- 1. Experimental Research ByShafqat Rasool
2. Experimental research answers the question What if?The
researchermanipulates independent variables (e.g., type of
treatment, teaching method,communication strategy) andmeasures
dependent variables (anxiety level, English comprehension, s
atisfaction) in order to establish cause-and-effect relationships
between them.Theindependent variable is controlled or set by the
researcher. Thedependent variable is measured by the researcher.An
experiment is a prescribedset of conditions which permit
measurement of the effects of a particular Treatment. 3. Threats to
experimental researchInternal validityInternal invalidity asks the
question, Are the measurements I make on my dependent (i.e., the
variable I measure) variable influenced only by the treatment, or
are there other influences which change it?External validity To how
much the results are generalized to target population. 4. Internal
validity History,Maturation,Testing, Instrumentation, Statistical
regression, Differential selection, Experimental mortality, And
selection-maturation interaction.The John Henry effect and
experimental treatment diffusion. 5. History History refers to
events other than the treatment that occur during the course of an
experiment which may influence the post-treatment measure of
treatment effect. If the explosion of the nuclear reactor in
Chernobyl, Ukraine had occurred in the middle of a six-month
treatment to help people reduce their anxiety of nuclear power,Must
occur during the experiment. Controlled be control group 6.
Maturation Subjects change over the course of an experiment. These
changes can be physical, mental, emotional, or spiritual.
Perspective can change. The natural process of human growth can
result in changes in post-test scores quite apart from the
treatment.Question: How would a control group control this source
of internal invalidity 7. Testing A common research design is to
give a group a pre-test, a treatment, and then a post-test . If the
same testis used both times, the group may show an improvement
simply because of their experience with the test. This is
especially true when the treatment period is short and the tests
are given within a short time. 8. Instrumentation If you use
different tests for pre- and post-measurements, then the change in
pre- and post-scores may be due to differences between the tests
rather than the treatment.The best remedy is to use randomization
and a post-test only design. 9. Statistical regression Statistical
regression refers to the tendency of extreme scores, whether low or
high, to move toward the average on a second testing. Subjects who
score very high or very low on one test will probably score less
high or low when they take the test again. That is, they regress
toward the mean. Do not study groups formed from extreme scores.
Study the full range of scores. 10. Differential selection If we
select groups for treatment and control differently, then the
results may be due to the differences between groups before
treatment.Randomization solves this problem by statistically
equating groups. 11. E xperimental mortality Experimental
mortality, also called attrition, refers to the loss of subjects
from the experiment. If there is a systematic bias in the subjects
who drop out, then posttest scores will be are biased. For example,
if subjects drop out because they are aware that theyre not
improving as they should, then the post-test scores of all those
who complete the treatment will be positively biased. Your results
will appear more favorable than they really are. How does use of a
control group solve the problem of attrition? 12.
Selection-Maturation Interaction of Subjects Interaction means the
mixing or combining of separate elements. If you draw a group of
subjects from one school to serve as the treatment group, and a
second group from a different schools to serve as a control, you
could well find -- beyond the simple problem of selection
differences (Are the two groups equivalent?) --a mixing of
selection and maturation factors to compound the extraneous
influence on your measurements.For example, if the two schools
differ in the average age of their members, they may well respond
to the treatment differently due to inherent maturational
factors.Randomly selecting all subjects from a defined population
solves this problem. 13. The John Henry Effect John Henry, the
legendary steel drivin man, set himself to prove he could drive
railroad spikes faster and better than the newly invented
steam-powered machine driver. He exerted himself so much in trying
to outdo the "experimental" condition that he died of a ruptured
heart.If subjects in a control group find out they are in
competition with those in an experimental treatment, they tend to
work harder. When this occurs, differences between control and
treatment groups is decreased, minimizing the perceived treatment
effect. 14. Treatment diffusion Similar to the John Henry effect is
treatment diffusion. If subjects in the control group perceive the
treatment as very desirable, they may try to find out whats being
done. Both the John Henry Effect and Treatment Diffusion can be
controlled if experimental and control groups are isolated. 15.
- Threats to external validity
- Reactive effects of testing
- Treatment and Subject Interaction
- Testing and Subject Interaction
- Multiple Treatment Effect
16. Reactive effects of testing Subjects in your samples may
respond differently to experimental treatments merely because they
are being tested. Since the population at large is not tested,
experimental effects may be due to the testing procedures rather
than the treatment itself. This reduces generalizability. One type
of reactive effect is pretest sensitization.Another type of
reactive effect is post-test sensitization. The posttest can be, in
itself, a learning experience that helps subjects to put all the
pieces together. Different results would be obtained if the
treatment were given without a posttest. While researchers must
make measurements, care must be taken to measure treatment effect,
not add to it, with a post-test. 17. Treatment and Subject
Interaction Subjects in a sample may react to the experimental
treatment in ways that are hard to predict. This limits the ability
of the researcher to generalize findings outside the experiment
itself. If there is a systematic bias in a sample, then treatment
effects may be different when applied to a different sample. 18.
