Analyzing qualitative data 4 13-17
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This document provides guidance on analyzing qualitative research data through coding. It discusses the importance of conceptualizing chunks of text with labels called concepts. Concepts that are similar can be grouped into categories to develop explanatory terms. The researcher engages in an iterative process of constantly comparing concepts to categories to develop theories grounded in the data. Memos tracking the researcher's analysis, interpretations and questions are also important. The goal is to allow patterns and insights to emerge from careful examination of qualitative data like interview transcripts and observations.
Analyzing qualitative data 4 13-17
- 1. Analyzing and Coding Qualitative Research Basics of Qualitative Research (3rd ed.) Strauss, A. & Corbin, J. (2007) ADLT 673, Session 10
- 2. Collection of tuition waivers Update on assignments – All work due by Friday, April 28 Remaining class schedule, April 20 and 26 (Symposium) Opportunity for individual meetings Discussion of interviews and focus groups Data coding and analysis
- 3. Review of Assignments Worksheets, Engagement, and Participation (30%) CITI Social Behavioral exam, print completion report (15%) Outline of a SoTL Research Proposal for Medical Education (50%) * Alternative to small group presentation of project (5%) – Medical Education Research Symposium
- 4. Before Data Collection Setting the boundaries for the study Purposefully select participants who are best suited to provide insight into the research question Collecting information through observations, interviews, / focus groups, documents, and visual materials
- 5. The Researcher’s Role Researcher biases, background, steps taken re: reflexivity Why this site? What was done at the site? Will it be disruptive? How minimize? What effects might that have on the quality of the data? How will results be reported? What will the “gatekeeper” gain from the study?
- 6. Thoughts on Interviewing In-depth interviewing is a means to understand the experience of other people What, how, and why questions Use probes (follow-up questions) Watch for markers and follow them up with a question to elicit additional information
- 7. Conducting Focus Groups Requires a highly skilled facilitator to draw people out Goal is to obtain in-depth, “rich, thick” description Build rapport with group “Can anyone else relate to that experience” or “Has anyone else had a different experience?” Ask for examples, and keep asking for examples
- 8. Use digital recorder(s) – need 2 or 3 for a table of 12 participants No more than 4-5 questions per hour/ 6 to 8 in 1.5 hours Round robin number your participants If you cannot conduct the interview, ask another (qualified) person to serve as your facilitator Use a transcriptionist familiar with qualitative data Always listen to your data; do not rely on transcripts alone
- 9. The detailed line-by-line analysis necessary at the beginning of a study to generate initial categories and to suggest relationships among categories
- 10. Participants’ recounting of actual events and actions as they are remembered and Texts, observations, videos, or other materials gathered by the researcher, and field notes made by the researcher Researcher’s memos of those events, objects, happenings, and actions Interplay between data and researcher as the instrument of interpretation
- 11. Qualitative analysis is a way of thinking about data Learn to listen, letting the data speak to the researcher Learn to relax, adopt a more flexible, less preplanned, and less controlled approach to research
- 12. Major Points About Data Analysis Must listen closely, taking into account the interviewees’ interpretations Conceptualize and classify chunks of meaning Enables researchers to examine what assumptions about the data they are taking for granted
- 13. Conceptualizing is the first step in analysis or theory building (in a grounded theory study). A concept is a labeled phenomenon. Can label a word or groups of words, such as a phrase
- 14. The researcher’s record of analysis, thoughts, interpretations, questions, and directions for further data collection. Often called analytic memos
- 15. Categories are concepts, derived from data, that stand for phenomena. Phenomena are important analytic ideas that emerge from the data. They answer the question “What is going on here?”
- 16. Once concepts begin to accumulate, the researcher should begin the process of grouping them into explanatory terms called categories. Example: A researcher is studying children at play and notices acts that she labels “grabbing,” “hiding,” “avoiding,” and “discounting.”
- 17. Then, on observing the subsequent incident, it suddenly dawns on the researcher that what the children are doing is trying to avoid something through those actions. Thus, grabbing, hiding, avoiding, and discounting are grouped under the more abstract heading of “strategies.”
- 18. But strategies for what? The most probable answer is to avoid “toy sharing.” In this manner, it emerges that one of the important phenomena to study in relation to groups of children at play is “toy sharing,” with “strategies” for either sharing or not sharing being a subcategory
- 19. How would we begin to code these pages from an actual focus group transcript of physicians in a Master Teacher program? What conceptual labels might you assign to the passages you read? Which concepts can be grouped into categories? What sense are you making of the data?
- 21. Research Question: What did Master Teachers learn? Focus Group Questions: Changes in methods used to teach? Changes in clinical practice, and how relate to patients? Specific incident that had a significant impact on teaching? What organizational barriers encountered in using what was learned? The Task