Assignment: Thematic Coding Discussions

Assignment: Thematic Coding Discussions

Assignment: Thematic Coding Discussions

When to use thematic analysis
Thematic analysis is a good approach to research where you’re trying to find out something about people’s views, opinions, knowledge, experiences or values from a set of qualitative data – for example, interview transcripts, social media profiles, or survey responses.

Some types of research questions you might use thematic analysis to answer:

How do patients perceive doctors in a hospital setting?
What are young women’s experiences on dating sites?
What are non-experts’ ideas and opinions about climate change?
How is gender constructed in high school history teaching?
To answer any of these questions, you would collect data from a group of relevant participants and then analyze it. Thematic analysis

allows you a lot of flexibility in interpreting the data, and allows you to approach large data sets more easily by sorting them into broad themes.

However, it also involves the risk of missing nuances in the data. Thematic analysis is often quite subjective and relies on the researcher’s judgement, so you have to reflect carefully on your own choices and interpretations.

Pay close attention to the data to ensure that you’re not picking up on things that are not there – or obscuring things that are.

Different approaches to thematic analysis
Once you’ve decided to use thematic analysis, there are different approaches to consider.

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There’s the distinction between inductive and deductive approaches:

An inductive approach involves allowing the data to determine your themes.
A deductive approach involves coming to the data with some preconceived themes you expect to find reflected there, based on theory or existing knowledge.
Ask yourself: Does my theoretical framework give me a strong idea of what kind of themes I expect to find in the data (deductive), or am I planning to develop my own framework based on what I find (inductive)?

There’s also the distinction between a semantic and a latent approach:

A semantic approach involves analyzing the explicit content of the data.
A latent approach involves reading into the subtext and assumptions underlying the data.
Ask yourself: Am I interested in people’s stated opinions (semantic) or in what their statements reveal about their assumptions and social context (latent)?

After you’ve decided thematic analysis is the right method for analyzing your data, and you’ve thought about the approach you’re going to take, you can follow the six steps developed by Braun and Clarke.

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