What type of experimental design is being used

Therefore, the quasi-experimental research bearing a resemblance to the true experimental research, but not the same. In quasi-experiments, the participants are not randomly assigned, and as such, they are used in settings where randomization is difficult or impossible. This is very common in educational research, where administrators are unwilling to allow the random selection of students for experimental samples.

Some examples of quasi-experimental research design include; the time series, no equivalent control group design, and the counterbalanced design. The true experimental research design relies on statistical analysis to approve or disprove a hypothesis. It is the most accurate type of experimental design and may be carried out with or without a pretest on at least 2 randomly assigned dependent subjects.

The true experimental research design must contain a control group, a variable that can be manipulated by the researcher, and the distribution must be random. The classification of true experimental design include:.

The first two of these groups are tested using the posttest-only method, while the other two are tested using the pretest-posttest method. Experimental research examples are different, depending on the type of experimental research design that is being considered. The most basic example of experimental research is laboratory experiments, which may differ in nature depending on the subject of research.

During the semester, students in a class are lectured on particular courses and an exam is administered at the end of the semester. In this case, the students are the subjects or dependent variables while the lectures are the independent variables treated on the subjects. Only one group of carefully selected subjects are considered in this research, making it a pre-experimental research design example. We will also notice that tests are only carried out at the end of the semester, and not at the beginning.

Further making it easy for us to conclude that it is a one-shot case study research. Before employing a job seeker, organizations conduct tests that are used to screen out less qualified candidates from the pool of qualified applicants. This way, organizations can determine an employee's skill set at the point of employment. In the course of employment, organizations also carry out employee training to improve employee productivity and generally grow the organization.

Further evaluation is carried out at the end of each training to test the impact of the training on employee skills, and test for improvement.

Here, the subject is the employee, while the treatment is the training conducted. This is a pretest-posttest control group experimental research example. Let us consider an academic institution that wants to evaluate the teaching method of 2 teachers to determine which is best. Imagine a case whereby the students assigned to each teacher is carefully selected probably due to personal request by parents or due to stubbornness and smartness.

This is a no equivalent group design example because the samples are not equal. By evaluating the effectiveness of each teacher's teaching method this way, we may conclude after a post-test has been carried out.

However, this may be influenced by factors like the natural sweetness of a student. For example, a very smart student will grab more easily than his or her peers irrespective of the method of teaching.

Experimental research contains dependent, independent and extraneous variables. The dependent variables are the variables being treated or manipulated and are sometimes called the subject of the research. The independent variables are the experimental treatment being exerted on the dependent variables. Extraneous variables, on the other hand, are other factors affecting the experiment that may also contribute to the change. The setting is where the experiment is carried out.

Many experiments are carried out in the laboratory, where control can be exerted on the extraneous variables, thereby eliminating them. Other experiments are carried out in a less controllable setting. The choice of setting used in research depends on the nature of the experiment being carried out. Experimental research may include multiple independent variables, e. Experimental research design can be majorly used in physical sciences, social sciences, education, and psychology.

It is used to make predictions and draw conclusions on a subject matter. Some uses of experimental research design are highlighted below. The changes observed during this period are recorded and evaluated to determine its effectiveness. This process can be carried out using different experimental research methods. The other person is placed in a room with a few other people, enjoying human interaction.

There will be a difference in their behaviour at the end of the experiment. For example, when finding it difficult to choose how to position a button or feature on the app interface, a random sample of product testers are allowed to test the 2 samples and how the button positioning influences the user interaction is recorded. Data collection methods in experimental research are the different ways in which data can be collected for experimental research. They are used in different cases, depending on the type of research being carried out.

This type of study is carried out over a long period. It measures and observes the variables of interest without changing existing conditions.

When researching the effect of social interaction on human behavior, the subjects who are placed in 2 different environments are observed throughout the research. No matter the kind of absurd behavior that is exhibited by the subject during this period, its condition will not be changed.

This may be a very risky thing to do in medical cases because it may lead to death or worse medical conditions. This procedure uses mathematical, physical, or computer models to replicate a real-life process or situation. It is frequently used when the actual situation is too expensive, dangerous, or impractical to replicate in real life.

This method is commonly used in engineering and operational research for learning purposes and sometimes as a tool to estimate possible outcomes of real research. Not all kinds of experimental research can be carried out using simulation as a data collection tool. The primary disad vantage of within-subjects designs is that they can result in carryover effects. One type of carryover effect is a practice effect , where participants perform a task better in later conditions because they have had a chance to practice it.

Another type is a fatigue effect , where participants perform a task worse in later conditions because they become tired or bored.

Being tested in one condition can also change how participants perceive stimuli or interpret their task in later conditions. This type of effect is called a context effect. For example, an average-looking defendant might be judged more harshly when participants have just judged an attractive defendant than when they have just judged an unattractive defendant.

Within-subjects experiments also make it easier for participants to guess the hypothesis. For example, a participant who is asked to judge the guilt of an attractive defendant and then is asked to judge the guilt of an unattractive defendant is likely to guess that the hypothesis is that defendant attractiveness affects judgments of guilt. This knowledge could lead the participant to judge the unattractive defendant more harshly because he thinks this is what he is expected to do.

Carryover effects can be interesting in their own right. Does the attractiveness of one person depend on the attractiveness of other people that we have seen recently?

But when they are not the focus of the research, carryover effects can be problematic. Imagine, for example, that participants judge the guilt of an attractive defendant and then judge the guilt of an unattractive defendant.

If they judge the unattractive defendant more harshly, this might be because of his unattractiveness. But it could be instead that they judge him more harshly because they are becoming bored or tired. In other words, the order of the conditions is a confounding variable.

