Experimental Design

EXPERIMENTAL RESEARCH
DESIGN
Dr. K. Thiyagu, Assistant Professor, Department of Education, Central University of
Kerala, Kasaragod
Dr. K. Thiyagu,

What is Research?
A systematic means of problem solving (Tuckman
1978)
5 key characteristics:
1. Systematic – research process
2. Logical – induction/deduction
3. Empirical – evidence based
4. Reductive – generalisation
5. Replicable – methodology

Research Design Continuum
Research Design
Analytical Research
Descriptive Research
Experimental Research
Reviews
Historical
Philosophical Case Study Survey
Cross-Sectional
Longitudinal
Correlational
Pre-designs
Quasi-designs
True-designs
Statistical-
designs
Meta-Analyses

Analytical Research
• Reviews
• A critical account of present understanding
• A meta-analysis is a quantitative method of review
• Historical Research
• Accessing both primary (e.g. witnesses) or
secondary (e.g. literature) sources to document
past events
• Philosophical Research
• Organising existing evidence into a comprehensive
theoretical model

Descriptive Research
• Case Study
• Accrual of detailed information from an
individual
• Survey
• Cross-sectional: Status of a various groups at
a given point in time
• Longitudinal: Status of a given group at
various points in time
• Correlational: Relationships between
variables

Experimental Research
• Experimental research involves a direct
assessment of how one variable influences
another
• This allows the establishment of causality
• All extraneous variables must be held
constant while a single variable is
manipulated and the effect measured

Independent Variable =
this variable is the ‘cause’ / as the predictor
variable
Dependent Variable =
this variable is the ‘effect’ / should only vary in
response to the IV / also known as the criterion
variable
Extraneous Variables =
must be controlled to isolate the effect of the IV
on the DV
Confounding Variables =
extraneous variables which have co-varied with
Variabl
es

Experimental Method
• Experimental is most scientifically
sophisticated research method.
• It is defined as ‘observation under
controlled conditions’.
• Experimental research design are
concerned with examination of the effect of
independent variable on the dependent
variable, where the independent variable is
manipulated through treatment or
intervention(s), & the effect of those

EXPERIMENTAL
RESEARCH
Dependent VariableIndependent Variable
Experimental or
Treatment
Variable
Criterion or
Outcome
Variable
Best research methodology to
establish cause-and-effect relationships among

True Experimental
Design
True experimental research designs
are those where researchers have
complete control over the
extraneous variables & can predict
confidently that the observed effect
on the dependable variable is only
due to the manipulation of the
independent variable.

ESSENTIAL
CHARACTERISTICS…
A true experimental research design must
essentially consist of the following three
characteristics:
1. Manipulation
2. Control
3. Randomization

Manipulation:
• Manipulation refers to conscious control of
the independent variable by the researcher
through treatment or intervention(s) to
observe its effect on the dependent
variable.

Control:
• Control is another essential element of true
experimental design.
• Control refers to use of control group & controlling
the effects of extraneous variables on the
dependent variable in which researcher is
interested.
• The subject in the control & experimental groups
are similar in number & characteristics, but the
subject in the control group receive no
experimental treatment or any intervention at all.

Randomization:
• Randomization means that every subject has an equal
chance of being assigned to experimental or of study
subjects on a random basis. Through random assignment of
subject under experimental or control group, chances of
systemic bias is eliminated.
• Randomization is used in true experimental research design
to minimize the threat of internal validity of the study & to
eliminate the effect of extraneous variables on dependent
variables.
• Through randomization, on average the characteristics of
the subject in experimental & control groups are similar, thus
influence of extraneous variables on dependant variable is

 Random assignment of subject may done with simple flip of
a coin for each subject; if coin lands on its ‘head’, subjects
are assigned to first group & with ‘tail’ subjects are assigned
to control group.
 Another possible method is to write the names of the
subjects on slips of paper & put the slips into a bowl & then
draw lots. The first designated numbers of subjects are
placed in one group, & rest are assigned under another
group.
 Thirdly a random table may be used to facilitate the
randomization process. In this method, blind-folded
subjects choose a number from a table of number
horizontally (row) or vertically (columns), till a requisite
number is reached for both experimental & control groups.
METHODS OF
RANDOMIZATION

TYPES OF TRUE EXPERIMENTAL
DESIGN
True Experiential
Design
Post-test
only
Factorial
Pretest
post-test
only
Crossove
r
Solomon
4 groups
Randomize
d block

Post-test-only Control Design:
• Composed of two randomly assigned group, i.e.
experimental & control, but neither of which is pretested
before the implementation of treatment on the experimental
group.
• In addition, while treatment is implement on the
experimental group only, post-test observation is carried out
on both the group to assess the effect of manipulation.
• This design can be helpful in situations where it is not
possible to pretest the subjects.

