Overview of Non-Experimental Research

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Table of Contents

Non-Experimental
Quasi-Experimental
Qualitative
Correlational
References

Non-Experimental

The non-experimental research design was used in the study aimed at examining the stress level in people depending on their planning skills. It fits the criteria for this type of research due to the lack of manipulation of an independent variable, which is making daily lists of things to do, and the measurement of variables as they occur (“Overview of non-experimental research,” n.d.). In other words, researchers did not affect the processes but only observed them.

Quasi-Experimental

An example of quasi-experimental research is a study aimed at evaluating a new method of teaching fractions to third graders. It fits the criteria, such as the manipulation of an independent variable, which is the introduction of an innovative approach and the lack of randomization in selecting participants (“Quasi-experimental research,” n.d.). In this way, there was no actual experiment conducted, and the required degree of validity was ensured through the implementation of new measures.

Qualitative

An example of qualitative research is the study examining the methods of the families of teenage suicide victims cope with these events. It corresponds to the type’s criteria, which are the collection of a small amount of data from the participants through unstructured interviews and the lack of a clear research question (“Qualitative research,” n.d.). Therefore, the use of nonstatistical techniques and the limitations regarding the number of people allow attributing it to this research design.

Correlational

Correlational research design represented by the statistical analysis of variables was used in the study of the interrelation between self-esteem and school achievement. In this case, the applicable criteria were the lack of manipulation of variables and the absence of control over external circumstances (“Overview of non-experimental research,” n.d.). Thus, scholars only collected the data and analyzed them in order to reveal the connection between the indicators.