1. FCE 3900 PENYELIDIKAN PENDIDIKAN

2. Rekabentuk Quasi-Eksperimen The word "quasi" means as if or almost, so a quasi-experiment means almost a true experiment.

3. Kenapa Quasi-Eksperimen?
Dinamakan Quasi-Eksperimental kerana penyelidikan yang dilakukan hampir menyerupai reka bentuk eksperimen, kecuali tiada pembahagian secara rawak dilakukan.
Pembahagian rawak sukar dijalankan dalam keadaan tertentu seperti pemboleh ubah atribut (jantina, ras, pendapatan penjaga dll) kerana akan menjejaskan pemboleh ubah seperti rasa terasing dalam kumpulan baru dan sebagainya. Oleh itu reka bentuk ini digunakan.
Kaedah reka bentuk quasi-eksperimen bukan sebenar-benar eksperimen kerana tiada pembahagian rawak dilakukan.
Gunakan kumpulan sedia wujud dalam (intact group).
Quasi-experimental Design

4. QUASI-EXPERIMENTAL DESIGNS
are usually constructions that already exist in the real world. Those designs that fall into the quasi-experimental category fall short in some way of the criteria for the true experimental group. A quasi-experimental design will have some sort of control and experimental group, but these groups probably weren't randomly selected. Random selection is usally where true-experimental and quasi-experimental designs differ.
Some advantages of the quasi-experimental design include:
Greater external validity (more like real world conditions)
Much more feasible given time and logistical constraints
Disadvantages:
Not as many variables controlled (less causal claims)

5. Ciri-Ciri Rekabentuk Quasi-Eksperimen
Dua atau lebih daripada kumpulan responden yang tidak diagih secara rawak.
Memerlukan kawalan terhadap pemboleh ubah luaran yang tegas.
Mengutamakan perbezaan antara kumpulan responden secara semula jadi.

6. Perbezaan antara eksperimen dengan quasi-eksperimen.
True and Quasi-Experimental Designs.
Aktiviti bacaan: Sila baca artikel yang bertajuk;
EXPERIMENTAL AND QUASI-EXPERIMENTAL RESEARCH DESIGN

7. Causal-Comparative Studies
Important Issues:
Primary purpose should be developing cause-and-effect relationships when experimentation is not possible
The “intervention” must have already occurred
Must identify and consider extraneous variables
Differences between the groups not due to the independent variable should be controlled
Be careful with causal conclusions 17 17

8. Causal-Comparative Studies
Go beyond relationships/associations to examine cause-and-effects.
Two types of these studies:
Ex Post Facto
Correlational 13 13

9. Causal-Comparative Studies Ex Post Facto
Applied when seeking cause-and-effect relationships, but cannot do experiments
One or more independent variables are used to study their effects on one dependent variable
Ex: What is the impact of a particular training on job performance 14 14

10. Causal-Comparative Studies Ex Post Facto (cont’d)
Ex. Continued:
Approach 1: Select two groups, one group is trained, the other is not. Next their job performance is measured (experimental design)
Approach 2: Look for groups with pre-existing conditions and compare their job performance. e.g., select a group that is already trained and one that is not trained and compare their job performance.
The groups selected must be as close as possible except for the independent variable 15 15

11. Causal-Comparative Studies Correlational
These studies use more sophisticated versions of correlation analysis to investigate cause-and-effects
Path Analysis: A causal model is developed from theory which shows by arrows the causal sequence that is expected. Correlation between these variables is used as empirical evidence of the proposed links.
Newer, more sophisticated methods:
Structural Equation Modeling
Latent Variable Causal Modeling 16 16

12. Ex Post Facto

13. ‘from what is done afterwards’
Ex post facto
‘from what is done afterwards’

14. From what is done afterwards
Ex post facto
The Latin term "Ex post facto" means, in a UK legal context: "by reason of a subsequent act".
Ex-post-facto designs ("after the fact")
From what is done afterwards

15. Studies that investigate possible cause and effect relationships by observing an existing condition or state of affairs and searching back in time for plausible causal factors.

