research in education qualitative quantitative

Quantitative vs. Qualitative Research According to Lopez-Alvarado (2017) and Muijs (n.d.), research design decisions are linked to ontology and epistemology. Ontology refers to the researcher’s beliefs about whether reality is absolute or contextual, universal or relative. Whether the researcher is a realist or a relativist determines research questions and designs, with an increased tendency for relativists to focus on phenomenological and qualitative methods and a realist to use quantitative methods.

Muijs (n.d.) describes quantitative research as using numerical data and mathematical methods, showing how a realist will use these types of methods to seek for an objective truth. Likewise, epistemology refers to how the researcher acquires knowledge, or what sources of knowledge are deemed valid. A researcher who believes in absolutism and realism will veer towards quantitative methods, which yield absolute and generalizable results. On the other hand, a researcher who values subjectivity would take a phenomenological and qualitative approach.

Lopez-Alvarado (2017) describes how culture and other contextual variables may have a strong bearing on a researcher’s ontological orientation. Muijs (n.d.) also points out that it is rare for a researcher to be fully positivist or fully subjectivist, for the extremes of these two ontological frameworks are problematic. Ideally, researchers use a research design that is appropriate for answering the specific research questions or for achieving specific goals with the research. For instance, quantitative research yields numerical results and can be used to test hypotheses.

Qualitative research is best for uncovering meaning to problems or solutions to complex problems that cannot be reasonably simplified into just a few testable variables. Experimental vs. Quasi-Experimental Design Both experimental and quasi-experimental designs are used in quantitative research. The main difference between experimental and quasi-experimental designs is that the latter does not use random assignment to control and experimental groups. With a quasi-experimental design, the control group is called the comparison group (Muijs, n.d., p. 27).

To ensure validity and reliability, the researcher must ensure that population characteristics are as similar as possible between to the two groups to avoid problems with mitigating variables. For example, if a researcher wanted to test the effects of a gifted program on standardized achievement test scores, the comparison group would need to be of the same age, grade, and also with similar pre-test scores. When possible, the researcher also ensures that demographics are similarly distributed among the comparison and experimental groups.

When studying the efficacy of dual-credit programs, a quasi-experimental research design would be most suitable because it would be impossible to ethically assign students randomly to one or the other group. Instead, the researcher needs to study students who are already enrolled in a specific program and make sure that the experimental and comparison groups are as similar as possible. Question 2 on page 33 of the Muijs text refers to the difference between causation and correlation—one of the most fundamental issues in empirical research.

When interpreting the results of a study it is critical to avoid assuming causation; causation is actually difficult to prove and requires the use of strict random assignment, tight controls,.