This section should hook the reader. My preference is that the student should use statistical data or a scholarly story (a story that can be traced to a reputable article or magazine or news or …). The student must show how because of the statistics there is need to do the research.

A problem is the difference between the actual and the desired (Sekaran & Bougie, 2016). I like to see students write about the desired, and then show how there is a gap between the actual and the desired. They then state the problem in such a way that no one can doubt that this is a problem. This section should end with the student showing that the research is set up to address this problem.

A purpose statement is not merely about writing a purpose. The elements of a purpose statement should be the following: the problem, the research design, research strategy, the method of data collection, the method of data collection, the variables, and the reasons for choosing the design (Creswell, 2014).

Questions should be derived from a well formulated theoretical framework (Marshall & Rossman, 2011). This section must have researchable questions, not merely a set of questions that have no link to any theoretical framework.

In this section of the paper discuss the theoretical framework you designed. Take each variable and explain how they interact and iterate to cause or solve the problem being studied (Sekaran & Bougie, 2016; Lee & Lings, 2008).

Based on the theoretical framework designed, formulate hypothesis or hypotheses for the research. Remember that hypotheses are intelligent conjectures that need to be accepted or rejected based on findings from inferential statistical analyses (Strauss & Corbin, 2014).

This section must show that the research is important (Marshall & Rossman, 2011). To show that a study is important, it must demonstrate it has filled gaps in literature, gaps in methodology, and gaps in theory. It should also be shown that the study affects other areas of knowledge.

All terms contained in topic must be defined. Definitions must be scholarly; they must be extracted from journal articles and books (Creswell, 2014; Cooper & Schindler, 2011). They are to be critiqued, not merely written down. The preferred definition must be shown.

Research must be done ethically (Walton, 2017; Todd, et al., 2017; Eriksen, 2016). This section of the paper is to show that the research proposed will be done in an ethical manner. Human subjects will not be involved without their consent. The risks of the research must be clearly shown to them. The researcher must be able to say how risks will be reduced.

Delimitations are demographic and other boundaries of the research (Cristina-Elena, 2017; Nitescu & Dobre-Baron, O, 2017). Criteria for inclusion and criteria for exclusion must be given.

All the constraints of the research must be shown including time, financial constraints, and other constraints or problems associated with the research.

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Is it post-positivism, or constructivism, or advocacy, or pragmatism (Creswell, 2014; Bisel & Adame, 2017). The chosen worldview must be explained, and the reason for choosing it must be carefully articulated.

A research design that is aligned to the chosen worldview is given (Creswell, 2014 (Bornstein, 2017)). The chosen design is explained, and the reason for the choice given.

Table 1: Table explaining the relationship between research worldview, design, strategy, method of data collection and analysis.

See figure 1. A strategy must be chosen that aligns with the research worldview, and the research design. The strategy chosen must be explained, and the reason for the choice given.

See figure 1. A data collection method that aligns with the research worldview, the research design, and the research strategy must be given. The chosen method of data collection must be explained. The reason for choosing this method of data collection must be defended.

See figure 1. A method of data analysis that aligns with the research worldview, the research design, the research strategy, and the method of data collection must be given. The chosen method of data analysis must be explained and defended.

The population must be explained. Who are they? Their demographic boundaries must be properly explained as well. The reason for choosing this population must also be shared. Are there some peculiarities about them that must be discussed? Are they too large for this research?

If they are too large, then a sample must be chosen. How the sample was chosen should be discussed. Validity and reliability must be supported.

Bisel, R. S., & Adame, E. A. (2017). Post-Positivist/Functionalist Approaches. In University of California, & Arizona State University, The International Encyclopedia of Organizational Communication (pp. 1-22). Hopoken, NJ: Wiley.