Explain the coding process.

Week 5 – Assignment: Develop a Teaching Resource for Qualitative Data Analysis
Instructions
As you read through the set of reflexive questions that are provided this week, you will see that these questions are designed to serve as prompts for journaling throughout the dissertation process. These questions will help you think more critically and reflectively about the process of analysis in general, and more specifically about your role as a qualitative researcher. As you read these prompts, think carefully about all of the actions you might take in the analytic process and the implications thereof. As you read through these lists of reflexive questions, give deep thought to those that seem significant to you; you may also want to note some of your responses in your research journal.
This week, you are asked to switch roles and imagine you are a dissertation instructor. You have been assigned the task of explaining to your graduate students how to go about analyzing, evaluating, and presenting their research data. To do this, you will create a PowerPoint presentation.
In your presentation, explain the process of qualitative data analysis. For each slide, include applicable speaker notes, which can be in the form of brief paragraphs or bulleted lists. Remember, as you are creating this presentation that it is important to keep in the forefront of your mind what new learning you want your students to come away with; that is, what you want them to know, understand, recognize, and acknowledge. As you think about this, you may want to brainstorm and jot down some ideas in your research journal.
This assignment can be completed by following these guided steps:
Slides 1-5: Explain the coding process. Refer to the relevant literature, and include citations as needed. Make sure that you mention all of the key elements that you have learned about data analysis in this course thus far.
Slide 6: Provide a coding example for instructional purposes. To do this, you will engage in a rather fun activity by developing and compiling a mock coding scheme to illustrate how the coding process takes place. Here is one example of how this is done: Have you seen when you order coffee the person taking your order usually writes your name and a few other letters on the paper cup? For example, you may notice the following letters on your cup (descriptions for each are provided in parentheses):
• CB Sk (cold brew skim milk)
• CB Oat (cold brew oat milk)
• MOC FRAP LI (mocha frappucino light ice)
• CB H/H (cold brew half/half)
• L S/M (latte skim milk)
• S F/C (Small, full cream milk)
• CB LI -PM (cold brew light ice leave place for milk)
• DR 2SH/EXP (dark roast with 2 shots of espresso)
• XMAS-NS-NC (Christmas blend, no sugar, no cream)
What the person taking your order is actually doing is providing a code of your order for the barista who is making the drink. The code is essentially a short-hand version of what drink you have ordered. You can use this same concept to explain the coding process to your students. To illustrate the coding process, choose one of the following coding scenarios or metaphors and develop 12-15 applicable codes to create your mock coding scheme:
• Taking inventory in a toy store
• Selecting plants to be delivered to the botanical garden
• Taking inventory at a used car lot
• Packing a suitcase for a beach holiday
• Packing a suitcase for an Antarctic trek
Slides 7-10: Explain the process of evaluating and presenting research findings. Refer to the relevant literature from Weeks 1-4, and include citations as needed.
Slides 12 -14: Here you will be providing your reflections on the analytic process that you have conducted. You will need to choose to respond to at least four reflective questions from the textbook.
• Reflective questions, pp. 258-259. Address two questions of your choice (1-2 slides)
• Reflective questions, pp. 293-294. Address two questions of your choice (1-2 slides)
Slide 15: Provide a final reference slide.
Length: 15 slides with relevant speaker notes for each slide
References: Minimum of 4 scholarly sources to explain the coding process (Slides 1-5) and a minimum of 4 scholarly sources to explain the process of evaluating and presenting research findings (Slides 7-10)
Your presentation should demonstrate thoughtful consideration of the ideas and concepts presented in the course and provide new thoughts and insights relating directly to this topic. Your response should reflect scholarly writing and current APA standards. Be sure to adhere to Northcentral University’s Academic Integrity Policy.

