias
and Assignments
In a true experiment, randomization
means that it is unlikely that one subject is significantly superior or
inferior to another. This means that variables associated with individuals are
not sources of constant or systematic error, although there still may an
element of bias in the overall design of the experiment.
Randomization can be achieved by
tossing a coin, rolling a die or using a computerized random number generator
to assign treatments to subjects. In quasi experiments, nonrandom assignment -
based on first-come, first-served, perceived ability or some other criterion -
can significantly influence the outcome of the experiment, particularly if
differences in immeasurable characteristics, such as intelligence, exist among
subjects.
D. Components of Experimental Research Design
1.
The
Manipulation of Predictor Variables
In an experiment, the researcher manipulates the factor that
is hypothesized to affect the outcome of interest. The factor that is being
manipulated is typically referred to as the treatment or intervention. The
researcher may manipulate whether research subjects receive a treatment (e.g.,
antidepressant medicine: yes or no) and the level of treatment (e.g., 50 mg, 75
mg, 100 mg, and 125 mg).
Suppose, for example, a group of researchers was interested
in the causes of maternal employment. They might hypothesize that the provision
of government-subsidized child care would promote such employment. They could
then design an experiment in which some subjects would be provided the option of
government-funded child care subsidies and others would not. The researchers
might also manipulate the value of the child care subsidies in order to
determine if higher subsidy values might result in different levels of maternal
employment.
2.
Random
Assignment
·
Study participants are randomly assigned
to different treatment groups
·
All participants have the same chance of
being in a given condition
·
Participants are assigned to either the
group that receives the treatment, known as the "experimental group"
or "treatment group," or to the group which does not receive the
treatment, referred to as the "control group"
·
Random assignment neutralizes factors
other than the independent and dependent variables, making it possible to
directly infer cause and effect
3.
Random
Sampling
Traditionally, experimental researchers have used convenience
sampling to select study participants. However, as research methods have become
more rigorous, and the problems with generalizing from a convenience sample to
the larger population have become more apparent, experimental researchers are
increasingly turning to random sampling. In experimental policy research
studies, participants are often randomly selected from program administrative
databases and randomly assigned to the control or treatment groups.
E. Validity of Results
The two types of validity of experiments are internal and
external. It is often difficult to achieve both in social science research
experiments.
1.
Internal
Validity
·
When an experiment is internally valid,
we are certain that the independent variable (e.g., child care subsidies)
caused the outcome of the study (e.g., maternal employment)
·
When subjects are randomly assigned to
treatment or control groups, we can assume that the independent variable caused
the observed outcomes because the two groups should not have differed from one
another at the start of the experiment
·
For example, take the child care subsidy
example above. Since research subjects were randomly assigned to the treatment
(child care subsidies available) and control (no child care subsidies
available) groups, the two groups should not have differed at the outset of the
study. If, after the intervention, mothers in the treatment group were more
likely to be working, we can assume that the availability of child care
subsidies promoted maternal employment
One potential threat to internal validity in experiments
occurs when participants either drop out of the study or refuse to participate
in the study. If particular types of individuals drop out or refuse to
participate more often than individuals with other characteristics, this is
called differential attrition. For example, suppose an experiment was conducted
to assess the effects of a new reading curriculum. If the new curriculum was so
tough that many of the slowest readers dropped out of school, the school with
the new curriculum would experience an increase in the average reading scores.
The reason they experienced an increase in reading scores, however, is because
the worst readers left the school, not because the new curriculum improved
students' reading skills.
2.
External
Validity
·
External validity is also of particular
concern in social science experiments
·
It can be very difficult to generalize
experimental results to groups that were not included in the study
·
Studies that randomly select
participants from the most diverse and representative populations are more
likely to have external validity
·
The use of random sampling techniques
makes it easier to generalize the results of studies to other groups
For example, a research study shows that a new curriculum
improved reading comprehension of third-grade children in Iowa. To assess the
study's external validity, you would ask whether this new curriculum would also
be effective with third graders in New York or with children in other
elementary grades.
Glossary
terms related to validity:
F. Ethics
It is particularly important in experimental research to
follow ethical guidelines. Protecting the health and safety of research
subjects is imperative. In order to assure subject safety, all researchers
should have their project reviewed by the Institutional Review Boards (IRBS).
The National Institutes of Healthsupplies strict guidelines for
project approval. Many of these guidelines are based on the Belmont
Report.
The
basic ethical principles:
·
Respect for persons --
requires that research subjects are not coerced into participating in a study
and requires the protection of research subjects who have diminished autonomy
·
Beneficence --
requires that experiments do not harm research subjects, and that researchers
minimize the risks for subjects while maximizing the benefits for them
·
Justice --
requires that all forms of differential treatment among research subjects be
justified
G.
Advantages of True Experiment
1.
Reliable
Results
Researchers
collect data during the experiment and subject this to statistical analysis to
determine the significance of their findings. Whether in the physical sciences
or the social sciences, true experiment results are considered reliable because
they lend themselves to such statistical study.
2.
Causality
The biggest
advantage of a true experiment is that it is the only experimental design that
allows researchers to determine the cause and effect relationship between two
factors. The factor that a researcher modifies is known as the independent
variable and the effect he seeks to observe is called the dependent variable.
For example, if a researcher studies the occurrence of cancer in people who
smoke, existence of the disease is the dependent variable and smoking is the
independent variable. Performing a true experiment helps the scientist study
the nature of the relationship between the dependent and independent variable.
3.
Control
Groups
In a true
experiment, the researcher uses two groups: an experimental group and a control
group. The purpose of the control group is to account for extraneous factors
other than the independent variable that may have an influence on the
experimental results. In such experimental designs, researchers assign subjects
randomly to either the experimental or control group. Continuing with the
cancer research example, the scientist assigns both male and female subjects of
different age groups randomly to either the experimental or control group.
Randomization removes the influence of these extraneous factors such as sex and
age on the occurrence of cancer and helps the researcher focus on the
relationship between smoking and cancer.
CONCLUSION
True experiments must have at least three things:
·
Two comparison groups (in the simplest
case, an experimental and a control group) Comparison/control group – do not
get confused.
·
Variation in the independent variable
before assessment of change in the dependent variable
·
Random assignment to the two (or more)
comparison groups.
True experiments must have at least one experimental
group (subjects who receive some treatment) and at least one comparison group
(subjects to whom the experimental group can be compared). All true experiments
have a posttest—that is, measurement of the outcome in both groups after the experimental
group has received the treatment. Many true experiments also have pretests that
measure the dependent variable prior to the experimental intervention.
REFERENCES
http://www.uic.edu/classes/socw/socw560/EXPERMT/sld008.htm
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