Qualitative Research Topic : Analysis is Ongoing (P.272~290) MA1C0109 Owen 楊勝雄

Analysis is Ongoing Many methodological writers present two options for formal analysis First is ongoing analysis Second is analysis at the end of data gathering

No matter ongoing or toward the end, keep in mind the following pointers to facilitate analysis. 1.Refer regularly to your conceptual framework. 2.Keep your questions in mind. 3.Modify your data gathering based on what you are learning. 4.Write all the time.

5. Talk your ideas through with people. 6. Read and read and read. 7. Be creative. In addition, practice good management skills is very important for keeping the data organized and accessible. * Manage your data-don’t rely on your memory.

Categorical or Holistic Analysis Qualitative methodologists recognize two sets of overall analytic strategies. Frist, emphasizing the development of analytic categories. Second, focusing more on description.

Categorizing strategies- Identify similarities and differences among the data, coding and sorting them into appropriate categories. These strategies require decision rules to help guide the assignment to particular categories.

Holistic strategies- Describe connections among the data in the actual context- a place, an event, a person’s experience, a text. * The result is a narrative portrait of an individual or program.

Data connection *Categorizing *Seeking patterns and themes Analysis is pattern identification over awareness of detail. Whatever strategies you use, the foundation of analysis is thick description.

Thick description details physical surroundings, time, and place, actions, events, words, and people on the scene. Thick description makes analysis and interpretation possible.

Generic Analysis Analytic procedures typically fall into the Following seven phases: * Organizing the data * Familiarizing yourself with the data * Generating categories and themes * Coding the data * Interpreting * Searching for alternative understandings * Writing the report

Each phase entails data condensation. Data condensation * Is the process of synthesizing material into shorter formulations. * Requires judgment about the salience and power of data to tell the story. * Is guided by purpose and the conceptual framework.

Organizing the Data As a preliminary step, inventory on note cards the data that you have gathered. Tools for organizing: 1.Note cards 2.Magic markers 3.Post-it notes 4. File folders 5. Software programs

Familiarizing yourself with the data Have to read, reread and once more read through the data. Familiarize: * Review and review the data * Let the data incubate * Review and review again * Live with the data * You have to know the data intimately- there is no substitute for this.

Generating Categories and Themes There is much confusion, especially among beginners, about the difference between a category and a theme. Category- As a word or phrase describing some segment of your data that is explicit. Categories provide direction for data Gathering.

Theme- Is a phrase or sentence describing more subtle and tacit processes. Theme often emerge during intensive analysis as the researcher locates and describes more subtle processes.

Thematic analysis typically emerges from the deep familiarity with the data that comes from categorizing. Inductive analysis is one strategy to identify salient categories within the data. Indigenous categories are those expressed by the participants; the researcher discovers them through analysis of how language is used.

Analyst- Constructed categories do not necessary correspond directly to the categories of meaning used by the participants.

What is a theme? Van Manen (1990) defines the concept as follows: 1.Theme is the experience of focus, of meaning, of point. 2.Theme formulation is at best a simplification. 3.Themes are not objects one encounters at certain points or moments in a text. 4. Theme is the form of capturing the phenomenon one tries to understand.

Coding Coding is the formal representation of analytic thinking. A code- Is a word or short phrase that captures and signals what is going on in a piece of data in a way that links it to some more general analysis issue. * Mechanics of coding very, depending on your style and what works for you.

Interpretation Interpretation- Means attaching significance to what was found, making sense of findings, offering explanations, drawing conclusions, extrapolating lessons, making inferences, considering meanings and otherwise imposing order.

Interpretation * Requires the telling of a story * Is not rule bound * Depends on thick description Kvale (1996) identifies three contexts of interpretation: 1.Participants understanding 2.Commonsense understanding 3.Theoretical understanding

Searching for Alternative Understandings Alternative understandings always exist: You will need to search for, identify, and describe them and then demonstrate how your interpretation is sound, logical and grounded in the data.

Alternative understandings * What are other plausible interpretations? * How does your argument stand up to these? * Is your argument well supported by the data? * Is your argument credible? Part of this process is to assess the data for their credibility, use-fulness, and centrality.

Writing the Report For now, we turn to a brief discussion of three Specific analysis strategies drawn from Cognitive anthropology, phenomenology, and narrative analysis for analyzing interview data. The interpretive process illuminates the multiple meanings of events, objects, activities, experiences and words.