One-Shot Experimental Case Study
Is a type of pre-experimental design where a single group of test unit is exposed to an experimental treatment and a single measurement is taken afterward. The measurement only takes place once; it is commonly used as a post-course or event survey or evaluation in (Learning, Performance, or Change Interventions), and it is important to note that the evaluation in the one-shot design really only provide feedback on the intervention or survey that the individual happens to be rolling out. It doesn't provide any other background information or any other evaluation. It is only evaluating that event or course that just took place.
The one-shot experiment design requires that several assumptions be made. For starters, they are going to assume that the measurement is related in some way to the intervention and not necessarily some other factors. However, this assumption may not be completely accurate. A good example of what they may look like; if an individual gave a training intervention and he or she receives poor scores, it may be related to some external factors going on in the institution; like poor communication from the top down regarding the requirement for training or the institution or organization is going or undergoing some form of reorganization and overall, there are really bad feelings amongst staff members about what is going on.
Sure enough that individual trainer or instructor for that invention is going to get an evaluation may reflect that and may not reflect the actual learning. On the flip side, it could work to give the individual a false positive. For instance, you receive a holiday bonus shopping gift in the amount of $500.00 from your employer, you may receive positive scores having nothing to do with the learning, but the fact everyone is just having a great old at the job.
The measurement may also be related to existing knowledge not learn during training. So people may respond to your score in the affirmative now they know how to respond to your training and utilize the materials or tools or the participants are used to it or maybe they know how to use it prior, or perhaps, the evaluation is limited to the specific group. It may not be applicable or generalized to other populations unless participants were randomly selected. Let say the trainer takes a group in the Marketing Department and trained them; it may just be you trained them in something that may work well for marketing but may not necessarily work well for say the IT Department.
That is a big assumption; the only way to get out of that assumption is when the trainer or researcher selects a random group of people from across the institution only then you can get a fair sampling to determine if the training may be effective for everybody.
Advantages and Disadvantages
Lastly, is to take a look at the advantages and disadvantages of the one-stop design. Well, some of the advantages of the one-shot design are, well, it is simple and cost-effective, more or less a small group, the researcher got his or group captured and he or she knows what he or she needs to evaluate. It can help reduce the cost and time frame for data collection because has captured that population that is already trained. It helps produce data that can be analyzed quickly and effectively. The data that the researcher gathers can be as part of the learning, performance, or change event since it is given out right after the training, and it will provide needed information if the researcher needs to use an ideal comparison.
Some of the disadvantages of the one-shot design, well, as mentioned early, it doesn't into account the external factors like prior knowledge or organizational issues that may be going on or the owners may be thinking of. It assumes positive reactions and knowledge tests lead to behavior change. And lastly, the findings may not generalize to other populations. The researcher really needs to get a good sampling of his or her organization to help if the one-shot design is to be used.
Example of a one-shot design research is the survey given at the end of an 8-week course 'Share Your Grantham Experience' or other research in the form of surveys sent to existing students. Based on the feedbacks, an administrator may determine what the can improve, include, or exclude. In such case, the students are the captured population.
Ex Post Facto Design
Ex post facto study or after-the-fact research is a category of research design in which the investigation starts after the fact has occurred without interference from the researcher. The majority of social research, in contexts in which it is not possible or acceptable to manipulate the characteristics of human participants, is based on ex-post facto research designs. This method identifies the previous events and present conditions and then collects data to investigate a possible relationship between these factors and subsequent behaviors. It is also often applied as a substitute for true experimental research to test hypotheses about cause-and-effect relationships or in situations in which it is not practical or ethically acceptable to apply the full protocol of a true experimental design.
Despite studying facts that have already occurred, ex-post facto research shares with experimental research design some of its basic logic of inquiry. That is the independent variable is causing changes in the dependable variable. This is the basis of an experiment. This done by having an experimental group and a control group. So if a new type of medication is been tested, the experimental group gets the new type of medication while the control group gets the old type of medication. This allows the researchers to test the efficacy of the new medication.
Ex post facto designs are different from True Experiment because ex-post facto designs do not use random assignment. True experiments have random assignments because the researcher(s) is looking at something else. In ex-post facto, the researcher is looking at a prior variable present in the participants.
In an ex-post facto design, the researcher is not randomly assigning people to experimental group or control group. The researcher is purposely putting people in a particular group based on some prior thing that they had. Example, they must have glasses or must be overweighed. There is no limit to the way the researcher(s) can divide the population. The prior thing that the participants must have is something that the researcher can just create or apply to people.
Commonly, an ex-post facto design is used for health psychology because like gender, you can't assign obesity, organ defect, or brain damage. Yes, a person could give another person a brain damage, but it will be really unethical.
Example: Which gender retains more information?
In a true experiment, the researcher will assign random of participants to the experimental group while assigning the other of participants to the control. But in the ex-post facto experiment, the researcher is trying to determine if there is a difference between the two genders. Since the researcher can't assign a person gender, he or she is forced to work around it. The two groups will simply be drawn alone the gender line. This experiment, unfortunately, does not take into consideration those of alternate genders; Group 1: female, Group 2: male.
Here, the researchers don't have an answer of how the experiment will turn out, but they can tell you it is an ex-post factor because they can't unassigned a person's gender and are forced to work with what they have.
Ex post facto design is a quasi-experimental study examining how an independent variable, present prior to the study in the participants affects a dependable variable. A quasi-experimental study is simply meant participants are not randomly assigned. Random Assignment is where a participant has an equal chance of being in the experimental or control group. The Ex post facto designs are most often used in health psychology because of it is difficult to assign a person a medical condition.
So when to use the ex-post facto design? It is used where more powerful experimental designs are not possible; when the researcher is 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.
Advantages and Disadvantages
Some of the advantages of the ex-post facto design show correlations where more rigorous experimental are not possible. It uses exploratory tools to avoid artificial in the research and to show the cause and effect relationships as well. On the other hand, some its disadvantages include the lack of control for the independent variable and randomizing subjects. Also, it never certain if a causative factor has been included or identified. The relationship between the two factors does not establish cause and effect. And, it may be regarded as too flexible.
For example, researchers are interested in the drink choices of Type 2 diabetics. So they form two groups, a group formed of Type 2 diabetes sufferers and a group with no diagnosed diabetics. The researchers then allow them to choose whatever drink they want from many choices in a waiting room before the study 'begins'. They then record what each person chooses and analyze the results.
Salkind, N. J. (2010). Encyclopedia of research design Thousand Oaks, CA: SAGE Publications Ltd doi: 10.4135/9781412961288
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