Testing and Subject Interaction Subjects in a sample may react to
the process of testing in ways that are hard to predict. This
limits the ability of the researcher to generalize findings outside
the experiment itself. If there is a systematic bias of test
anxiety or test-wiseness in a sample, then treatment effects will
be different when applied to a different sample 19. Multiple
Treatment Effect Normally we find a single treatment in an
experiment. If, however, an experiment exposes subjects to, say,
three treatments (A, B, and C) and test scores show that treatment
C produced the best results, one cannot declare treatment C the
best. It may have been the combination of the treatments that led
to the results.Treatment C, given alone, may produce different
results. 20.
- Different types of experimental research can be conducted
depending on the nature of subjects and the instruments, and the
way data are collected and analyzed.
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- - Will there be a control group?
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- - How many subjects will there be?
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- - Will the subjects be randomly selected?
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- - Will each group be pretested?
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- - How will the obtained data be analyzed?
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- What factors may affect the internal validity?
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- What factors may affect the external validity
21. True-Experimental Design Quasi-Experimental design
Pre-Experimental Design
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- Pretest/posttest control group design
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- Posttest only control group design
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- Solomon four group design
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- Non-equivalent control group
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- One-group, pretest/posttest
Single variable designs Factorialdesigns Types of Experimental
Research 22. True Experimental group Design Advantages of the
true-experimental design include: Greater internal validity Causal
claims can be investigated Disadvantages: Less external validity
(not like real world conditions) Not very practical True
Experimental Designs Experimental designs are consideredtrue
experiments when they employ randomizationin the selection of their
samples and control for extraneous influences of variation on the
dependent variable. The three designs we will consider in this
section are thebest choices for an experimental dissertation. These
are the pretest-posttest control group design, the Posttest Only
Control Group design, and the Solomon Four Group design. 23.
Quasi-experimental Design Without proper randomization Lack of
rigorous statistical scrutiny Some advantages of the
quasi-experimental design include: Greater external validity (more
like real world conditions) Much more feasible given time and
logistical constraints Disadvantage: Not as many variables
controlled (less causal claims) 24. Pre-experimental Design Lacking
in several areas of the true-experimental criteria. No random
selection in most of the cases. Employment of just single group
that receives treatment, no control group. The advantages are: Very
practical Set the stage for further research Disadvantages: Lower
validity 25. True Experimental Design The posttest only control
group design. The pretest posttest control group design. The
Solomon four group control design. 26. Quasi-experimental
DesignNonequivalent Control Group DesignTime Series Multiple Time
Series 27. Pre-experimental Design The one-shot case studyOne group
Pretest Posttest studyThe static group comparison study 28. If
there is only one independent variable that can be manipulated,
then asingle-variable design is used. If there are two or more
independent variables, and at least one can be manipulated, then a
factorial design should be chosen. 29. Single-variable
designs.These studies are classified under three main headings
depending on the degree of control maintained on other variables:1.
Pre-experimental designs (low degree of control)2. True
experimental designs (high degree of control)3. Quasi-experimental
designs (medium degree of control) 30.
- Classified depending on whether there is an involvement of one
or two groups, and whether the groups are posttested only, or both
are pretested and posttested:
- One-group pretest-posttest design:
- Static-group comparison design:
31. One-shot case studies:One group is exposed to the treatment,
and only a posttest is given to observe or measure the effect of
the treatment on the dependent variable within the experimental
group. Since it is applied on a single group, there is no control
group involved in this design.First of all, the chosen group is
exposed to the treatment ,and then it is tested only once for the
purpose of measuring the degree of change on the dependent variable
after the treatment. 32. One-group pretest-posttest design:One
group is pretested and exposed to the treatment, and then
posttested. This is called a one-group pretest-posttest design
because the two tests are administered to the same group.The first
one is administered at the beginning of the treatment and the
second one at the end. 33. Static-group comparison design At least
two groups are involved. After one group receives the treatment,
all groups are posttested.This design has better control over most
of the variables 34.
- Advantages of pretest design
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- Can measure extent of change
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- Assess reasons for and effects of mortality
- Disadvantages of pretest design
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- Sensitization to pre-test
35. True experimental designsHave the highest level of control
among the three single-variable experimental designs because the
subjects within the groups arerandomly assigned for each group .
