In this tutorial, we will revisit and extend our understanding of Reflexive Thematic Analysis by analysing video interviews, developing and refining themes, and reflecting on how our assumptions and perspectives shape the interpretation of qualitative data in HCI research. We will then go one step further, from themes to implications: what a theme means for the people who design, study or live with technology.
In this pre-class task, you will practise taking observational notes from a video interview. You will use these notes during the tutorial to revisit the thematic analysis process covered in the Week 7 workshop.
Select one of the three videos below and take observational notes while watching it. As you may have experienced in Assignment 2, observational notes can be taken during interviews or while participants perform certain tasks. They help researchers capture participants’ experiences, behaviours, interactions and the context in which these occur. While watching, pay attention to:
Record at least 3–5 observations, including timestamps where possible. Distinguish between what you directly observe (O), what the participant reports (R), and your own interpretations (I).
The videos below present personal accounts of three individuals, Simon, Sarah and Stacey, and their experiences with different forms of technology. Before selecting a video, read its content warning and context.
Simon’s Experience with Assistive Technology
Content warning: Discussion and depiction of physical disability and reliance on assistive technology.
Context: Simon demonstrates how he uses assistive technology in everyday life. His equipment includes a communication aid, powered wheelchair, environmental controls and a computer scanning interface. He uses head-operated switches to access these systems. The video provides an opportunity to examine accessibility, independence and interaction design.
Content warning: Discussion of romantic relationships with AI, emotional attachment and intimacy.
Context: Sarah describes her romantic relationship with Sinclair, an AI conversational companion. Her account raises questions about emotional connections with AI, what makes interactions feel personal, and how conversational technologies influence people’s understanding of companionship.
Stacey’s Life with Aibo, Sony’s Robotic AI Dog
Content warning: References to the loss of a companion animal and grief.
Context: Stacey shares her experience living with Mia, Sony’s Aibo robotic dog. She discusses how Mia’s behaviours and responses develop through interaction, and how she forms a bond with the robot over time. The video offers an opportunity to explore human-robot interaction, companionship and emotional attachment to robotic technologies.
Create a short Ed post including the following:
Bring your full observational notes to the tutorial. You will use them to develop codes, identify patterns and construct a candidate theme. You do not need to develop codes or themes before class.
Throughout this tutorial, we will explore the following research question:
How do individuals experience and make sense of their relationships with technology in everyday life?
As a group, you will use observational notes from your pre-class tasks. Although these interviews explore different technologies, they may reveal related experiences, meanings and tensions. Your task is to explore these connections through Reflexive Thematic Analysis (RTA). Remember that RTA is an iterative and interpretive process. Researchers actively construct codes and themes through their engagement with qualitative data. Different researchers may develop different, well-supported interpretations of the same material.
In this task, you will use your pre-class observational notes to develop initial codes, identify patterns across interviews and construct a candidate theme.
Before beginning your analysis, consider:
Write down a brief response. You will revisit it later in the tutorial. Next, revisit the observational notes you collected before class. Select 3–5 observations and develop initial codes that capture something meaningful about the speaker’s experience with technology. The codes can capture explicit meanings (what the participant directly says or does) or implicit meanings (what you interpret their experience to suggest). You may use the following format to structure this part of the task. You should consider whether your initial assumptions influenced how you coded the observations.
| Observation or excerpt (with timestamp) | Initial code | Why did you assign this code? |
|---|---|---|
| … | … | … |
Form groups of 4–5 students. Your group members do not need to have watched the same video. Each member should briefly introduce the video that they watched and share two or three interesting observations and corresponding codes. As a group, discuss:
Use the table below to organise your discussion. You do not need to reach agreement on every interpretation. Differences in interpretation can help you recognise how researchers’ experiences, assumptions and analytical interests shape qualitative analysis.
| Related observations and codes | What connects or distinguishes them? | What might this suggest about people’s relationships with technology? |
|---|---|---|
| … | … | … |
Using your group discussion, develop one candidate theme that addresses the research question. A theme captures a pattern of shared meaning organised around a central organising concept. It should go beyond describing a topic and offer an interpretation of the participants’ experiences.
As a group, identify:
Tip: You do not need to include every observation or every interview in your theme. Consider whether the evidence supports the connections you are making.
Keep your candidate theme available for the next two tasks.
Developing themes is an iterative process. In this task, you will evaluate two tutor-prepared candidate themes that address the same research question and draw on observations from the three interviews.
Your tutor will provide two candidate themes, Theme A and Theme B, along with supporting observations from the interviews.
In your group, examine both themes and centre your discussions around the following table. During this process, you should consider whether your own assumptions or experiences influence which interpretation you find more convincing.
| Evaluation criteria | Theme A | Theme B |
|---|---|---|
| Central organising concept | ||
| Supporting observations | ||
| Strengths | ||
| Limitations or alternative interpretations |
Using your evaluation, work together to improve the theme that you identified as weaker. You may revise its name and central organising concept, or clarify its supporting evidence or analytical interpretation. Draw on the tutor-provided observations and your group’s pre-class notes where relevant.
Some prompts for you to consider:
Return to the candidate theme you developed in Task 1. Based on what you have learnt from critiquing and refining the tutor-prepared themes, make one change that strengthens it, and note why you made that change. Has your understanding of the interviews, or of your own assumptions, changed?
A theme tells your reader what is going on in your data. A research project also has to answer so what? That answer is an implication: the interpreted insight you want readers to take away, and what it means for the people who design, study, or live with technology. Themes are the output of your analysis; implications are your contribution to HCI.
An implication goes beyond a theme by saying who should do or think something differently, and what. It might be for design, but it can also be for research or practice (Dourish, 2006). For example, from the kind of data some of you collected in Assignment 2:
Take your refined theme from Task 2 and write one implication in two or three sentences. Then check it:
Each group shares its theme and implication. As a class, discuss which implications went furthest beyond their theme, and what they added.
If you want to see how published papers make this move (usually in their Discussion sections), look at Deng et al. (2022) (pp. 11–16), Tahmidul Karim et al. (2025) (pp. 3–5), Choi et al. (2024) (pp. 221–224) or Adiwangsa et al. (2024) (pp. 5–8).
Create a short Ed post (approximately 100–150 words) responding to the following questions:
Use examples from your analysis where possible.
Today’s tutorial is a simplified exercise in RTA. Each student has closely examined one interview, and your group has explored connections across a small collection of observations. In a full RTA study, researchers engage with the entire dataset repeatedly, revisiting and refining codes and developing themes through continuous analysis. If your final project includes qualitative data, you will follow a similar process, and you should present implications arising from your themes, not just the themes themselves (see Phase 6 in the Reflexive Thematic Analysis lecture). The same applies to quantitative results: a significant difference is a finding; what it means for your design is the implication. As you work through your analysis, refer to the Week 7 workshop and the Ed posts you and your peers contributed today, as these may help you reflect on different interpretations and analytical decisions.
Organise a time to meet with your research cluster (or form a new one; ask your peers during the tutorial!) and share plans for your final projects. It’s ok if you haven’t completely decided on your final project yet; this meeting is to understand and discuss ideas.
As a group you should: