Recently, Nick Hopwood and I joined a community of practice meeting with Science academics who were keen to understand more about researching their teaching practice. Nick opened up the discussion about why qualitative analysis can feel so difficult, and shared how academic research is slowly changing to accommodate techniques beyond traditional (and comfortable!) coding.

Building on Nick’s points, this post looks at approaches to qualitative research design which help you uncover richer insights, and some practical techniques to hone your observation skills, drawn from real-world qualitative projects in education.

Analysing throughout the research process

One of the first things you learn in qualitative research analysis is that it’s not an isolated process, but happens through each phase in your project. As soon as you start reviewing the literature and scanning previous findings, you’re already analysing to better define your research questions. Likewise, your choice of research approach and methodologies are informed by your analysis so far, and will impact the outputs you’ll analyse later.

During the fieldwork, whether it’s ethnography, observations, interviews or group discussions, the questions you ask and how you listen and prompt for detail are all examples of analysis too. Qualitative research with human beings in all their messy and hard-to-code detail means you’re often analysing as you go, responding to each moment to make sure you learn as much as you can from participants.

Safely back at your desk, the process of scanning and sorting through notes and themes can start (more on that later). The analysis continues right through to report writing and presenting. Every decision you make about what to include, emphasise or leave out is part of your process.

A mind map showing the analysis already taking place as the discussion guide is planned

Analysing in the field: your human observation toolkit

To get the most from your research analysis, try to conduct your own fieldwork as often as you can, ideally collaborating with other researchers to compare and contrast what you’re seeing. If you run your own research interviews, you can try out different techniques and work on your observation skills, enriching your analysis and ultimately your research outcomes, too.

Try asking yourself and your co-researchers some of these observational questions next time you’re interviewing:

💬 What do people say, and how do they say it?

Interview transcripts are one aspect, but what about tone, emphasis and expression? How do the words “I really liked learning online” change with enthusiasm, sarcasm or different context around them?

🤐 What are people not saying?

Is there a hesitation or pause at a key moment? Was there something missing from an answer that you had been expecting? Perhaps you’re asking about technology, but your interviewee keeps talking about people instead? Does the pattern repeat across interviews?

🧐 What facial expressions can you observe?

Transcripts don’t include details like facial expressions, but you can. An exasperated eye roll, a wide smile or a knowing smirk can change the meaning of a sentence, and therefore how you interpret it in your analysis.

🤦🏽‍♀️ What’s going on with that body language?

You don’t need to be an expert in psychology to pick up on slumped shoulders, nervous toe-tapping or impatience. What is it about the topic or question that prompted the reaction? Can you ask a follow-up question to find out more?

✍️ What can be expressed differently in writing or a drawing?

Writing and drawing are great additions to the qualitative research toolkit. Ask participants to keep a short diary or note key reflections before you meet, when there’s time to think and less pressure to ‘perform’. Or ask them to draw a key moment or experience (it doesn’t matter how badly) then tell you about it. You’ll be surprised at the depth of insight that can emerge, just by offering a different medium for expression.

🎒 What’s in someone’s bag, desk or workspace?

Qualitative research is sometimes criticised for asking people to remember or describe something accurately, when we know memories fail and distort information. So why not ask them to show you, if the situation is right? If you’re researching learners and learning, physical context can be a great reality check (“Oh yes, I forgot I had that notepad… that’s really important because…”).

👥 How are people interacting with each other?

If you’re observing a space like a classroom or library (with permission), qualitative details might be found in non-verbal interactions, as well as direct questioning. Who’s talking to whom? How long for? Is it always the same, or different people? Who’s not interacting at all?

🧑🏻‍💻 How do they navigate online? What’s on their devices?

If you want to understand how learners use a portal, app or website, one of the best things you can do is observe them using it. Give them a task to carry out, some information to find or an assignment to upload. How do they navigate there? What’s in their favourites? Where do they miss key information we thought they should know?

Use ongoing analysis to refine your data collection

Some important outcomes of ongoing analysis come from insights into the way you are collecting your data. Ask yourself:

  • What does this data suggest I should keep doing or do more of? Which interview techniques are working really well? Which are the best places/ times to observe?
  • Given the silences I’ve noticed (what people aren’t saying, things I’m not seeing), should I change something to try to address that?
  • How am I tracking in relation to my aims or research questions? Do my data feel like they align with these? Am I approaching saturation, or am I still learning something new? Do I change something to try to get fresh insights, or is it time to leave the field? If the data aren’t helping me answer my research questions, what needs to change? The approach to fieldwork or the questions?

This third question relates to an iterative process that begins in the field and continues through the post-fieldwork analysis – a process involving changing relationships between what the data are telling you and what you want to know. For more on this, check out Srivastava & Hopwood’s (2009) OpenAccess paper (thanks to Nick Hopwood for the additional tips!).

Capture rich data for now – and later

To give yourself the best chance of some deep and rich analysis after your fieldwork, keep your phone close, and your notepad closer! I find that my handwritten notes, doodles and triple-underlined sections with arrows hastily scribbled often take me back to key points more efficiently than a set of transcripts can. Combine that with anything you can capture as a picture, video or audio recording (with all the appropriate permissions to do so) and you have the ingredients for a vibrant set of analysis sessions once your interviews, discussions or observations have wrapped up.

Keep your camera close: capture details in the moment

Now that you’ve gathered the best data you can, the upcoming final blog in this series will be exploring the kinds of mapping, models and approaches you can use to make sense of it all. There are also ideas about how to bring others into the analysis and feedback process, including those who participated. Stay tuned!

In the meantime, if you’re keen to explore more about qualitative research from a wider (non-academic) perspective, take a look at Ray Poynter’s notes for a non-researcher conducting qualitative research. It’s written from a market/commercial research perspective, with some great points about analysis, narrative and research design that are highly practical for academic researchers too.

Photo by Kari Shea on Unsplash

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