When subjects are randomly assigned, there is higher control of the
internal validity as well as the external validity. Moreover, there
is always acontrol groupto compare the results of the subjects in
the experiment with other subjects of similar status that have not
been exposed to the treatment. 36. True experimental research may
be designed with or without a pretest on at least two groups of
randomly assigned subjects. The classification of true experimental
designs is made accordingly :1. The posttest-only control group
design2 .The pretest-posttest control group design3. Solomon
four-group design 37. Posttest Only Control Group Subjects are
randomly selected and assigned to two groups. Due to randomization,
the two groups are statistically equal. No pretest is given. One
group receives the Treatment RXO 1 RO2 Example. Third graders are
randomly assigned to two groups. Then one group receives a special
study on the life ofIqball. Both are tested on their knowledge of
Iqball at the conclusion of the study. Analysis. The difference
between group means (O1 and O2) can be computed byan independent
groups t-test. 38. 39. Pretest-Posttest Control Group Two randomly
selected groups are measured before (O1 and O3) and after (O2 and
O4) one of the groups receives a treatment (X). RO 1XO 2RO3O4
Example. Third graders are randomly assigned to two groups and
tested for knowledge of Arithmetic. Then one group gets a
specialstudy on Arithmetic. Both are then tested again. 40. 41.
Analysis. The t-test for independent samples (Chapter 20) can be
used to determineif there is a significant difference between the
average scores of the groups (O2 and O4). You can also compute gain
scores (O2 - O1 and O4 - O3) and test the significance of the
average gain scores with the matched samples t-test. This designs
only weakness is pre-test sensitization and the possibleinteraction
between pretest and treatment. 42. Solomon four-group designTakes
the effect of pretest and posttest sensitivization into
consideration.It is the combination of pretest-posttest control
group (G1 and G2) and posttest only control group (G3 and G4)
designs. In this case,subjects are randomly selected and placed
into four groups; 43. 44. Example. Third graders are randomly
assigned to 1 of 4 groups. The knowledgeoflanguage is measured in
groups 1 and 2. Groups 1 and 3 are given a special study on the
language learning. When the special study is over, all four groups
are tested. Analysis. One-way ANOVA can be used to test the
differences in the four posttestmean scores (O2, O4, O5, O6). The
effects of the pretest can be analyzed by applying a t-test to the
means of O4 (pretest but no treatment) and O6 (neither pretest or
treatment). The effects of the treatment can be analyzed by
applying a t-test to the means of O5 (treatment but no pretest) and
O6 (neither pretest or treatment). Subject maturation can be
analyzed by comparing the combined means of O1 and O3 against O6.
45. - the first and the second groups are retested;- the first and
the third groups are exposed to the treatment, and the second and
the fourth groups are taken as control groups;- all four groups are
posttested.This design provides the best result but it requires a
large sample so that enough subjects could be assigned to four
groups.When the sample is large, administering the tests becomes
difficult, time and energy consuming. 46. Quasi-experimental
Designs The termquasi- (pronounced kwahz-eye) meansalmost, near,
partial, pseudo, orsomewhat . Quasi-experimental designs are used
when true experiments cannot be done. A common problem in
educational research is the unwillingness of educational
administrators to allow the random selection of students out of
classes for experimental samples. Without randomization, there are
no true experiments. So, several designs have been developed for
these situations that are almost true experiments, or
quasi-experimental designs.Well look at three:the time series,the
nonequivalent control group design,and the counterbalanced design.
47. Time Series Establish a baseline measure of subjects by
administering a series of tests over time (O1 through O4 in this
case). Expose the group to the treatment and then measure the
subjects with another series of tests (e.g., O5 through O8).
O1O2O3O4XO5O6O7O8 Comments. Since there is no control group, one
cannot determine the effects of history on the test
scores.Instrumentation may also be a problem (Are the tests
equivalent?)the reactive effects of repeated testing of subjects is
a source of external invalidity. 48. Nonequivalent Control Group
Design Subjects are tested in existing or intact groups rather than
being randomly selected. The dotted line in the diagram represents
non-equivalent groups. Both groups are measured before and after
treatment. Only one group receives the treatment. O 1XO
2--------------------- O3O4 Comments. This design should be used
only when random assignment is impossible. It does not control
forselection-maturation interactionstatistical regression.pretest
sensitization. 49. Counterbalanced Design Subjects are not randomly
selected, but are used in intact groups. Group 1 receives treatment
1 and test 1. Then at a later time, they receive treatment 2 and
test 2. Group 2 receives treatment 2 first and then treatment one.
Time 1 2 Group1X1OX2O Group2X2OX1O Example. Two third grade classes
receive two special studies on language: one inclassroom and the
other on a computer. Class 1 does the classroom work first,
followed by the computer; class 2 does the computer work first.
Both groups are tested after both treatments. 50. Analysis. Use the
Latin Squares analysis (beyond the scope of this text). Comments.
Since randomization is not used in this design,
selection-maturation interaction may be a problem. Multiple
treatment effect is a possible source of external invalidity. 51.
52. Thank You