The attractive condition is always the first condition and the unattractive condition the second. Thus any difference between the conditions in terms of the dependent variable could be caused by the order of the conditions and not the independent variable itself.

There is a solution to the problem of order effects, however, that can be used in many situations. It is counterbalancing , which means testing different participants in different orders.

For example, some participants would be tested in the attractive defendant condition followed by the unattractive defendant condition, and others would be tested in the unattractive condition followed by the attractive condition. With counterbalancing, participants are assigned to orders randomly, using the techniques we have already discussed. Thus random assignment plays an important role in within-subjects designs just as in between-subjects designs.

Here, instead of randomly assigning to conditions, they are randomly assigned to different orders of conditions. In fact, it can safely be said that if a study does not involve random assignment in one form or another, it is not an experiment. An efficient way of counterbalancing is through a Latin square design which randomizes through having equal rows and columns. For example, if you have four treatments, you must have four versions. Like a Sudoku puzzle, no treatment can repeat in a row or column.

For four versions of four treatments, the Latin square design would look like:. There are two ways to think about what counterbalancing accomplishes. One is that it controls the order of conditions so that it is no longer a confounding variable.

Instead of the attractive condition always being first and the unattractive condition always being second, the attractive condition comes first for some participants and second for others. Likewise, the unattractive condition comes first for some participants and second for others.

Thus any overall difference in the dependent variable between the two conditions cannot have been caused by the order of conditions. A second way to think about what counterbalancing accomplishes is that if there are carryover effects, it makes it possible to detect them. One can analyze the data separately for each order to see whether it had an effect.

Researcher Michael Birnbaum has argued that the lack of context provided by between-subjects designs is often a bigger problem than the context effects created by within-subjects designs. One group of participants were asked to rate the number 9 and another group was asked to rate the number Birnbaum, [4]. Participants in this between-subjects design gave the number 9 a mean rating of 5. In other words, they rated 9 as larger than ! According to Birnbaum, this difference is because participants spontaneously compared 9 with other one-digit numbers in which case it is relatively large and compared with other three-digit numbers in which case it is relatively small.

So far, we have discussed an approach to within-subjects designs in which participants are tested in one condition at a time. There is another approach, however, that is often used when participants make multiple responses in each condition. Imagine, for example, that participants judge the guilt of 10 attractive defendants and 10 unattractive defendants.

Instead of having people make judgments about all 10 defendants of one type followed by all 10 defendants of the other type, the researcher could present all 20 defendants in a sequence that mixed the two types.

Or imagine an experiment designed to see whether people with social anxiety disorder remember negative adjectives e. The researcher could have participants study a single list that includes both kinds of words and then have them try to recall as many words as possible.

The researcher could then count the number of each type of word that was recalled. There are many ways to determine the order in which the stimuli are presented, but one common way is to generate a different random order for each participant. Almost every experiment can be conducted using either a between-subjects design or a within-subjects design.

This possibility means that researchers must choose between the two approaches based on their relative merits for the particular situation. Between-subjects experiments have the advantage of being conceptually simpler and requiring less testing time per participant. They also avoid carryover effects without the need for counterbalancing.

Within-subjects experiments have the advantage of controlling extraneous participant variables, which generally reduces noise in the data and makes it easier to detect a relationship between the independent and dependent variables. A good rule of thumb, then, is that if it is possible to conduct a within-subjects experiment with proper counterbalancing in the time that is available per participant—and you have no serious concerns about carryover effects—this design is probably the best option.

If a within-subjects design would be difficult or impossible to carry out, then you should consider a between-subjects design instead.

A within-subjects design with counterbalancing would require testing some participants in the treatment condition first and then in a control condition. Clearly, a between-subjects design would be necessary here. Remember also that using one type of design does not preclude using the other type in a different study. The sample would split into two groups experimental A and control B.

Although order effects occur for each participant, because they occur equally in both groups, they balance each other out in the results. A matched pairs design is an experimentl design where pairs of participants are matched in terms of key variables, such as age or socioeconomic status.

One member of each pair is then placed into the experimental group and the other member into the control group. One member of each matched pair must be randomly assigned to the experimental group and the other to the control group. Matched pairs : Each condition uses different participants, but they are matched in terms of important characteristics, e.

Read about each of the experiments below. For each experiment, identify 1 which experimental design was used; and 2 why the researcher might have used that design. In order to compare the effectiveness of two different types of therapy for depression, depressed patients were assigned to receive either cognitive therapy or behavior therapy for a week period.

The researchers attempted to ensure that the patients in the two groups had a similar severity of depressed symptoms by administering a standardized test of depression to each participant, then pairing them according to the severity of their symptoms.

To assess the difference in reading comprehension between 7 and 9-year-olds, a researcher recruited a group of each from a local primary school. They were given the same passage of text to read, and then asked a series of questions to assess their understanding. To assess the effectiveness of two different ways of teaching reading, a group of 5-year-olds were recruited from a primary school.

Their level of reading ability was assessed, and then they were taught using scheme one for 20 weeks. At the end of this period, their reading was reassessed, and a reading improvement score was calculated. They were then taught using scheme two for a further 20 weeks and another reading improvement score for this period was calculated. The reading improvement scores for each child were then compared.

In order to assess the effect of organization on recall, a researcher randomly assigned student volunteers to two conditions. Condition one attempted to recall a list of words that were organized into meaningful categories; condition two attempted to recall the same words, randomly grouped on the page.

These are the ways that the experimenter can accidentally influence the participant through their appearance or behavior. The clues in an experiment that lead the participants to think they know what the researcher is looking for e.