EDU 5900 AB RAHIM BAKAR 1 Research Approach Quantitative Qualitative Experimenta l Ex Post Facto Correlational Survey Pre experiment True Experiment Quasi

EDU 5900 AB RAHIM BAKAR 1

Research ApproachResearch Approach

Quantitative Qualitative

Experimental

Ex Post Facto

Correlational

Survey

Pre experiment

True Experiment

Quasi Experiment


Types of ResearchTypes of Research

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

Purpose or end sought

Descriptive

EXPLORE DESCRIBE EXPLAIN-PREDICT

CONTROL

[PRE EXPERIEMNTAL]

SURVEY RESEARCH CORR & EX POST

TRUE EXP &QUASI EXP


Research ApproachResearch Approach

Quantitative Qualitative

Experimental

Ex Post Facto

Correlational

Survey

Pre experiment

True Experiment

Quasi Experiment


Experimental Research Designs Experimental Research Designs have Two Purposes:have Two Purposes:

• …to provide answers to research questions

• ...to control variance (differences)


The main function of the experimental The main function of the experimental

research design is to control variance.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.


Therefore the researcher attempts to: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 ).


Maximization of Experimental VarianceMaximization of Experimental Variance

• 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.


Maximization of Experimental VarianceMaximization of Experimental Variance

• 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.


Minimizing Error Variance has Two Minimizing Error Variance has Two Principle Aspects: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)


Experimental DesignsExperimental Designs

Three types of experimental research designs:

• pre-experiment, • true experimental and • quasi-experimental.

•


• 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.


• All experiments involve

– treatment – outcome – units of assignment – comparison from which change can be

inferred and attributed to the treatment.


Characteristics of True Characteristics of True ExperimentsExperiments

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.


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.

•


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


Strengths of the Experimental DesignStrengths 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.


Weakness of the Experimental DesignWeakness 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.


• 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 ------ ------- O2 X2 O2


• 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!


• 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


• 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)


STATIC GROUP COMPARISON

X1 O1 inquiry Ujian ------------------------ X2 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. • Existing group or intact group (2 classrooms)• No randomization of subjects to groups. Sebab

tak boleh nak randomized.


• 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.


• True experimental designs include:

– -pre-test/post-test control group design – -Solomon four-group design – -post-test only control group design


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


• 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.


• 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.


• Randomize Posttest-Only Control Group Design

R X O1 or R X1 O1 R O2 R X2 O2 which can easily be

extended to R X1 O1 R X2 O2 R X3 O3 R X4 O4


• 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.


• 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)


Solomon Three-Group DesignSolomon 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…..


SOLOMON THREE GROUP DESIGNSOLOMON THREE GROUP DESIGN

Group Pretest Treatment

Posttest

(R) E Y1 X Y2

(R) C1 Y1 _ Y2

(R) C2 _ X Y2


• Solomon Four-Group Design

• R O1 X O2 or R O1 X1 O2 • R O3 O4 R O3 X2 O4 • R X O5 R X1 O5 • R O6 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



• 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.


• 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


• 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


Group Pretest Treatment Posttest

(R) E Y0 X Y1

(R) C1 Y01 _ Y2

(R) C2 _ X Y3

(R) C3 _ _ Y4


Factorial designsFactorial 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


• 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


• 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

Mean 43 35

Example A


small large

30

35

40

45

5046

4038

32

inquiry

lecture

In example, the inquiry method is shown to In example, the inquiry method is shown to be superior in both small and large classes. be superior in both small and large classes. Hence there is no interaction effect. Hence there is no interaction effect. Regardless of class size, inquiry method is Regardless of class size, inquiry method is superior than lecture method. There is no superior than lecture method. There is no interactioninteraction

What is interaction What is interaction effect? The effect effect? The effect obtained may be differ obtained may be differ for a different group. The for a different group. The result is moderated by result is moderated by another variableanother variable


Method of teaching

Class size Method A Method B Mean

Small 48 42 45

large 32 38 36

Mean 40 40

Example B


small large

30

35

40

45

5048

32

inquiry

lecture

42

38

Studenst did better in small class than in largeClass with both methods.However, students in smallClass did better when taughtUsing inquiry method. Students in large classDid better when taught usingLecture method. Here there is an interaction betweenClass size and teachingmethods


• 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)


• 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

Documents

EDU 5900 AB RAHIM BAKAR 1 Research Approach Quantitative Qualitative Experimenta l Ex Post Facto Correlational Survey Pre experiment True Experiment Quasi