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IB DP Psychology — Data Analysis and Interpretation | SL & HL | Paper 3
🎯 Learning Intentions By the end of this note, you will be able to:
- Define thematic analysis, themes, and codes using IB-aligned terminology.
- Explain the six phases of thematic analysis and how each phase contributes to the overall process.
- Describe the difference between inductive and deductive approaches to coding qualitative data.
- Evaluate the strengths and limitations of thematic analysis as a method of qualitative data analysis.
- Apply thematic analysis concepts to a research scenario, identifying codes and potential themes from raw qualitative data.
- Discuss how researcher bias and reflexivity influence the outcomes of thematic analysis.
- Analyse thematic analysis using relevant concept areas: Bias, Measurement, Perspective, and Responsibility.
Introduction & Context
Imagine you have just conducted ten in-depth interviews with teenagers about their experiences of social media. You sit down with a stack of transcripts — hundreds of pages of people's words, stories, and feelings. How do you make sense of it all? You cannot simply count responses or calculate a mean. The richness of what people have said resists reduction to numbers. You need a systematic way to read across all of that data and identify the patterns that matter.
This is precisely the challenge that qualitative researchers face, and thematic analysis is one of the most widely used tools for meeting it. Rather than imposing a predetermined framework onto the data, thematic analysis allows researchers to move through the material carefully, labelling meaningful segments, grouping those labels together, and gradually building a picture of the recurring ideas — the themes — that run through participants' accounts. It is both a method and a craft, requiring rigour and interpretive sensitivity in equal measure.
In IB Psychology, thematic analysis is particularly relevant to Paper 3, where you are expected to understand how qualitative data is collected, processed, and interpreted. Understanding thematic analysis means understanding not just the steps involved, but also the assumptions behind them — about what counts as knowledge, whose voice is centred, and how a researcher's own perspective shapes what they find.
🔍 Analogy — Sorting a Pile of Photographs Imagine you have been given a large, unsorted pile of photographs taken at a school over an entire year. Your task is to make sense of them. At first, you simply look through them all carefully. Then you start grouping: photos of sports events here, photos of classroom learning there, photos of social gatherings in another pile. Some photos could belong to more than one group. You refine your categories, rename some, merge others. Eventually, you have a set of meaningful collections that together tell the story of the school year. Thematic analysis works in exactly this way — moving from raw, unorganised data toward a structured, meaningful account of what the data contains.
Core Concepts
Before we can understand how thematic analysis works, we need to understand what it is trying to produce. When qualitative researchers analyse data, their goal is not simply to describe what participants said — it is to identify the underlying patterns of meaning that run across multiple accounts. These patterns are what we call themes, and recognising them requires a structured process of reading, labelling, and interpreting the data.
📖 Key Definition — Thematic Analysis Thematic analysis is a qualitative method of data analysis used to identify, analyse, and report patterns of meaning (themes) within a dataset. It involves systematically working through data to code meaningful segments and then organising those codes into broader themes that capture something important about the research