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Scholar practitioner's guide to research design

25/03/2021 Client: saad24vbs Deadline: 2 Day

Discussion 3:

Evaluating Research Questions, Hypotheses, and Quantitative Research Designs

With a clear purpose in place, quantitative researchers have a roadmap for crafting their research questions and hypotheses that will further focus the approach they will take to investigate their topic (i.e., their study’s research design).

The selection of a research design is guided by the study’s purpose and research questions and hypotheses, and the design then links the research questions and hypotheses to the data that will be collected. You should keep in mind, however, that the research process is interactive, not necessarily proceeding in a linear fashion from one component to the next. Rather, the writing of research questions could, for example, necessitate adjustments to the study’s purpose statement.

Nevertheless, when presented together, the various components of a research study should align. As you learned last week, alignment means that a research study possesses clear and logical connections among all of its various components.

In addition to considering alignment, when researchers select a research design, they must also consider the ethical implications of their choice, including, for example, what their design selection means for participant recruitment, procedures, and privacy.

For this Discussion, you will evaluate quantitative research questions and hypotheses in assigned journal articles in your discipline and consider the alignment of theory, problem, purpose, research questions and hypotheses, and design.

You will also identify the type of quantitative research design the authors used and explain how it was implemented. You will also complete online training in the protection of human research participants.

Due 06/27/2017 by 5 pm

References

Spencer, M. S., Rosland, A. M., Kieffer, E. C., Sinco, B. R., Valerio, M., Palmisano, G., . . . & Heisler, M. (2011). Effectiveness of a community health worker intervention among African American and Latino adults with type 2 diabetes: A randomized controlled trial. American Journal of Public Health, 101(12), 2253–2260. doi:10.2105/AJPH.2010.300106

Burkholder, G. J., Cox, K. A., & Crawford, L. M. (2016). The scholar-practitioner’s guide to research design. Baltimore, MD: Laureate Publishing.

· Chapter 4, “Quantitative Research Designs”

Babbie, E. (2017). Basics of social research (7th ed.). Boston, MA: Cengage Learning.

· Chapter 5, “Conceptualization, Operationalization, and Measurement”

Purpose Statement Checklist Use the following criteria to evaluate an author’s purpose statement.

Look for indications of the following:

• Does the statement begin with signaling words?

• Does the statement identify the research approach (quantitative, qualitative, or mixed)? • Does the statement clearly state the intent of the study?

• Does the statement mention the participants? • Does the statement mention the research site?

• Is the statement framed in a way that is consistent with the identified problem? If the study is qualitative, does the purpose statement do as follows? •

Focus on a single phenomenon • Use an action verb to convey how learning will take place • Use neutral, non-directional language

• Provide a general definition of the central phenomenon If the study is quantitative, does the purpose statement do as follows?

• Identify the variables under study • Provide a general definition of each key variable • Use words that connect the variables

• Identify a theory If the study is mixed methods, does the purpose statement do as follows? • Discuss the reason(s) for mixing both quantitative and qualitative data

• Include the characteristics of a good qualitative purpose statement (as listed above) Research Theory, Design, and Methods Walden University © 2016 Laureate Education, Inc. Page 2 of 2

• Include the characteristics of a good quantitative purpose statement (as listed above)

• Indicate the specific method of collecting both quantitative and qualitative data

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