Here is page 258-259

“Reflexive Questions for Chapter 4: Analyzing Data and Reporting Findings

What am I hoping to convey with my findings?
What shapes my research agenda?
Who is the audience I am writing for?
Why? How does my intended audience shape my sense regarding the structure and write-up of the findings?
Are there other potential audiences that could benefit from my learning and knowledge?
What are these other audiences?
How and in what ways might they benefit from this knowledge?
How might I structure my writing to fit the needs of other audiences?
How do I, as the researcher and author, represent myself in the narrative?
Why? What forms of authority do I use to make my case?
What mediates these choices?
Has my representation of the site/setting, research participants, and participants’ experiences accurately, ethically, and with integrity portrayed the lived experiences of those involved in this research?
Whose voice(s) will be privileged in this study, and whose voice(s) may be silenced?
Why? Who is heard in my writing, and why?
Who is not heard, and why?
How do I bring in participants’ voices?
What informs these choices?
What choices do I make about how I portray the participants and their experiences?
Why? How will these choices influence the way(s) I include (or exclude) data?
Have I provided sufficient information for readers to understand the contextual factors at play, and therefore better understand the findings of my study “in context”?
How will I structure the report so that data are meaningfully contextualized and do not appear “out of context”?
In writing up my study’s findings, have I fully respected participants (without judgment) and attempted to the best of my ability to do justice to their lived experiences?
Is there a possibility that readers could identify participants?
What are the risks to confidentiality? How and in what ways can I address these concerns to ensure that all ethical principles are upheld?
If my research participants were reading my study, how would they feel?
Would my findings and the way I have represented the site/setting and the participants themselves resonate with them?
Will my writing be accessible to the participants?
Why or why not?
Do participants have a say in how they are represented?
Should they?
Why or why not?
In what ways could I collaborate with research participants by including them in some of the choices pertaining to voice and/or language?
What might be possible challenges or benefits to this?
Have I carefully attended to participants’ language, culture, contexts, and perspectives?
Have I taken into account that these may be different from my own?Am I clear about the role of sociopolitical realities (historical and current), and how these realities impact the study’s findings and the way that I report these?
How, if at all, do I deal with and represent power asymmetries, including the researcher–participant relationship, and possible implications?
Have I engaged in dialogue and collaboration with colleagues or “thought partners” regarding the way I have presented the study’s findings, including researcher identity, power differentials, and positionality?
If not, why? If so, how have I responded to questions or concerns? Am I receptive to critical feedback?
Chapter Summary Discussion
Qualitative data analysis is an attempt to summarize the data collected from multiple data sources in a dependable and accurate manner. When analyzing qualitative data, you need to challenge yourself to explore every possible angle to find patterns and relationships among the data. The amount of data that need to be transcribed, organized, and reduced can indeed be overwhelming. This chapter explains how to go about organizing and preparing the data for analysis and includes discussion around data reduction and data display. Organizing, preparing, and presenting the findings of your research is, as described in this chapter, a somewhat objective exercise; the researcher is, in this instance, a reporter of information.
Although the mechanics of data analysis vary greatly and are undertaken differently depending on genre and theoretical framework, some general guidelines can be useful. Although the guidelines we provide describe the analytic process as if it were a series of separate sequential steps, it must be remembered that qualitative data analysis is an interactive and recursive process rather than a linear one. The steps are repeated several times until the researcher feels that there has been sufficient immersion in the data, that sufficient information has been extracted from the data, and that the research questions have been adequately addressed. It is important to recognize that in qualitative research, data collection and data analysis are intimately interconnected processes. Having said that, our view is that for purposes of a dissertation, although it might seem a little contrived, it is most effective to present the findings (an objective exercise) and the analysis of those findings (a subjective exercise) as two separate chapters. (Note that some universities may require that these chapters are combined, thereby producing a five-chapter dissertation.)
Qualitative research is typically reported in a narrative manner. Although the overall intent is not to quantify qualitative data, tallies and frequencies in qualitative research are essentially a supplement to the narrative. Essentially, you are forming a record of frequently occurring phenomena or patterns of behavior. Once you have established patterns, these need to be explained. You have to consult the literature and consider your pattern findings in light of previous research and existing theory. Do your findings confirm similar research? Do they contradict previous studies? How can you explain these differences or similarities? As you begin to consider answers to these sorts of questions and provide convincing explanations, you are interpreting and synthesizing. This is the stuff o”