Random
assignment
Exp. group Treatment Post-test
Control group Post-test
Post-test-only Control Design:

Example
Post-test-Only Control Group Design
100 randomly
selected teachers
R
50 teachers
X
Dance for
Peace
Training-
Workshop
O
Posttest:
Faculty Self-
Awareness
Questionnaire
R
50 teachers
C
No training
O
Posttest:
Faculty Self-
Awareness
Questionnaire

Pretest-post-test-only design
• In this research designs, subjects are randomly assigned to
either the experimental pr the control group.
• The effect of the dependent variable on both the groups is
seen before the treatment (pretest).
• Later, the treatment is carried out on experimental group
only, & after-treatment observation of dependant variable is
made on both the groups to examine the effect of the
manipulation of independent variable on dependant
variable.
• For example, such a design could be used for ‘an
experimental study to assess the effectiveness of cognitive
behavioral therapy interventions for patients with breast

Random
assignment
Exp.
group
Treatmen
t
Post-
test
Control
group
Post-
test
pretest
pretest
Pretest-post-test-only design

Example
Posttest-Only Control Group Design
100
randomly
selected
teachers
R
50 teachers
O
Pretest:
Faculty Self-
Awareness
Questionnair
e
X
Dance for
Peace
Training-
Workshop
O
Posttest:
Faculty Self-
Awareness
Questionnaire
R
50 teachers
O
Pretest:
Faculty Self-
Awareness
Questionnair
e
C
No training
O
Posttest:
Faculty Self-
Awareness
Questionnaire

Solomon four-group design
• There are two experimental groups (experimental group 1 &
experimental group 2) & two control groups (control group 1
& control group 2).
• Initially, the investigator randomly assigns subjects to the
four groups.
• Out of the four groups, only experimental group 1 & control
group1 receives the pretest, followed by the treatment to the
experimental group 1 & experimental group 2.
• Finally, all the four groups receive post-test, where the
effects of the dependant variables of the study are observed
& comparison is made of the four groups to assess the
effect of independent variable (experimental treatment) on
the dependant variable.
• The solomon four-group design is believed to be most

Random
assignment
Exp. Group 1
Control Group 1
Exp. Group 2
Control Group 2
pretest treatment Post-test
pretest Post-test
treatment Post-test
Post-test
Solomon four-group design

Example
The Solomon Four- Group Design
100
randomly
selected
teachers
R
25
teachers
(Exp-1)
O
Pretest:
Faculty Self-Awareness
Questionnaire
X
Dance for
Peace
Training-
Workshop
O
Posttest:
Questionnaire
R
25
teachers
(Con-1)
O
Pretest:
Questionnaire
C
No training
O
Posttest:
Questionnaire
R
25
teachers
(Exp-2)
X
Dance for
Peace
Training-
Workshop
O
Posttest:
Questionnaire
R
25
teachers
C
No training
O
Posttest:

Factorial design
• In factorial design, researcher manipulates two or more
independent variables simultaneously to observe their effects
on the dependant variables. This design is useful when there
are more than two independent variables, called factors to be
tested.
• This design also facilitates the testing of several hypothesis at
a single time.
• Typical factorial design incorporates 2X2 or 2X3 factorial, but
it can be in any combination.
• The first number (α) refers to the independent variables or the
type of experimental treatments, & the second number (β)
refers to the level or frequency of the treatment.

Factorial design
Frequency of
mouth care
Protocols of the mouth care
Chlorhexidine (α1) Saline (α2)
4 hourly (β1) α1….β1 α2….β1

Randomized block design
• Control of inherent differences between
experimental subjects & differences in experimental
conditions is one of the difficult problems faced by
researcher in biological sciences.
• When there are a large number of experimental
comparison groups, the randomized block design is
used to bring homogeneity among selected different
groups.
• This is simple method to reduce the variability
among the treatment groups by a more
homogeneous combination of the subjects through

Randomized block design
Types of
antihypertensiv
e drugs
Blocks
Patients with
primary
hypertension (I)
Diabetic patients
with hyper
tension (II)
Renal patients
with
hypertension (III)
A A, I A, II A, III
B B, I B, II B, III
C C, I C, II C, III
• For example, a researcher wants to examine the effects of
three different antihypertensive drugs on patients with
hypertension.
• In this example, to ensure the homogeneity among the subjects
under treatment, researcher randomly places the subjects in
homogeneous groups (blocks) like patients with primary
hypertension, diabetic patients with hypertension, & renal
patients with hypertension .

