Category: Questionnaire
Evaluating the limitations and importance of quasi experiment to formulate better research questionnaire
21/11/2022
A research questionnaire is just formulating some questions for the research respondents so that you can gather and analyze their responses to know about the research topic. Now, if we do not have the idea to create research questionnaires, then how will we create better research questions? Well, there is a certain type of experiment called “quasi-experiment” that can help us formulate better questions. But is it effective? Does it have any limitations? In this blog, we will identify the limitations and importance of quasi-experiments to formulate better research questionnaires.
Describing quasi-experiment
A quasi-experiment is a type of study that resembles an experimental study but does not meet all of the requirements for a true experiment. In a true experiment, the researcher randomly assigns participants to different groups and manipulates an independent variable to observe its effect on a dependent variable. In a quasi-experiment, the researcher does not have control over the assignment of participants to groups, but still observes the effect of an independent variable on a dependent variable. Quasi-experiments are often used in naturalistic settings where it is not possible or ethical to manipulate the independent variable.
Evaluating the limitations and importance of quasi-experiment to formulate a better research questionnaire
Quasi-experiments are important in formulating research questions because they can be used to investigate causality in situations where true experiments are not feasible. For example, in a quasi-experiment, a researcher might be interested in studying the effect of a new educational program on student achievement. Because it would not be ethical to randomly assign students to either receive or not receive the program, the researcher would instead use existing groups of students who are already participating in the program and compare their achievement to a similar group of students who are not participating. This allows the researcher to draw causal inferences about the program’s effectiveness, despite the lack of random assignment. In addition, Quasi-experiments can also help to build the case for more rigorous, true experiments that can be carried out later.
There are several limitations to using quasi-experiments to formulate research questions. Some of the main limitations include:
1. Selection bias: As participants are not randomly assigned to the experimental and control groups, there may be systematic differences between the groups that could affect the results.
2. Lack of control: Quasi-experiments typically have less control over the conditions of the study than true experiments, which can make it more difficult to isolate the specific factors that are affecting the outcome.
3. Difficult to establish causality: Without random assignment, it can be difficult to establish causality and rule out alternative explanations for the results.
4. Generalizability: Quasi-experiments are often conducted in specific settings or with specific populations, which limits their generalizability to other settings or populations.
5. Confounding variables: Quasi-experiments are more likely to have uncontrolled confounding variables that might affect the outcome.
Quasi-experiments can be a useful research method in certain situations, but it’s important to be aware of their limitations and the potential for bias when interpreting the results.
Finally, we can say that a quasi-experiment is a little different from other experiments as you need to have thorough knowledge about them. If you want us, fivevidya, to help you, then you can simply reach out to us from our website https://www.fivevidya.com/ if you want to learn more about quasi-experiment, you can comment below so that we can provide you with free in-depth blogs on it.
Information about Likert scale in designing survey questionnaire for PhD research
03/09/2020
The Likert Scale( frequently known as agree-disagree scale) was first published by physiologist Rensis Likert in 1932. The technique presents respondents with a series of attitude dimensions ( a battery), for each of which they are asked whether, and how strongly, they agree or disagree, using one of the numbers of the positions on a five-point scale.
With face-to-face interviewer-administered scale batteries, the responses may be shown on a card whilst the interviewer reads out each of the statements in turn. With telephone interviewing, the respondent may sometimes be asked to remember what the response categories are, but preferably be asked to write them down.
The technique is easy for administrators in self-completion questionnaires, either paper or electronic, and may often be given to respondents as a self-completion section in an interviewer-administrator survey.
Responses using a Likert scale can be given scores for each statement, usually from 1 to 5, negative to positive, or -2 to +2. As these are interval data, means and standard deviations can be calculated for each statement.
The full application of the Likert scale is then to sum the scores from each respondent to provide an overall attitudinal score for each individual. Likert’s intention was that the statement would represent different aspects of the same attitude. The overall score, though, is rarely calculated in commercial research (Albaum,1997) where the statement usually covers a range of attitudes. The responses to individual statements are of more interest in determining the specific aspects of attitude that drive behaviour and choice in a market, or summations are made over small groups of items. The data will tend to use in factor analysis, in order to identify the groups of attitudinal dimensions, data are then often used in various forms of cluster or segmentation analyses, in order to segment data into groups of respondents with similar attitudes.
There are four interrelated issues that questionnaires writers must be aware of when using Likert scales :
Order effect
Acquiescence
Central tendency
Pattern answering