16. Ex Post Facto (Causal-Comparative) Research
Explores possible causes and effects.
The independent variable is not manipulated, it has already been applied.
Focuses first on the effect, then attempts to determine what caused the observed effect.

17. The ex post facto design is a variation of the "after-only with control group" experimental design. The chief difference is that both the experimental and control groups are selected after the experimental variable is introduced rather than before. This approach eliminates the possibility that participants will be influenced by an awareness that they are being tested.

18. This type of study is very common and useful when using human subjects in real-world situations and the investigator comes in "after the fact." For example, it might be observed that students from one town have higher grades than students from a different town attending the same high school. Would just "being from a certain town" explain the differences? In an ex post facto study, specific reasons for the differences would be explored, such as differences in income, ethnicity, parent support, etc.

19. Characteristics of Ex Post Facto
Researcher takes the effect/dependent variable and examines it retrospectively
Establishes causes, relationships or associations and their meanings.
Researcher has little to no control over independent variables.
Flexible by nature.

20. Characteristics of Ex Post Facto Research
There is a control or comparison group.
Intact groups are used.
The treatment is not manipulated, it has already occurred.

21. Characteristics of Ex Post Facto Studies
 There may be both “treatment” and
“control” groups, however these will be
existing, not assigned by the researcher
 There is no manipulation of conditions

22. Ex Post Facto research
Researcher cannot manipulate some variables and therefor selects participants that have certain values for those variables by themselves (gender, personality, illness, ...)
Pros
Often only possible approach
Cons
Selection threat to internal validity: probably not only independent variable differs among participants

23. The experimenter does not manipulate the IV
The experimenter does not manipulate the IV... that is subjects cannot be randomly assigned to the levels of the IV - rather they assign themselves because the IV is not manipulated, it also qualifies as a descriptive technique

24. When to use this?
You can use this where more powerful experimental designs are not possible; when you are unable to select, control and manipulate the factors necessary to study cause and effect relationships directly, or when control variables except a single independent variable may be unrealistic and artificial.

25. Ex post facto advantages and disadvantages
Show a correlation where more rigorous experimentation is not possible
Exploratory tool
Useful to avoid articiality in the research.
Shows cause and effect relationships
Disadvantages
Lack of control for independent variable and randomizing subjects.
Never certain if causative factor has been included or identified
Relationship between two factors does not est. cause and effect.
May be regarded as too flexible.

26. What is causal research?
Casual Research explores the effect of one thing on another and more specifically, the effect of one variable on another. The research is used to measure what impact a specific change will have on existing norms and allows market researchers to predict hypothetical scenarios upon which a company can base its business plan.

27. For example, if a clothing company currently sells blue denim jeans, casual research can measure the impact of the company changing the product design to the colour white. Following the research, company bosses will be able to decide whether changing the colour of the jeans to white would be profitable. To summarise, casual research is a way of seeing how actions now will affect a business in the future.

28. Causality and ex-post-facto designs.
like "smoking causes cancer".

29. Melibatkan perbandingan antara kumpulan yang sedia wujud
Contoh: Menyelidik murid-murid yang menonton rancangan belajar bahasa Inggeris melalui siaran TV dan membandingkan prestasi mereka untuk mengkaji sama ada menonton program bahasa Inggeris di TV dapat membantu meningkatkan pencapaian mata pelajaran tersebut. Murid-murid dikumpulkan dalam beberapa kumpulan mengikut banyaknya mereka menonton siaran tersebut.

30. Examples of Ex Post Facto Studies
 What is the effect of day care on the social
skills of children?
 What is the relationship between
participation in extracurricular activities
and self concept?

31. Depression in rape victims
Ex Post Facto - example
Depression in rape victims

32. Research design X1 = rape victim X2 = control
Yij = average depression score in group i, at time j
indicates possible unequality of groups in both conditions

33. Reka bentuk ini menekankan sebab yang dijangka.
Contoh 1: Adakah program pendidikan pemulihan meningkatkan prestasi 3M murid-murid yang lemah?
Contoh 2: Adakah program kaunseling individu meningkatkan motivasi murid bermasalah?
Tafsiran sebab-akibat (cause-effect relationship)
Penyelidik perlu memastikan:
Terdapat hubungan antara A dan B;
A datang dahulu daripada B;
Tidak ada kesan pemboleh ubah luaran terhadap A, B atau interaksi A dan B.

