Critical Behavior In Research

Princess Gunthrope

University of Phoenix

In research it is very important to adhere to ethical norms, these values ensure the proper and initial aim of research is carried out. The law of ethics in research prohibit researchers from falsifying information or misrepresenting information to participants. Often times “research involves a great deal of cooperation and coordination among many different people in different disciplines and institutions, ethical standards promote the values that are essential to collaborative work, such as trust, accountability, mutual respect, and fairness”(Sent, 2003). The critical behavior in research analysis will analyze an ethical issue raised in the article, The Causal Generalization Paradox: The Case of Treatment Outcome Research, written by Graham L. Staines. The article by Staines discusses the causal generalization paradox. The ethical issue at the heart of the article is the use of improper sampling procedures. With the vast amount of research taking place and random assignment techniques, less of a priority is being placed upon random sampling. According to Staines,2008 experimental research typically selects units, in part or in whole, at the convenience of the researcher. The researcher then makes no attempt, or often times only a limited attempt, to ensure that this sample is an accurate representation of some larger group or population. This form of convenience sampling is an ethical issue simply because experimental data based upon the use of “convenience samples rather than probability based samples, there is almost never a formal justification, or set of rigorous guidelines, for generalizing the study’s findings to other populations” (Staines, 2008).

The generalization paradox and improper sampling procedures may often cause researchers to make misleading or over simplified assumptions. If this issue is not properly addressed by the researcher the question of whether the data is applicable to different circumstances and participants may be raised. “Unless the experimental results have some generality (or robustness), they contribute little to scientific knowledge” (Staines, 2008). The use of convenience sampling does not allow formal justification of data nor does it allow the ability to generalize to other populations. As Shadish et al. (2002, p. 18) explained, causal generality, although a serious problem in all research, is the Achilles heel of experimentation: “The strength of experimentation is its ability to illuminate causal inference. The weakness of experimentation is doubt about the extent to which that causal relationship generalizes”. By maximizing internal validity casual generality if often neglected. The fallibility of researchers’ predictions is thus an inherent component of causal generalizations (Matt, 2003). The generalization paradox and the utilization of improper sampling procedures are relevant to researchers in the field of education because any improper use of sampling may distort data results. There are many different types of research that may contribute to the laws, procedures, and educational initiatives. If the population the researcher is aiming to study is improperly sampled the researcher generalizations will not be aimed at the proper population. The data findings will be less significant and will not clearly indicate the researcher’s goal.
Researchers in the field of education utilize observation techniques designed to show good consistency in the data collection process. Convenience sampling is not often used as a sampling technique in an effort to decrease generalization and bias.

As a researcher I plan to prepare a sampling strategy prior to conducting research, I will outline the pros and cons of each method in an effort to understand how each method will affect my data. According to Christensen, Johnson and Turner (2010) the sampling method is important if the researcher intends to “generalize directly to a population based on his or her single research study results” (p. 149). In terms of convenience sampling, I will make a conscious effort to stay away from sampling methods that are the easiest to obtain, as I realize this may not always be the most effective method.

References

Christensen, L.B., Johnson, R.B., & Turner, L.A. (2010). Research methods, design and analysis (11th ed.). Boston, MA: Allyn & Bacon.
Matt, G. E. (2003). Will it work in Munster? Meta analysis and the empirical generalization of

causal relationships. In H. Holling, V. Bo¨ hning, & R. Schulze (Eds.), Meta-analysis (pp.

113–139). Berlin: Springer.

Sent, E. (2003). Thomas Kuhn: the wrong person at the right place at the right time. Social

Epistemology, 17(2/3), 291-292. Retrieved from EBSCOhost. Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental

design for generalized causal inference. Boston: Houghton Mifflin.

Staines, G. L. (2008). The causal generalization paradox: The case of treatment outcome

research. Review of General Psychology, 12(3), 236-252. doi:10.1037/1089-

2680.12.3.236