Crossover design
• In this design, subjects are exposed to more than one
treatment, where subjects are randomly assigned to
different orders of treatment.
• It is also known as ‘repeat measures design’.
• This design is more efficient in establishing the highest
possible similarity among subjects exposed to different
conditions, where groups compared obviously have equal
distribution of characteristics.
• Through crossover design is considered as an extremely
powerful research design, sometimes it is not effective
because when subjects are exposed to two different
conditions, their responses of the second condition may be

Crossover design
• For example, when we are comparing the effectiveness of the
chlorhexidine mouth care protocol on group I & saline mouth
care protocol on the subjects of group II.
• Later, the treatment is swapped, where group I receives the
saline mouth care & group II receives chlorhexidine. In such
studies, subjects serve as their own control.
Groups Protocols of the mouth care
Group I Chlorhexidine (α1) Saline (α2)
Group II Saline (α2) Chlorhexidine (α1)

Advantages of True experimental design
• Experimental research designs are considered the most powerful
designs to establish the causal relationship between independent &
dependant variables.
• Where the purpose of research is explanation, causal relationship may
be established among the variables by experimentation, especially in
studies involving physical objects, where the variables are more easily
controlled than in human studies.
• In this studies, the controlled environment in which the study is
conducted can yield a greater degree of purity in observation.
• When the experiment is conducted in a laboratory, experimental unit, or
other specialized research setting, it is removed from the pressure &
problems of real-life situations & the researcher can pursue his or her
studies in a more leisurely, careful, & concentrated way.

Quasi –
Experimental
Research Design

• Quasi-experimental research design involves the
manipulation of independent variable to observe to effect on
dependant variable, but it lacks at least one of the two
characteristics of the true experimental design;
randomization or a control group.
• In other words, quasi-experimental designs have an element
of manipulation but lack at least one of the other two
properties that characterize true experiments; randomization
or a control group.
• Quasi-experimental designs are generally used to establish
the causality (effect of independent variable on dependent
variable) in situations where researchers are not able to
randomly assign the subjects to groups or for various
Quasi – Experimental Research Design

Main characteristics…
• Manipulation of the independent variables to
observe the effects on the dependant variables.
• Lack of at least one of the two other essential
characteristics of the true experiment, i.e.
random assignment of subject or a control
group.
• Quasi-independent variables are used instead
of true independent variables. Where
independent variable is not manipulates in
complete controller situations.

Types of quasi-experimental
design
Quasi-experimental
design
Nonrandomized control
group design
Time-series design

Nonrandomized control group design
• It is also known as the ‘nonequivalent control group design’.
• This design is identical to the pretest-posttest control group
design, except there is no random assignment of subjects in
experimental & control groups.
• In this design, experimental & control groups are selected
without randomization, & dependent variables are observed
in experimental as well as control groups before the
intervention.
• Later, the experimental group receives treatment & after that
posttest observation of dependant variables is carried out for
both the groups to assess the effect of treatment on
experiment group.

Exp. group
Control
group
Pretes
t
Pretes
t
Treatment Post-test
Post-test
Nonrandomized control group design

Time-series design
• This design is useful when the experimenter wants to
measure the effects of a treatment over a long period of time.
• The experimenter would continue to administer the treatment
& measure the effects a number of times during the course of
the experiment.
• Generally it is a single-subject research, in which the
researcher carries out an experiment on an individual or on a
small number of individuals, by alternating between
administering & then withdrawing the treatment to determine
the effectiveness of the intervention.

Exp.
group O1 O3O2 O3O2O1Treatment
Time-series design

Advantages of quasi-experimental design
• Quasi-experimental designs are more frequently used
because they are more practical & feasible to conduct
research studies in different field, where in the absence of a
large sample size, randomization &/ or availability of control
groups are not always possible.
• This design is more suitable for real-world natural setting
than true experimental research designs.
• It allows researchers to evaluate the impact of quasi-
independent variables under naturally occurring conditions.
• It may be able to establishing casual relationship. Wherein
some of the hypotheses are practically answered through
this design only.

Pre –
Experimental
Research Design

• This research design is considered very
weak, because the researcher has very
little control over the experiment
Pre –
Experimental
Research Design
One-shot case design
One-group pretest-posttest
design
Pre – Experimental Research Design

One-shot case design
• In this research design, a single
experimental group is exposed to a
treatment & observations are made after
the implementation of that treatment.
• There is no random assignment of
subjects to the experimental group & no
control group at all.
Exp.
group Treatment Post-test
Example: suppose you wish to see if a new textbook increases
student interest in your course (history, science, statistics, etc.)

