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Taking an example of some educational program seeking to look into carious program variations, in an effort to arrive at a decision as to which program works best. For example, one would seek to alter the time students receive instruction where one group receives teaching instruction for one hour a week, the other group for two hours a week, and the third group for three hours a week. More so, one can opt to alter the setting such that each of the four groups are subjected to four different settings. With each group being taught in a different classroom with different styles of relaying teaching instruction, different sitting arrangements, different study materials and different teaching aids then to realize which would result in the best educational program would be dependent on the factorial design.
In this case, the crossing each of the three instruction relaying time per week conditions with each of the four settings the factorial design would be 3×4. Factorial design allows for a factor to be considered as the major independent variable and the two factors in this case are instruction relay times and the classroom settings (Cozby, 2006). On the other hand, the level relates a subdivided factor such that relay of student instruction has three levels while classroom setting are represented in four levels. The dependent variable in this case will be the students learning outcomes. Therefore the students that produce the best results as desired by educational planners would champion for the adoption of the most successful educational program.
Considering a research group studying the impact of selected food additives with regard to the development of fish in an aquaculture farm, one can employ factorial design to describe the 4×4 design. This is used to optimize the coordination of the food additives experiment in four different fish stock densities by choosing four groups. Employing scientific method rules, statistics compels each experiment to be carried out in triplicate. Thus testing four levels of additive concentrations in four different fish tank densities, the factorial design would be 4×4, where the independent variables are the additive concentrations and the different fish densities with the fish development outcome being the dependent variable (Cozby, 2006).
1) ABA research design
This design incorporates the establishment baseline condition, introductory treatment and experimental treatment prior to winding up to the baseline condition (Cozby, 2006). This experimental design is employed where it is necessary to make observation on behavioral changes that a subject may present due to a prescribed treatment regime.
2) ABAB research design.
This research design involves the baseline as the initial measurement attained as represented by the initial (A) then the treatment measurement established as represented by the initial (B), while the second (A) represents removal from the treatment regime and finally a re-introduction to the same treatment design as represented by the second (B) (Cozby, 2006). It therefore incorporates two components, the first being the collection of baseline data, treatment application and the measurement of treatment outcomes. The second component includes; return to baseline measurements to observe reaction from treatment withdrawal, the subsequent return to treatment and the measurement of the resultant change.
3) What are the advantages of an ABAB design over ABA design?
The advantage of ABAB over ABA is that it enables researchers to establish an underlying functional relationship occurring between a treatment intervention and observed behavior changes (Cozby, 2006). Another advantage is that it allows for treatment discontinuation in case dangerous behavior and instances where a target behavior is considered as irreversible as it may involve a learning experience (Cozby, 2006).
This would entail a selection regression such that a selected program group being high at the pretest phase as with the students joining a social fraternity. They may however score low compared to the comparison group which is the honors fraternity group during the post test phase. This would imply a regression towards the measured population’s mean (Cozby, 2006). In the posttest, the group that does not join a fraternity is seen to perform poorly in relation to exhibiting concern to civil issues translating to a case of pure regression.
Cozby, P. C. (2006). Methods in Behavioral Research, 9th Edition. New York City, NY: McGraw-Hill.