Internal validity refers to the clarity of relationships between variables and can be affected by various threats such as subject characteristics, loss of subjects, location, and instrumentation. Examples illustrate how these factors can lead to bias or inaccuracies in research results, such as the effect of participant characteristics on outcomes. To minimize these threats, standardization of conditions and detailed study designs are recommended.

1. Internal
Validity

2. What is internal validity?
Any relationship observed between
two or more variables.
*should be unambiguous as to what it
is mean to something else:
a.Number of factor (age, level, grade
etc.)
b.Type of material which is used

3. Example of internal validity:
A researcher wants to know the correlation
between students high and ability in
speaking.
The result says “the taller students have better
ability in speaking rather than the shorter
students.”
= the taller students are in 3-4 grade and the
shorter students are in 1-2 grade.

4. Threats (extraneous)
1. Subject characteristic
2. Loss of subject
3. Location
4. Instrumentation
• Instrument Decay
• Collector characteristic
• Collector bias
1. Testing
2. History
3. Maturation
4. Attitude
5. Regression
6. Implementation

5. 1. Subject characteristic
The result in individual or group differ from one
to another in united ways.
Example: why English 2011 often lose from
lectures in the pulling rope competition?
-subject characteristic:
a.Nutrient consumption
b.Weight
c. Height

6. 2. Loss of subject
Loss of participant.
Example:
Firstly there is 100 participants, a week later
there are only 88, then where 22 students go?
May be they got:
• Illness
• Dying
• Absent etc.

7. 3. Location
The particular place which the data are
collected.
Example: Doing an interview with students in
the classroom and students lounge will give
different result

8. 4. Instrumentation
The way in which the instrument is used.
Instrument decay (is not used properly)
Example: Checking a bunch of questionnaires,
firstly the researcher is firing up to do
checking, later on he gets tired and messily
checking.

9. 5. Collector characteristic
Sometimes data collector is gathered and
inevitable part of instrumentation.
Example: A researcher wants to know how the
society opinion towards police’s duties, in
case the researcher dress up like a police.
Therefore people tend to give a positive
opinion.

10. 6. Collector bias
Collector preference or judgment
Example: what do you think about WIFI?
-since the collector is “sensitive” with Wi-Fi,
sometime he neglect the rubric and tend
interrogating the participant.

11. 7. Testing
Where data are collected over a
period of time, it is common to test subjects at
the beginning of the intervention(s).
Testing using an instrument.
However in some case the researcher use the
same instrument so the students are not
really filling the test instead of memorizing the
answer from the previous test.

12. • Another case of testing.
A researcher wants to see the effectiveness on
collaborative method. He create an
experiment and applied collaborative method
in group A. However he doesn’t apply it in
group B

13. 8. History
The condition which effecting the participant
(experience).
Example: The participant really nervous during
the interview because the participant
remembered about the previous interview
which gives “complicated questions”.

14. 9. Maturation
Naturally participants will have development
both cognitive and physical.
Example: A researcher doing an experiment
about a grow up supplement to a young child
at 7th
. After a year that child has grow up.
It is bias whether it caused by the supplement or
the child is naturally grow up.

15. 10. Attitude of subject
To provide the control or comparison group(s)
with a special or novel treatment comparable
to that received by the experimental group.
How to treat the participants properly.

16. A researcher want to know the effectiveness of
suggestopedia.
He played a music in class A but not in class B.
He said to students in class B that music can not
played in the class.
In this case the researcher does not treat the
participants properly.

17. 11. Regression
there is no fix reasons to explains regression in
research.
Example: first test student A get 10 but in the
second test with the same test but different
days he gets 5.

18. 12. Implementation
The possibility that the experimental group may
be treated in ways that are unintended and
not necessarily part of the method.
It is occur because:
• First- assigned to implement different
methods, so the out comes will different
• Second-have a personal bias in favor of one
• method over the other

19. How to minimize the threat
1. Standardize the condition, procedure and
information
2. More information for the subject /
participant
(avoiding: subject characteristic, mortality,
regression, maturation)
3. More information on the detail of the study
(avoiding: location, instrument, history,
subject attitude, and implementation)
4. Choose proper design