2. Intact Group Design and
True Experimental
design
Presenter : Minh Sang

3. Intact Group Design
 This is the design that most classroom
researchers use.
 Step 1 : Select 2 classes to make 2 groups.
One is experimental group and the other is
control group ( You can decide it by the flip of
a coin )
 Step 2 : You give the treatment ( experimental
instruction ) to the experimental group, not the
control group

4. Intact Group Design
 Step 3 : Give the 2 groups a posttest. After the
posttest, we can have the result for the
research.
In short, an intact group design is :
G1 x T1
G2 T1
G1 : Experimental Group
G2 : Control Group
T1 : Posttest

5. Intact Group Design
 Example :
 You want to investigate the effect of grammar
correction on the writing skills of ESL students
 Step 1 : Select two similar groups of ESL ss.
Flip the coin to decide which group is the
experimental and control group
 Step 2 : Give the Exp Group the treatment
( grammar correction ) and do nothing with the
Control group.

6. Intact Group Design
 Step 3 : Give a pottest to 2 groups. After the
test, you will have a conclusion that grammar
correction is effective or not ( If the Exp Group
has the higher scores, it means that your
treatment – grammar correction is effective )

7. True Experimental Design
 This design is used for situations in real life,
when we don’t have any particular groups or
classes, teams for our research.
 It is similar to the intact group design. and you
may have a pretest for the Pretest pottest
control group design

8. True Experimental Design
 Pottest only control group : this is nearly the
same as the the intact group design. The
difference is that we choose the members for
the group randomly :
So we have : G1 ( random ) X T1
G2 ( random ) T1

9. True Experimental Design
 Pretest pottest control group design : We may
have a pretest for this design :
G1 ( random ) T1 X T2
G2 ( random ) T1 T2
So why do we have the T2 ( prettest ) ?

10. True Experimental Design
 The T2 ( prettest ) is given when the time you
have between the prettest and pottest is not
considerable ( not sufficient ) and it may affect
the conclusion of your research.
  It is when you give a prettest to test the
knowledge, ability…of the 2 groups that you
have. After all, your conclusion should be
much more defensible.

11. QUASI-EXPERIMENTAL DESIGN
Presenter: Minh Dang

12. • Quasi-experimental design is practical
compromises between true experimentation
and which we wish to investigate.

13. • Quasi-experimental design is susceptible
(easily effected) to some of the questions of
internal and external validity

14. • By using Quasi-experimental design, we
control as many variables as we can and also
limit the kinds of interpretations we make
about cause-effect relationships and hedge
the power of our generalization statements

15. Time-series design
• Because of limitations  sometimes it is
impossible to have a control group
•  use time-series design to deal with the
lack of control group

16. • Time-series design use several pretest and
several postest
• No treatment during the pretests  know the
changes when there are no treatments
• After some pretests  treatment  some
posttests  changes from the treatment
•  more accurate comparison, conclusion

18. • Line 1: no effect
• Line 2: negative effect
• Line 3: positive effect  treatment is
effective

19. Equivalent time sample design
• The treatment is introduced and
reintroduced between every other pretests
and posttests
• Test 1  treatment  test 2  treatment 
test 3 treatment  …

20. In short
• Quasi-experimental design: control many
variables and reduce limitations
• Time-series design: pretests  treatment 
posttests
• Equivalent time-sample design: test 
treatment  test  treatment  …

21. EX POST FACTO DESIGNS
Presenter: Huu Loc

22. EX POST FACTO DESIGNS
 When researchers control the threats to
internal and external validity, they are trying
to find a direct relationship between the
independent and dependent variables.
 In other words, they select the
population, sample, treatments, and
variables in order to find a cause-and-
effect relationship between the variables.

23. example
You may have created a series of media lessons
on how to say no to requests in English.
Not randomly select Can not draw causal
your Ss, organize relationships
your control and between your media
treatment groups, materials and Ss'
and control for improvement in
factors aside from ability to turn down
the media lessons requests gracefully in
which might English.
influence the results

24. When considering all the factors that you
would need to control, you might think that
designing a true experimental research project
is almost impossible.
But , it should not mean that we have to give
up approximating the ideal as much as
possible.
 X causes Y is an extremely difficult thing
to do unless the research is carefully
designed and as many extraneous factors
are controlled as possible.

