1. Research Approach Qualitative Quantitative Experimental Pre experiment
Ex Post Facto
True Experiment
Correlational
Quasi Experiment
Survey
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2. Types of Research Purpose or end sought EXPLORE DESCRIBE EXPLAIN-
To become familiar with phenomena; to gain new insight; to formulate a more specific research problem or research hypothesis (use research questions or objectives
To portray accurately the incidence, distribution, and characteristics of a group or situation (usually do not begin with specific hypothesis; use research questions or objectives
To investigate relationships between variables (Begin with specific hypothesis)
To test hypotheses of causal relationships between variables
EXPLORE
DESCRIBE
EXPLAIN-
PREDICT
CONTROL
Descriptive
[PRE EXPERIEMNTAL]
SURVEY RESEARCH
CORR &
EX POST
TRUE EXP &
QUASI EXP
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3. Research Approach Qualitative Quantitative Experimental Pre experiment
Ex Post Facto
True Experiment
Correlational
Quasi Experiment
Survey
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4. Experimental Research Designs have Two Purposes:
…to provide answers to research questions
...to control variance (differences)
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5. In other words control variance.
The main function of the experimental research design is to control variance.
Principle: maximize systematic variance, control extraneous systematic variance, and minimize error variance.
MAX-MIN-CON
In other words control variance.
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6. Therefore the researcher attempts to:
maximize the variance of the variable(s) of the research hypothesis (i.e., maximize the difference in the dependent variable [outcome] caused by maximizing the differences in the independent variable [treatment]).
control the variance of extraneous or "unwanted" variables that may have an effect on the experimental outcomes, but which he/she is not interested (limit factors other than the treatment (IV) that could be causing differences in the outcome (DV) .
minimize the error or random variance (i.e., avoid unreliable measurement instruments which have high errors of measurement ).
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7. Maximization of Experimental Variance
the variance due to the manipulated (i.e., treatment) or attribute (i.e., gender) variables (IV)
research precept:
design, plan and conduct research so that experimental conditions are as different as possible on the independent variable.
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8. Maximization of Experimental Variance
the variance due to the manipulated (i.e., treatment) or attribute (i.e., gender) variables (IV)
research precept:
design, plan and conduct research so that experimental conditions are as different as possible on the independent variable.
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9. Minimizing Error Variance has Two Principle Aspects:
reduction of errors of measurement through controlled conditions (i.e., standardize testing procedures)
increase in the reliability of measures (i.e., revise test instruments or find more reliable ones)
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10. Experimental Designs Three types of experimental research designs:
pre-experiment,
true experimental and
quasi-experimental.
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11. These designs are generally used to determine cause and effect
These designs are generally used to determine cause and effect. They allow us to make inferences. According to David Hume, there are three criteria to be met to infer causality:
Contiguity between the presumed cause and effect. In other words, the causal variable (independent) and the effect variable (dependent) must be associated.
Temporal Precedence. In other words, the cause must precede effect.
Constant conjunction. In other words, the cause is present whenever the effect is obtained.
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12. All experiments involve treatment outcome units of assignment
comparison from which change can be inferred and attributed to the treatment.
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13. Characteristics of True Experiments
Manipulation
The experimenter does something to at least some of the subjects in the experiment. The introduction of that something is often referred to as the experimental treatment or experimental
Intervention. This is also known as the independent variable. The researcher manipulates this independent variable by administering it to some subjects and withholding it from other subjects. In other words, the experimenter varies the independent variable and observes the effect that the manipulation has on the dependent variable of interest.
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14. Control
Control summarizes all of the major experimental activities. They are manipulation, use of comparison (control) groups, and randomization.
Campbell and Stanley (1963) observed that obtaining scientific evidence requires at least one comparison. Control groups are used for this purpose.
The term control group refers to the subjects that do not receive the experimental treatment and their performance on the dependent variable serves as a basis for evaluating the performance of the experimental group (the group who received the experimental treatment) on the same dependent variable.
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15. Randomization
The assignment of subjects to groups on a random basis. The term random essentially means that every subject has an equal chance of being assigned to any group.
The intent is to equalize the groups however, there is no guarantee that the groups will be equal. The chance of obtaining unequal groups diminishes as the sample size increases. Researchers generally use a table of random numbers to facilitate the randomization
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16. Strengths of the Experimental Design
Some researchers believe that this is the most powerful research design as it gives us cause and effect relationships.
If we do this then we can expect that. This if-then relationship is important to those health care practitioners who want to predict and control.
Therefore the strength lies in the fact that causal relationships can be inferred.
This is not without controversy. Some scholars believe that the notion of causality among phenomenon is untenable.
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17. Weakness of the Experimental Design
There are a number of variable of interest that are not amenable to manipulation. For instance we cannot randomly confer upon infants their weight at birth to observe the effect of birth weight on subsequent morbidity.