p.293-294

“Reflexive Questions for Chapter 5: Analyzing and Interpreting Findings
What assumptions do I bring to this study?
What assumptions of mine continue to impact analysis of the study’s findings?
How, if at all, have I described the ways in which my biases or assumptions may have affected my analysis and interpretation of the findings?
Did any conflicts of interest impair or impact the way I approached the participants and/or the data?
Have participants provided sufficient information for me to make plausible interpretations?
Do I have sufficient knowledge of participants’ worlds to read their words and really understand these?
Do I provide sufficient social context on which to base my analysis and interpretation?
How and in what ways might I be misinterpreting the findings?
Have I challenged my interpretations? How might I do so more vigorously?
Have I understood and addressed all patterns and themes I see in the data?
Might I have omitted anything?
How do I understand my role in the creation of data so that the arguments I make are credible and authentic?
Have I addressed issues of interpretive authority—that is, the power of the researcher to be the translator and interpreter of the lived experiences and perspectives of others?
Have I made an effort to acknowledge the possibility thereof and, to the extent possible, challenge and resist its imposition?
In my analysis and interpretation, have I fully respected participants and attempted to the best of my ability to do justice to their lived experiences?
If my research participants were reading my study, how would they feel? Would my analysis and interpretation resonate with them?
How did early data analysis inform subsequent data analysis?
In what ways, if at all, did that shape or inform the findings?
To what extent do I allow theory to inform (frame and/or challenge) analysis and interpretation?
Have I sought out and engaged with disconfirming evidence to provide alternative perspectives, even though these may be surprising, unexpected, or even uncomfortable?
In what way(s) did I seek disconfirming evidence?
How can I do more of this?
Have I made any assumptions or generalizations beyond the scope of the data?
Am I making interpretive arguments that are grounded in my data, or are these arguments an inferential leap, or both?
What is the role of each of the research participants themselves in shaping the research and challenging my interpretations?
Am I providing this opportunity to them?
If so, how, and in what ways? If not, why?
Have I engaged in dialogue and collaboration with colleagues or “thought partners” regarding my data and the potential impact on data interpretation including researcher identity, power differentials, and positionality?
Am I receptive to critical feedback regarding my interpretations?
Have I taken all necessary precautions to respect research participants and the research site and to preserve anonymity?
Can any harm befall the site/setting and/or research participants at any point, now or in the future, as a result of my analysis or interpretation?
What immediate or future risk might occur by disseminating research material in published reports?
Chapter Summary Discussion
As pointed out previously, analysis of data begins to occur before you can present your findings; by coding and sorting, you are in effect analyzing your raw data. Having organized and prepared mounds of raw data so you could present an accurate and objective account of the findings of your research (as addressed in Chapter 9), you are now ready to move on to the final step of the analytic process: to provide an interpretation and synthesis of those findings. Both in the previous chapter and in this one, we emphasized the distinction between reporting and presenting findings and interpreting them. These are two distinct processes.
We have covered some difficult ground in this chapter. Qualitative analysis is a complex task and is therefore not simple to explain. Because the concepts of analysis, interpretation, and synthesis are difficult to explicitly articulate, thinking about how to compose a chapter describing these processes is somewhat challenging. Therefore, the suggestions we have made in this chapter should be viewed more in the nature of guides to possible approaches and combinations of approaches rather than as tight prescriptions. You should also be sure to check with your advisor regarding specific school or programmatic requirements in this regard.
In the previous chapter, you presented the analysis of your raw data, which were your findings. In this chapter, you presented the analysis, interpretation, and synthesis of your findings. You moved beyond data to information. In the findings chapter, you stood back and remained objective, to the extent possible. Your task was to offer an accurate account of the findings. In the analysis chapter, you moved from the objective to the subjective. Your voice and opinion, in conjunction with the literature, now take center stage. Findings cannot be taken at face value. Your aim in writing the analysis chapter is to tell a richly detailed story that takes into account a specific context that connects participants, processes, activities, and experiences to larger issues or phenomena. This chapter is essentially a well-thought-out conversation that integrates your findings with the literature, previous research, and practice.
First, you seek to identify significant patterns or themes. Then you move on to provide some sense of understanding; that is, you attempt to explain these patterns and themes—possibly the most creative part of the dissertation. Findings need careful teasing out. As a researcher, you must ask yourself what you have learned from conducting the research and studying the findings. What connective threads are there among the experiences of your study’s participants? How do you understand and explain these connections? What new insights and understanding do you have as a result of conducting your study? What surprises have there been? What confirmation of previous instincts and hunches has there been? Are your findings consistent with the literature? Have they perhaps gone beyond the literature? If so, how and in what ways? The answers to these questions add another dimension of understanding to your findings.
Bear in mind that analytical approaches are linked to particular forms of data collection and are underpinned by specific conceptual and philosophical traditions. And just as methodological congruence implies that there are clear analytic distinctions among qualitative traditions or genres, demanding that the researcher think about data analysis in a particular way, so are interpretation and representation strategies specific to each tradition. As such, each tradition provides a perspective on reality that is specific to that tradition, and so the way you go about developing themes and presenting interpretations is aligned with your chosen qualitative genre or tradition.
Providing careful step-by-step documentation of your analysis offers other researchers access to your procedures, thereby addressing the trustworthiness of your study. In this way, your study can become a model for other studies—a contribution to the research community and an implicit affirmation of the value of your work. Readers of dissertations also are drawn to visual representations of information, which typically compare and contrast key findings of the study. Displaying data visually makes things clear and also can facilitate your seeing findings in new and striking ways.
The central requirement in qualitative analysis and interpretation is clear and logical thinking. You need to examine your findings critically so as to produce credible and meaningful interpretations. Interpretation of qualitative data precludes reducing the task to any single defined formula or fixed blueprint. Moreover, we must appreciate that, in dealing with interpretation, we are unavoidably dealing with human subjectivity, and, as such, there are differences in the ways we make meaning. Be sure to acknowledge that there are multiple ways of interpreting findings, that you have sought rival explanations, and that your interpretations are but one perspective. The human as instrument in qualitative inquiry is both its greatest strength and its greatest weakness. Nowhere does this ring more true than in analysis and interpretation”