Qualitative Data Analysis

Step 1: Determining Questions “Start-up” questions are general questions that help to frame the initial qualitative research project. Emergent questions develop during the research process. Both “start-up” and “emergent” questions guide qualitative data analysis.

Step 2: Unitizing Textual Data Textual data must be unitized (broken-down into parts). Units must be heuristic. A unit of textual data is also called a concept. First order concepts Second order concepts Textual units are not generally standardized.

Step 3: Developing Coding Categories Coding categories are developed through an iterative process. There are several types of coding processes: Housekeeping coding Research process coding Analytic coding Constant Comparative Method Analytic Induction

Processes of Categorizing Read all of your data completely in order to immerse yourself in them. Identify your first unit of data. Identify your second unit of data. Make a basic judgment of similarity-difference between these two units. Proceed with the similarity-judgment task for all your units of data. Develop category labels and descriptions (memoing) for each of your categories. Start over.

Step 4: Plugging Holes Additional data are collected to clarify connections between units of data in a given category. Additional data are collected when there are few textual units in a category that the researcher find important. Additional data are collected when logic suggests that particular categories are missing.

Step 5: Checking Negative case analysis is a process in which the researcher “tests” categories against new data – searching for units that are deviant or discrepant. Member checks are conducted by reviewing the researcher’s categories with informants. Triangulation is used when the researcher applies her coding categories to other types of data or when additional researchers derive coding categories from the same data set.

Step 6: Finding Exemplars Not all of the data will be reported in the final qualitative research report, exemplars are chosen to represent those data. Exemplars are examples in the data that best illustrate or “bring to life” the categories. Exemplars should be chosen for their “thick description” (Geertz, 1973) to enable the transferability of the study.

Step 7: Integrating Coding Categories The relationships between coding categories are mapped. This is a meta-coding activity.

Models of Qualitative Data Analysis

The Developmental Research Sequence (DRS) The DRS is used to understand semantic relationships and rules of a given speech community. The study of semantic relationships is MOST often featured. There are four activities involved in the DRS: Domain Analysis Taxonomic Analysis Componential Analysis Theme Analysis

Grounded-Theory Development (GTD) GTD MOST often features the study of rules. The goal of GTD is inductive theory construction. There are four primary activities involved in GTD: Open Coding Axial Coding Process Analysis Selective Coding