25. When there is no possibility of random
selection of Ss, instead of abandoning the
research, we simply have to limit the domain
of our claims.
oWe have to avoid making cause and effect
statements.

26. EX POST FACTO designs are often used
when the researcher does not have
control over the selection and
manipulation or the independent
variable.
 Researchers look at the type and/or
degree of relationship between the two
variables rather than at a cause-and-
effect relationship.

27. example
 We can study the relationship between scores on
a school- leaving exam in ESL and teachers' ratings
for the Ss using an ex post facto design.
 We can see if there is a certain amount of
agreement between the two sets of scores. Any
relationship between the scores of the groups
would not be related to any instructional program
we had given them before the test.
 The designs are called ex post facto. The
researcher has no control over what has already
happened to the Ss.
 The treatment has been given prior to the
research project.

28. There’re 2 EX POST FACTO designs
o Correlational designs
o Criterion group
design

29. Correlational designs are the most
commonly used subset, in which a group of
Ss may give us data on two different
variables.
o For example, students planing to study in the US take
the TOEFL. Many universities also have entrance
exam to administer to students. We can then look at
the relationship of Ss’ scores on one test to their
scores on the other.
o Or, foreign students may be asked to take both the
Graduate Record Exam (GRE) and an English
placement exam prior to admission to a university.
o The score for each S on one test can be compared
with the score on the other, allowing us to see
whether whose students who score high on one lest
also score high on the other.

30. The schematic representation of this
design would be
T1 T 2

31. • It’s no causal relationship between the
two variables --> the distinction between
independent and dependent variables is
not well defined.
• It is arbitrary to call one or the other the
independent variable.
• But, it is usually the case that the
investigator may be more concerned with
one than the other and may therefore
label the first the independent variable
and the second the dependent variable
and show this by the labels X and Y.

32. In a CRITERION GROUP DESIGN, two
groups of Ss are compared on one
measure.
In this design, two groups of Ss are
compared on one measure. With this
design, you might, for example, measure
the reading peed of Iranian and French
students, assuming you want to see how
related or different they might be.

33. The design would look like this:
G1 T1
G2 T1

34. You can change the design into a two-
criterion design by considering level of
language proficiency as well as their native
language.
In this case the criterion group design forms
a factorial design.

35. FACTORIAL DESIGNS
Presenter: Ngan Giang

36. DEFINITION
• Is simply the addition of more variables to
the other designs
• There will be more than one independent
variable considered
• The variables may have one or many levels

37. 2 x 2 example
Room Temperature
Test Difficulty (Level) 50 degrees (Level) 90 degrees
(Level) Hard Test Hard Test in 50 degrees Hard Test in 90 degrees
(Level) Easy Test Easy Test in 50 degrees Easy Test in 90 degrees
We are interested in studying the effect of room temperature
on test taking. To do this, we compare test scores of students
who take a test in a 90 degree room vs. those who take a test
in a 50 degree room.

38. • Factor 1:
Treatment
– psychothera
py
– behavior
modification
• Factor 2:
Setting
– inpatient
– day
treatment
– outpatient

39. • higher scores
mean the
patient is
doing worse.
• day treatment is
never the best
condition.
• psychotherapy
works best with
inpatient care
and behavior
modification
works best with
outpatient
care.

40. THE PROS AND CONS
• Factorial designs are extremely useful to psychologists and
field scientists as a preliminary study, allowing them to
judge whether there is a link between variables, whilst
reducing the possibility of experimental
error and confounding variables .
• The factorial design, as well as simplifying the process and
making research cheaper, allows many levels of analysis.
As well as highlighting the relationships between variables,
it also allows the effects of manipulating a single variable
to be isolated and analyzed singly.
• The main disadvantage is the difficulty of experimenting
with more than two factors, or many levels. A factorial
design has to be planned meticulously, as an error in one
of the levels, will jeopardize a great amount of work.

41. Summary
1. What is experimental design?
2. Types of experimental design:
– Pre-experimental design
– True experimental design
– Quasi-experimental design
– Ex post facto design
– Factorial design

42. Thanks for your attention!
• Group 5:
1. Dinh Quoc Minh Dang
2. Vo Huu Loc
3. Nguyen Dinh Minh Sang
4. Nguyen Ngoc Cam
5. Tran Thi Ngan Giang