One-group pretest-posttest design
• It is the simplest type of pre-experimental design, where
only the experimental group is selected as the study
subjects.
• A pretest observation of the dependant variables is made
before implementation of the treatment to the selected
group, the treatment is administered, & finally a posttest
observation of dependant variables is carried out to assess
the effect of treatment on the group.
• Some researcher also argue this design as sub type of
quasi-experimental research design. However in absence
of both randomization & control group.
• This design ethically can not be placed under the

Exp.
group
Pretes
t
Treatment Post-test
One-group pretest-posttest design
Example: suppose you want to assess the effects of weekly
counselling sessions on the attitudes of identified bullies in school

ADVANTAGES OF PRE-EXPERIMENTAL DESIGN:
o Very simple & convenient to conduct these studies in natural
settings, especially in nursing.
oMost suitable design for the beginners in the field of
experimental research.
DISADVANTAGES OF PRE-EXPERIMENTAL DESIGN:
oConsidered a very weak experimental design to establish
casual relationship between independent & dependant
variables, because it controls no threat to internal validity. It
has very little control over the research.
oIt has a higher threat to internal validity of research, & may
Advantages & Disadvantages of pre-experimental de

Research Validity
• Internal Validity – the validity of findings with the
research study; the technical soundness of a
study, particularly concerned with the control of
extraneous influences that might effect the
outcome
• External Validity – the degree to which the findings
can be inferred to the population of interest or to
other populations or settings; the generalizability of
the results
• Both are important in a study but they are
frequently at odds with one another in planning
and designing a study
• Internal validity is considered the basic minimum
for experimental research

Threats to Internal
Validity
• History – events occurring during the experiment that
are not part of the treatment
• Maturation – biological or psychological processes
within participants that may change due to the passing
of time, e.g., aging, fatigue, hunger
• Testing – the effects of one test upon subsequent
administrations of the same test
• Instrumentation – changes in testing instruments,
raters, or interviewers including lack of agreement
within and between observers

Threats to Internal Validity
• Statistical regression – the fact that groups
selected on the basis of extreme scores are not as
extreme on subsequent testing
• Selection bias – identification of comparison groups
in other than a random manner
• Experimental mortality – loss of participants from
comparison groups due to nonrandom reasons
• Interaction among factors – factors can operate
together to influence experimental results

Types of External Validity
• Population Validity –
• refers to the extent to which the results can be
generalized from the experimental sample to a
defined population
• Ecological Validity –
• refers to the extent to which the results of an
experiment can be generalized from the set of
environmental conditions in the experiment to
other environmental conditions

Threats to External Validity
• Interaction effects of testing – the fact that the
pretest may make the participants more aware of
or sensitive to the upcoming treatment
• Selection bias – when participants are selected in
a manner so they are not representative of any
particular population
• Reactive effects of experimental setting – the fact
that treatments in constrained laboratory settings
may not be effective in less constrained, real-
world settings
• Multiple-treatment interference – when
participants receive more than one treatment, the
effects of previous treatments may influence

Common Sources of
Error
• Many possible sources of error can cause the
results of a research study to be incorrectly
interpreted. The following sources of error are
more specific threats to the validity of a study than
those described previously
• Selected examples:
• Hawthorne Effect
• Placebo Effect
• John Henry Effect
• Rating Effect
• Experimenter Bias Effect

Hawthorne Effect
• A specific type of reactive effect in which
merely being a research participant in an
investigation may affect behavior
• Suggests that, as much as possible,
participants should be unaware they are in
an experiment and unaware of the
hypothesized outcome

Placebo Effect
•Participants may believe that the
experimental treatment is supposed to
change them, so they respond to the
treatment with a change in
performance

John Henry Effect
• A threat to internal validity wherein
research participants in the control group
try harder just because they are in the
control group

Rating Effect
•Variety of errors associated with
ratings of a participant or group
• Halo effect
• Overrater error
• Underrater error
• Central tendency error

Experimenter Bias Effect
• The intentional or unintentional influence
that an experimenter (researcher) may
exert on a study

Dr. K. Thiyagu, Assistant Professor, Department of Education, Central University of
Kerala, Kasaragod
thiyagusuri@gmail.com thiyagusuri@cukerala.ac.in

Experimental Design

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Experimental Design