Qualitative Data Analysis Methods

In planning a qualitative study, the researcher must decide which research participants they will need information from (methods to create a research sample), how to appropriately collect information (data collection methods), and, once they have done that, how they plan to analyze all of the information (data analysis methods).

Analyzing qualitative data is different from analyzing quantitative data. The researcher must read all the information that was gathered (and re-read), and then sort and categorize it. The challenge is to reduce the volume of information, identify significant categories (patterns or themes), and construct a workable framework for communicating the data (Bloomberg & Volpe, 2019). Data analysis in qualitative research is informed by a set of guidelines and clear procedures. The analysis process is typically an iterative and recursive one that falls essentially into the following sequential phases: organizing the data, coding the data, identifying patterns and themes, and then generating categories of “findings.”

Creswell and Poth (2018) explain the process of qualitative data analysis as having two layers. The first layer is the process of coding and theme development. The second layer is to build on this general analysis by using specific procedures advanced for each research design. These procedures take data analysis beyond a generic approach and into a sophisticated and more advanced set of procedures, which Creswell and Poth (2018) explain in their book, including details regarding the similarities and differences among the various research designs.

As with data collection methods you will need to remain cognizant that your method of data analysis is in alignment with your chosen research design. Therefore, once the researcher has determined the preferred data collection method, it is important to choose a specific data analysis method that aligns with the specific research design utilized for the study to make sure that the method of analysis is congruent with the type of data to be gathered (Miles, Huberman, & Saldana, 2014).

Once data have been organized for analysis, then, it will be essential to follow the data analysis protocol aligned with the specific design that you have selected for your study. For example, data analysis for grounded theory will differ in procedure and protocol from data analysis typically used for case study or phenomenology. Thus, in order to achieve alignment among research design and methods, the clarity and rationale for the choice of qualitative data analysis must be thoughtfully articulated. You will be expected to describe in detail your analytic approach and explain clearly how you got from your raw data to your conclusions. This transparency is essential to enhance the overall trustworthiness of your study.

A word on data saturation is necessary here. As Hennink and Kaiser (2019) explain, data saturation refers to the quality and quantity of information in a qualitative research study. Saturation is the point at which no new information or themes are observed in the data. This is a core principle used in qualitative research and is used to determine when there is adequate data from a study to develop a robust and credible understanding of the phenomenon. Saturation is an important concept because it provides an indication of trustworthiness and therefore is often included in criteria to assess the quality of qualitative research. This concept has its origins in the grounded theory approach to qualitative research, where it is used to determine data adequacy for theory development; however, it is also used outside of grounded theory to justify sample sizes for qualitative studies. 

Consider computer-assisted qualitative data analysis (CAQDAS), which has become more prevalent over the last few years, and of which there are various applications. Of importance is that the principles of the analytic process are the same whether one is analyzing data manually or with the assistance of software. However, to remain informed, be aware of the following caveat as pointed out by Bloomberg and Volpe (2019),

Software analytical packages are essentially tools that can make the numerous tasks of the analytic process efficient in many ways, and the software is certainly useful in assembling and locating information. However, be aware that there are some limitations involved with this method. Software cannot interpret the emotional tone that is often critical to understanding the findings, and therefore neglects to take into account the contextual basis of information (p. 250).

Remember, while computer-assisted qualitative data analysis (CAQDAS) is often used, the software cannot interpret your data. Only the researcher can do that!

References

Bloomberg, L. D., & Volpe, M. (2019). Completing your qualitative dissertation: A road map from beginning to end (4th ed.). SAGE 

Carey, K. L., & Stefaniak, J. E. (2018). An exploration of the utility of digital badging in higher education settings. Educational Technology Research and Development, 66(5), 1211-1229.

Creswell, J. W., & Poth, C. N (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). SAGE.

Hennink, M. M., & Kaiser, B. N. (2019) Saturation in qualitative research. SAGE Research Methods.

Miles, M. B., Huberman, A. M., & Saldana, J. (2014). Qualitative data analysis: A methods source book. SAGE.

Weekly Resources and Assignments

Review the resources from the Course Resources link, located in the top navigation bar, to prepare for this week’s assignments. The resources may include textbook reading assignments, journal articles, websites, links to tools or software, videos, handouts, rubrics, etc.

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List of Topics and Sub-Modules for Week 4

Optional Badging Activity #1: Qualitative Principles Set 1Quiz This week, you have the opportunity to complete the first of the two optional, ungraded activities for the chance to earn the Qualitative Methodology badge.Remember that you must complete both the Week 4 and Week 7 activities with a passing score to earn the badge.The activity this week is a quiz. Remember that completion of the quiz is optional, and you are expected to adhere to Northcentral University’s Academic Integrity Policy.You will be able to see the badges you have earned in the My Awards section of NCUOne.If you have questions about concepts, please ask your professor. If you have trouble with accessing or completing the quiz, please contact the Service Desk using the “Support” link located under More on the top navigation bar of the course room.

Week 4 – Assignment: Determine a Method to Analyze Qualitative DataAssignment Due May 22 at 11:59 PMNote: This assignment is the required and graded assignment for Week 4. This assignment is NOT the optional badging activity. Please complete and submit this assignment.With a developing understanding of research designs and data collection methods, you can now begin to understand the concept of qualitative data analysis and select an appropriate data analysis method. This week, you will demonstrate your understanding of qualitative data analysis methods, as well as the appropriate application as prescribed by qualitative research principles. This assignment includes several prompts, and there is an option regarding presentation (essay, set of blog posts, or PowerPoint presentation). As with Week 3, in line with the principles of Andragogy, offering you a presentation choice will accommodate your individual preferences and abilities.This week, you are provided with an explanation of how to structure a presentation (Spotlight on Skills). Remember, slides are visual aids to support what you would say during a presentation. This resource will help you to compose your slides in a way that effectively balances visuals and text. You are also provided with an explanation of how to create a blog entry (Spotlight on Skills). Note that a blog (shortening of “weblog”) is a set of online informational posts, with a writer communicating their views on a subject in a conversational manner. Blogging is typically used for teaching and educational purposes.You have covered a lot of material these past 4 weeks.  Now, you have an opportunity to demonstrate your knowledge of qualitative methodology and designs through a true/false knowledge check. Correctly answering all of these quiz items will earn you a badge!For this week’s assignment, you will consider a data analysis method that aligns with the qualitative research design for a potential study that you proposed in Week 2. Address each of the following four prompts as an essay, series of blog posts, or presentation:

Explain your proposed method of data analysis in detail, and how this method aligns with your chosen research design.

Discuss what you see as the advantages and potential challenges of the proposed method.

Explain how you will code data, by providing examples to illustrate your analysis process. Based on your topic and research design as explored in Week 2, develop a mock coding scheme that includes a preliminary set of start codes. These codes can come from the relevant literature on your topic, or you can come up with some ideas based on your own experience.

Whether you choose to engage in a manual coding process to analyze your research data or to use NVivo (the data analysis software that is available to you through the University), there are some features regarding coding and analysis that are common to both approaches. Explain in what ways you think manual coding and software coding will be similar and/or different? State your preference, explaining the reasons for your choice.