A Practical Guide for Classroom Implementation

Why Thematic Analysis?

Thematic analysis (TA) offers an ideal entry point into qualitative research for undergraduate students and faculty new to qualitative methods. As Braun and Clarke (2006, 2013) have emphasized, TA provides a flexible yet systematic approach to identifying patterns of meaning across a dataset. Unlike some qualitative approaches that require deep engagement with specific theoretical frameworks, TA can be adapted to various epistemological positions, making it accessible for students still developing their methodological understanding.

The process of thematic analysis mirrors many cognitive skills that students already possess—identifying patterns, making connections, and interpreting meanings—but applies these skills systematically to research data. This familiar-yet-structured approach helps ease the transition from quantitative to qualitative thinking while still introducing students to the richness and complexity of qualitative inquiry.

Understanding the Thematic Analysis Process

While various approaches to thematic analysis exist, Braun and Clarke’s six-phase model provides a clear, accessible framework that works well in undergraduate teaching contexts. This section outlines each phase with specific considerations for classroom implementation.

Phase 1: Familiarization with the Data

What it involves: Immersing oneself in the data through repeated reading, listening to audio recordings (if applicable), and making initial notes about interesting aspects of the data.

Classroom adaptation:

• Have students read through the entire dataset at least once before beginning any formal coding
• Ask students to highlight sections that stand out to them and make margin notes about their initial impressions
• Create a shared document where students can post initial observations and questions

Teaching tip: Emphasize that this phase is not about rushing to analyze but about developing a deep familiarity with the data. Quality time spent here leads to more insightful analysis later.

Phase 2: Generating Initial Codes

What it involves: Systematically identifying and labeling features of the data relevant to the research question. Codes capture both semantic content (explicit meanings) and latent content (underlying assumptions).

Classroom adaptation:

• Begin with line-by-line coding as a class exercise, where students work individually or in pairs to assign brief descriptive labels to each meaningful unit of text
• Create a collaborative coding exercise where different students code the same excerpt, then compare and discuss their codes
• Use a physical approach with printed transcripts, colored pens, and sticky notes to make the process tangible

Teaching tip: Demonstrate the difference between descriptive codes (simply summarizing content) and interpretive codes (identifying implicit meanings or concepts). Both have value but serve different purposes.

Phase 3: Searching for Themes

What it involves: Examining codes to identify broader patterns of meaning (potential themes) and collating all relevant coded data extracts within these identified themes.

Classroom adaptation:

• Have small groups sort related codes into clusters, giving each cluster a provisional theme name
• Use a physical sorting activity where code labels written on small cards are arranged on a large surface
• Create a visual mapping exercise where students draw connections between related codes

Teaching tip: Use the metaphor that Braun and Clarke suggest: if codes are bricks and tiles, themes are the walls and roof panels. This helps students understand the relationship between codes and themes.

Phase 4: Reviewing Themes

What it involves: Checking if themes work in relation to both the coded extracts and the full dataset. This often involves refining, splitting, combining, or discarding themes.

Classroom adaptation:

• Conduct a “theme testing” exercise where groups present a potential theme along with supporting data extracts, while the class evaluates whether the theme is coherent and distinctive
• Create a collaborative thematic map that visually represents relationships between themes
• Use a “critical friend” approach where groups review and provide feedback on each other’s themes

Teaching tip: Emphasize that identifying a theme is not the endpoint but the beginning of a deeper analysis. Strong themes capture something important about the data in relation to the research question.

Phase 5: Defining and Naming Themes

What it involves: Refining the specifics of each theme and generating clear definitions and names that capture the “essence” of what each theme is about.

Classroom adaptation:

• Have students write a two-sentence definition for each theme: the first sentence defining what the theme is about, the second explaining what it tells us about the data
• Create a class activity where groups develop evocative theme names that capture complex ideas concisely
• Challenge students to identify subthemes within broader themes

Teaching tip: Show examples of theme names from published studies, contrasting generic descriptive labels with more conceptual, interpretive titles.

Phase 6: Producing the Report

What it involves: The final analysis and write-up, selecting compelling extract examples, relating the analysis back to the research question and literature.

