1. Dr. Erica Cirillo-McCarthy Assistant Director of Graduate and ADEP Writing The California Lutheran University Writing Center

2.  Brief overview of the writing process  Components of Introduction section  Components of Data Analysis: Description, Validity, Discussion, and Conclusion

3.  Inventing  Drafting  Revising  Editing In between all of these stages, you return again and again to the sources, to the research, to the theories, to the beginning, middle, and end

4.  When reviewing results, consider the following: ◦ Significance of results ◦ Generalizability of the research (limitations) ◦ Reliability ◦ Validity

5.  Free write a narrative regarding what brought you to this research ◦ Why are you interested in this research? ◦ What personal connections do you have to this method, the participants, the location, the problem?  Free write what you would like to see done with this research ◦ Consider audience – for whom is this research conducted? ◦ Who would use this research? In what way? ◦ Who are the key stake holders? ◦ What end result do you envision for this research, i.e. new policy implementation? ◦ What is the next step in this research, i.e., broader population or multiple sites?

6.  Brief overview of the context behind the study  Ask yourself: what was the problem that led you to this research?  That same question could be the big “Why?” Why did you decide as a researcher to look at this phenomenon, case, comparison?  Go back to the funnel process: start general, then move to more specific  Write this section last

7.  Contextualize data production (where, how, who, what, why)  Talk about the end of data – what was used and what was kept out and why  How were the findings produced? ◦ Consider themes and concepts – how were they derived? ◦ Show evidence of thinking – what led to what? How were the connections uncovered? Rule of thumb for description: readers should have enough information to be able to recreate data collection

8.  Some questions to consider when analyzing qualitative data in regards to validity: ◦ How well does this analysis explain why people behave in the way that they do? ◦ How comprehensive would this explanation be to a thoughtful participant? ◦ How well does the data cohere with what we already know?

9.  Clarity is most important  Consider this reason behind the methods section: so that others can replicate your study  The slow process of your research should be clearly described in this section  If you use a specific methodology (ethnography, case study, action research) then make that clear and refer to the experts in that methodology (Geertz for ethnography, Stake for case studies)  Finally, JUSTIFY your methods – why this method and not another?

10. Contextualize the research  Look back: ◦ Where does this research fit into the larger conversation? ◦ What is new or different from previous work? ◦ Look at similarities/differences in data, methods, location, theoretical grounding  Look forward: ◦ What are the implications of this study? ◦ Is it transferable? ◦ What are the weaknesses and limitations?

11.  Summarize results  Bring in validity  Look ahead – what is the next step in research  Reiterate key stake holders and potential of results

12.  Anderson, Claire. “Presenting and Evaluating Qualitative Research.” American Journal of Pharmaceutical Education 74.8 (2010): 141-145.  “Purdue OWL.” Purdue University. Accessed 11/1/12. http://www.owl.purdue.english.edu