Qualitative Data Analysis

• Qualitative data analysis is labor intensive, complex, and requires creativity and conceptual sensitivity.
• It involves organizing data, providing structure, and eliciting meaning.
• There are no universal rules for analyzing and summarizing qualitative data.
• Challenge is to summarize findings while preserving richness and evidentiary value.

Process

• Commences during data collection.
• Four cognitive processes are at work: comprehending, synthesising, theorising & re-contextualising.
• These processes do not occur linearly; they may occur simultaneously.

Comprehending

• Strive to derive meaning from the data.
• Attempts to determine what is occurring.
• It is possible to thoroughly articulate the phenomenon under examination, and the data has reached saturation.

Synthesizing

• Sifting through data and inductively assembling pieces.
• Understanding what is typical of a phenomenon and its variations.
• Researchers can make generalized statements about the phenomenon and study participants by this stage.

Theorising

• Entails systematically sorting data.
• The process yields explanations for the phenomenon.
• Researchers formulate explanations and compare them to the data to find the best fit.

Re-contextualising

• This involves developing the theory further and exploring its applicability to other settings or groups.
• Qualitative researchers aim to create adaptable and generalizable theories.
• Deals with the applicability to other settings/groups

Developing a category scheme

• A method to classify and index data.
• A reductionist phase converts data into smaller, more manageable units.
• It involves developing a category scheme and coding data accordingly through close scrutiny.
• This commences with carefully reading and re-reading the data to identify regularities, concepts, and clusters of concepts.

Category scheme development questions

• What is this?
• What is going on?
• What does it stand for?
• What else is like this?
• What is this distinct from?

Research Questions

• Consider the following categories, decisions, positive experiences, negative experiences, and suggestions for improvements.
• Why did you decide to study in Australia?
• Please describe any positive experiences you've had since beginning your studies in Australia.
• Please describe any negative experiences you've had since beginning your studies in Australia.
• What suggestions do you have for Australian universities so that they can help foreign students transition into their studies?

Coding qualitative data

• Re-read and code according to the relevant category.
• It is not always easy to determine the most appropriate code.
• It might be necessary to revise or merge categories.
• Traditionally, this has been done by hand, however computer programs are available now.
• Thematic analysis is used when the data is not based in a specific tradition.

Thematic Analysis

• General method for qualitative analysis of transcripts or similar textual data sources.
• It is applicable in every approach to qualitative methodology.
• When utilizing a specific tradition, follow their process of analysis & organisation of findings.

Preparing the data

• Transcribe the recorded interview.
• De-identify the data.
• Carefully check the transcription.
• Re-read the transcript.
• Understand overall meaning.

Coding The Data

• Read the transcript.
• Look for meaning units.
• Use a unit of text (statement) expressing a single idea.
• Develop a system of arrangement for the code.
• The code may be labeled using one word or statement.
• Ensure the code accurately describes the essential meaning.
• Continue the coding process until all meaning units within the text are coded.

Reduction

• Read through list of codes.
• Identify and group similar codes together.
• Reduce number of codes by either clustering those that relate to one another, or subsuming those codes that are part of the same concept.
• You should begin to see patterns within the data.

Developing sub-themes

• Cluster the codes into sub-themes once the list of codes has been reduced.
• The essence of the name should be conveyed.

Clustering of codes

• Clustering of codes example
• Improves teaching
• Information on teaching for teacher
• Teacher understands students view relate to "Advantages of student evaluation of teaching"
• Information on quality of content & teaching materials
• Lack of belief in the process
• Not understanding the process
• Evaluation influenced by personal feelings
• Teachers ability to influence evaluation can be labelled as "Factors hindering student evaluation of teaching

Developing themes

• Review the list of sub-themes.
• Cluster similar sub-themes together into themes.
• Name the themes, conveying the essence in that name

Writing up findings

• Links to the research objectives must be made.
• It must be systematic.
• Explain all key findings and support with pertinent participant quotes.
• Demonstrate that emerging picture is that of all participants.
• There should not be an over-reliance on certain participants.
• The same quote should not be used more than once.
• Diagrams can explain relationships between concepts.

Critical appraisal of qualitative analysis

• Were the data management and data analysis methods sufficiently described?
• Was the data analysis strategy compatible with the research tradition, nature, and type of data gathered?
• Did the analysis yield an appropriate product?
• Did the analytic procedures suggest the possibility of biases?

Critical appraisal of qualitative findings

• Were the findings effectively summarized, with good use of excerpts and supporting arguments?
• Did the analysis yield a meaningful picture of the phenomenon under investigation?
• Are the themes and patterns logically connected to each other to form a convincing and integrated whole?
• Were figures, maps, and models used effectively to summarize conceptualizations?