34. Two Basic Approaches to Ex Post Facto Research
Begin with subjects who differ on an independent variable (such as their principal instrument/voice) and study how they differ on dependent variables (such as levels of performance anxiety or music theory test scores).
Begin with subjects who differ on a dependent variable (such as attrition from music--comparing those students who drop out of music with those who persist) and study how they differ on various independent variables (such as how much they practice, how they feel about their relationship with their teacher, how they feel about themselves as musicians, etc.).

35. CAUSAL-COMPARATIVE RESEARCH
"ex post facto"
Causality
Example Causality

36. Causal-comparative research is a useful tool that can be employed in situations where experimental designs are not possible. The researcher must remember, however, that demonstrating a relationship between two variables (even a very strong relationship) does not "prove" that one variable actually causes the other to change.

37. Tiga Jenis Bukti Yang Perlu Untuk Mengesahkan Hubungan Sebab-akibat
Perhubungan statistik yang signifikan antara pemboleh ubah bebas dan bersandar wujud dengan sah.
Pemboleh ubah bebas wujud sebelum pemboleh ubah bersandar.
Pemboleh ubah lain tidak mempengaruhi pemboleh ubah bersandar.

38. Kawalan Reka Bentuk Ex Post Facto
Empat bentuk kawalan:
Perubahan markah, mengambil kira markah subjek pada ujian pra dan pos.
Memadankan subjek mengikut ciri yang membezakan sesuatu populasi.
Menggunakan hanya subjek yang serupa.
Menggunakan analisis statistik seperti ANOVA dan ANCOVA.

39. Tips…
Kajian perbandingan sebab perlu digunakan apabila kajian eksperimen tidak dapat dilakukan.
Keadaan sebab mesti berlaku sebelumnya.
Pemboleh ubah ekstranous perlu dikenalpasti dan dicatat.
Perbezaan antara kumpulan perlu dikawal.
Hubungan sebab-akibat perlu dinyatakan dengan berhati-hati!

40. Example: Causality
Let's say you want to determine that your new fertilizer, MegaGro, will increase the growth rate of plants. You begin by getting a plant to go with your fertilizer. Since the experiment is concerned with proving that MegaGro works, you need another plant, using no fertilizer at all on it, to compare how much change your fertilized plant displays. This is what is known as a control group.

41. Set up with a control group, which will receive no treatment, and an experimental group, which will get MegaGro, you must then address those variables that could invalidate your experiment. This can be an extensive and exhaustive process. You must ensure that you use the same plant; that both groups are put in the same kind of soil; that they receive equal amounts of water and sun; that they receive the same amount of exposure to carbon-dioxide-exhaling researchers, and so on. In short, any other variable that might affect the growth of those plants, other than the fertilizer, must be the same for both plants. Otherwise, you can't prove absolutely that MegaGro is the only explanation for the increased growth of one of those plants.

42. Such an experiment can be done on more than two groups
Such an experiment can be done on more than two groups. You may not only want to show that MegaGro is an effective fertilizer, but that it is better than its competitor brand of fertilizer, Plant! All you need to do, then, is have one experimental group receiving MegaGro, one receiving Plant! and the other (the control group) receiving no fertilizer. Those are the only variables that can be different between the three groups; all other variables must be the same for the experiment to be valid (see validity).

43. Controlling variables allows the researcher to identify conditions that may affect the experiment's outcome. This may lead to alternative explanations that the researcher is willing to entertain in order to isolate only variables judged significant. In the MegaGro experiment, you may be concerned with how fertile the soil is, but not with the plants' relative position in the window, as you don't think that the amount of shade they get will affect their growth rate. But what if it did? You would have to go about eliminating variables in order to determine which is the key factor. What if one receives more shade than the other and the MegaGro plant, which received more shade, died? This might prompt you to formulate a plausible alternative explanation, which is a way of accounting for a result that differs from what you expected. You would then want to redo the study with equal amounts of sunlight.

44. SEKIAN TERIMA KASIH