Ethical considerations may prevent the manipulation of the independent variable. You would not inflict pain for the sake of an experiment.
Artificial circumstances may affect the results. Laboratory designs take place in an artificial setting. Easier to control for external variables and is not as generalizable because it constrains the human experience. Field designs take place in the actual setting and may be better but there are more problems with controls.
The Hawthorne Effect: effect of being in the study group may be sufficient to cause people to change their behaviors. This is the reason that double blind studies are conducted. In which neither subject nor those who administer the treatment knows which is the experimental or control group.
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18. Pre-Experimental Designs 1. One-Shot Case Study X O
2. One-Group Pretest-Posttest Design
O1 X O2  
3. Static-Group Comparison or Intact- Group Comparison
X O1 or X1 O1
O X2 O2
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19. New textbook pencapaian
One shot case study
( X O)
satu kumpulan diberikan treatment atau didedahkan kepada suatu jenis treatment kemduain pengukuran dilakukan.
Misalnya try to determine the effect of a new teksbook on pencapaian dalam peperiksaan
X O
New textbook pencapaian
Tiada kawalan; no comparison (O1) yang ada hanyalah O2; no pretest score (O1)
Jadi tak pasti samada O di sebabkan oleh X
So, what causes O? Tak pasti lagi!
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20. One-group pretest-posttest design O1 X O2
Still no control group. Tapi tahu ada perubahan atau tidak kerana ada maklumat awal mengenai pencapaian subject berkenaan (pretest score).
Need to have a comparison group yang tak dapat treatmeNt yang sama.
belum boleh buat andaian lagi bahawa perubahan disebabkan oleh X
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21. History? Events that may occur between the two observations
What are the threats to internal validity posed by this design? Almost all!! Except selection & mortality.
History? Events that may occur between the two observations
Maturation > biological and psychological (grow older, tired, bored etc)
Testing >
Instrument decay > perubahan yang sengaja atu tidak sengaja (oberver/interviewer)
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22. STATIC GROUP COMPARISON
X O1
inquiry Ujian
X O2
lecture ujian
Gunakan dua atau lebih kumpulan eksperimen
Existing group or intact group (2 classrooms)
No randomization of subjects to groups. Sebab tak boleh nak randomized.
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23. Banyak digunakan dalam penyelidikan pendidikan
Berikan treatment yang berbeza (kaedah mengajar inquiry to group A dan lecture to group B)
Administrative performance of principals with bachelor degree and principals with Masters degree.
Any internal validity threats? Khususnya selection and mortality.
What selection? No random assignment of subjects to groups. Differences of subject characteristics.
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24. True experimental designs include:
-pre-test/post-test control group design
-Solomon four-group design
-post-test only control group design
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25. Pretest-Posttest Control Group Design R O1 X O2 or R O1 X1 O2
R O3 O4 R O3 X2 O4
which can easily be extended to
R O1 X1 O2
R O3 X2 O4
R O5 X3 O6
R O7 X4 O8
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26. The pre-test-post-test experimental design is more complex
The pre-test-post-test experimental design is more complex. It is called pre-test-post-test because there are two points of measurement, one before the experimental treatment and one after the experimental treatment.
Example: Suppose we wanted to examine the effect on the heart rate of being restrained. The design would involve imposing a posey belt on the experimental group and no posey belt on the control group. The dependent variable which is the heart rate would be measured at two points in time. Before the posey belt and after the posey belt. This allows us to examine if heart rate changes were produced as a result of being restrained.
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27. Kawal kesemua threats to internal validity
Kenapa ada prestest? Means of checking if both groups are similar & assess if changes occur due to treatment not because of existing factors
Dapatkan perbezaan skor ( O2 - O1) dan
(O4 - O3).
Jalankan ujian t atau anova (?) untuk uji hipotesis yang mengatakan treatment tidak ada kesan ke atas pencapaian.
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28. Randomize Posttest-Only Control Group Design
R X O1 or R X1 O1
R O R X2 O2
which can easily be extended to
R X1 O1
R X2 O2
R X3 O3
R X4 O4
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29. The post-test only experimental design is a simple design
The post-test only experimental design is a simple design. It is called post-test only because the data is collected after the experimental treatment is complete.
Example: Hypothesis is that the color of a pediatric nurses uniform affects the degree to which children display positive and negative affective behavior (laughing, crying).
The causative or independent variable is the uniform color and the effect variable or dependent variable is the child’s behavior.
The independent variable is manipulated by assigning some nurses white uniforms and some nurses colored uniforms.
Thus, in this study we could compare the affective behaviors of children cared for by nurses in white uniforms and those cared for nurses in colored uniforms.