Classroom adaptation:

• Structure a collaborative writing process where different groups develop sections of a findings report
• Have students create visual or multimedia presentations of key themes
• Implement a peer review process where students evaluate and provide feedback on each other’s written analyses

Teaching tip: Emphasize that the write-up is not simply describing themes but telling a coherent analytical story about the data that addresses the research question.

Common Challenges and Solutions in Teaching Thematic Analysis

Challenge: Students Struggle to Move Beyond Description

Solution: Provide sentence starters for interpretive coding like “This suggests…” or “This reveals…” Compare examples of descriptive versus interpretive codes side by side. Create an exercise where students intentionally transform descriptive codes into interpretive ones.

Challenge: Students Create Vague or Overlapping Themes

Solution: Teach students to test themes by articulating in one sentence what a theme reveals about the research question. Demonstrate how to check theme boundaries by assessing whether data extracts could fit equally well in multiple themes. Introduce the concept of theme “coherence” through concrete examples.

Challenge: Students Rush the Analysis Process

Solution: Structure the analysis timeline with specific checkpoints for each phase. Emphasize that quality analysis takes time and iteration. Demonstrate how early themes typically evolve substantially through the review and refinement process.

Challenge: Students Avoid Engaging with Contradictions in the Data

Solution: Explicitly value the identification of tensions and contradictions in the data. Create an exercise specifically focused on finding disconfirming cases or contradictory patterns. Show how nuanced analysis often reveals complexities rather than simple consensus.

Challenge: Students Struggle with Theoretical Integration

Solution: Begin with primarily inductive analysis focused on the data itself. Introduce theoretical concepts gradually as they become relevant to emergent themes. Provide scaffolded exercises where students practice connecting their findings to specific theoretical concepts.

Evaluating Student Thematic Analysis Work

Assessing qualitative analysis can be challenging, especially for faculty accustomed to quantitative assessment criteria. The following evaluation framework focuses on process and analytical quality rather than “correct” outcomes:

1. Systematic Approach

• Evidence of following the six phases of thematic analysis
• Documentation of analysis process and decision-making
• Organized management of data and codes

2. Analytical Depth

• Movement beyond surface descriptions to interpretive insights
• Consideration of multiple possible interpretations
• Engagement with implicit meanings and assumptions

3. Theme Quality

• Coherent themes with clear boundaries
• Compelling evidence from data extracts
• Themes that address the research question in meaningful ways

4. Reflexivity

• Recognition of how the analyst’s positioning affects interpretation
• Awareness of assumptions brought to the analysis
• Consideration of alternative perspectives

5. Communication

• Clear, concise theme definitions
• Logical organization of findings
• Effective use of data extracts to illustrate themes

Connection to Upcoming Activities

The concepts and skills introduced in this chapter provide the foundation for the collaborative research activities that follow. In subsequent chapters, students will have opportunities to:

1. Generate rich qualitative data through methods introduced in the previous chapter
2. Apply thematic analysis systematically to understand patterns across that data
3. Work collaboratively to develop deep, nuanced interpretations
4. Connect analysis findings to theoretical frameworks
5. Translate analytical insights into practical recommendations

By establishing a solid understanding of the thematic analysis process and practicing collaborative analytical skills through the activities in this chapter, students will be prepared to engage meaningfully with the more extensive research projects that follow.

References and Resources

Key Methodological Texts on Thematic Analysis

• Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101.
• Braun, V., & Clarke, V. (2013). Successful qualitative research: A practical guide for beginners. London: Sage.
• Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589-597.
• Braun, V., & Clarke, V. (2021). One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qualitative Research in Psychology, 18(3), 328-352.

Teaching Resources

• Clarke, V., & Braun, V. (2013). Teaching thematic analysis: Overcoming challenges and developing strategies for effective learning. The Psychologist, 26(2), 120-123.
• Terry, G., Hayfield, N., Clarke, V., & Braun, V. (2017). Thematic analysis. In C. Willig & W. Stainton-Rogers (Eds.), The Sage handbook of qualitative research in psychology (pp. 17-37). London: Sage.
• The University of Auckland. (n.d.). Thematic analysis: A reflexive approach. https://www.psych.auckland.ac.nz/en/about/thematic-analysis.html