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30. Subject di tempatkan dalam kumpulan secara random
Control for selection, maturation, statistical regression, testing.
May not control mortality- drop out> why drop out?
report berapa bilangan subject yang drop out
Drop out cuase dissimilarity of the groups
Instrumentation, history may still be the threats
Example of a study using this design?
Perhaps of all design to use if we have 40 subjects in each group (Frankael & Wallen, 1990)
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31. Solomon Three-Group Design
Three groups are involved
Overcoming the difficulty in Pretest-Posttest Control Group Design [effect pf pretesting and treatment]
A second control group [C2) is not pretested but exposed to treatment
Compare the Y2 of the three groups to see if treatment really made the difference
You can check of the interaction effect between pretest and treatment…..
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32. SOLOMON THREE GROUP DESIGN
Pretest
Treatment
Posttest
(R) E Y1 X Y2 C1 _ C2
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33. Solomon Four-Group Design R O1 X O2 or R O1 X1 O2 R O3 O4 R O3 X2 O4
R X O R X1 O5
R O R X2 O6
Rekabentuk ini merupakan modifikasi posttest only control group or pretest-posttest control group (Frankel & Wallen, 1990) yang membolehkankan kita melihat kesan pembolehubah tambahan
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34. EDU 5900 AB RAHIM BAKAR

35. The Solomon four-group design is a version of the pre-test-post-test design.
It adds two addition groups. The purpose of adding the two groups is to separate the effects of the pre-test and to segregate it from the intervention..
In other words, a pre-test may be a sensitizing treatment that may affect the results of an actual treatment.
1 is an experimental groups without the pretest 1 is the control group without the pre test
Example: If our intervention was a workshop to improve nurses attitudes toward alcoholic patients, the pre-test may sensitize the nurses and affect their attitudes at that point and obscure the analysis of the workshop’s effect.
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36. Usaha untuk menghapuskan kemungkinan kesan pretesting
Random assignment of subjects to four groups. Dua mendapat pretest dan dua lagi tidak. Kesemuanya akan diposttest
Better control for IV threat but require larger sample and a lot of hard work
Have to conduct two experiments simultaneously
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37. Strength of Solomon Four Group Design
Incorporate strengths of design Solomon Three Group Design and Randomized Pre and Posttest Designs, Randomized Posttest Only Control Group Design
Can make several comparison to determine the effect of the treatment
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38. Group Pretest Treatment Posttest (R) E Y0 X Y1 C1 Y01 _ Y2 C2 Y3 C3 Y4
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39. Factorial designs
Two or more variables are manipulated simultaneously in order to study the independent effect of each variable on the dependent variable as well as the effect caused by interaction of several independent variables
We can have the design whereby we manipulate only one independent variables or more than one independent variables
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40. Simple factorial design
The interest is on the effect of a single independent variable but must also consider other variable that may influence the dependent variable.
Typically these variables are attribute variable such as race, gender, SES, etc.
Enable the researcher to study several relationship with one set of data
Able to study interaction between variables
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41. The simplest factorial design is 2 X 2 Factorial Design
The simplest factorial design is 2 X 2 Factorial Design. Here you have two independent variables with two levels each
Method of teaching
Class size
Inquiry Method
Lecture Method
Mean
Small 46 38 45
large 40 32 36 43 35
Example A
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42. In example, the inquiry method is shown to be superior in both small and large classes. Hence there is no interaction effect. Regardless of class size, inquiry method is superior than lecture method. There is no interaction 50 46 45
inquiry
What is interaction effect? The effect obtained may be differ for a different group. The result is moderated by another variable 40 40 38 35
lecture 30 32
small
large
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43. Method of teaching Class size Method A Method B Mean Small 48 42 45
Example B
Method of teaching
Class size
Method A
Method B
Mean
Small 48 42 45
large 32 38 36 40
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44. small class than in large Class with both methods.
Studenst did better in
small class than in large
Class with both methods.
However, students in small
Class did better when taught
Using inquiry method.
Students in large class
Did better when taught using
Lecture method. Here there
is an interaction between
Class size and teaching
methods 50 48 45
inquiry 42 40 38
lecture 35 30 32
small
large
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45. There is an interaction between class size and methods
Even though students in small class did better than those in large class, how well depends on the method used.
As a result the researcher may conclude that effectiveness of the method is dependent on the class size.
There is an interaction between class size and methods
If factorial design was not used, you may conclude that there is no effect of method on achievement (40, 40)
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46. Moderator variable : (1) small class and (2) large class.
You can have a more complicated factorial design such as n BY n Factorial Design
Example: (1) CAI, (2) Lecture-Discussion (3) Television Lecture (4) Quite Reading
Moderator variable : (1) small class and (2) large class.
3X3 or 4X2 or 3X2
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