Qualitative HCI Research. Ann Blandford
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Figure 2.3: An idealised shape of a qualitative study.
Although we first present steps sequentially and simply, you should be aware that this is an over-simplification: it is hardly ever possible to separate the components of a study and treat them independently. The style of data gathering influences what analysis can be performed; the relationship established with early participants may influence the recruitment of later participants; ethical considerations may influence what kinds of data can be gathered, etc. Managing these interdependencies can make qualitative research particularly challenging at times, but successfully juggling and trading them off also makes qualitative research interesting and rewarding. We return to this topic of interdependencies later.
2.3 BEING REALISTIC: RESOURCES AND CONSTRAINTS
Every study has to be designed to work with the available resources. Where resources are limited it is necessary to “cut your coat according to your cloth.” For example, if you have three months to conduct a Master’s project you will need to fit ambitions, and hence purpose, to what is possible with the available resources. Here are some things to consider when thinking about the time involved for a qualitative study:
• Time to obtain ethical clearance will depend on how sensitive the study is and which review board is assessing it; you can often get local knowledge to help you plan this.
• Time to recruit participants also depends on their situations and how interesting the topic is to them. Recruiting through a general subject pool can often be quick, but if you are seeking participants with specialist skills or knowledge, you should factor in significant time for this.
• The mean duration of an interview is under an hour, depending on the scope of the interviews. Few interviews are much longer than that because attention drifts. Observations can be longer (several hours per session with comfort breaks).
• Transcribing audio data typically takes 4–6 times as long as the recording, depending on data quality, lengths of silences and the transcriber’s typing speed. Transcribing video data takes significantly longer, depending on the level of detail being transcribed.
• Analysis time can vary, depending on the quality of the data and the depth and focus of analysis, but is likely to take at least 2–3 days per hour of data.
In total, a Master’s dissertation of three months (typical in the U.K.) is likely to involve 10–15 hours of audio data, or equivalent. That does not sound like much, but is usually all that is feasible when all the other stages of the project (including literature review and writing up) are taken into account. It is therefore important that the data should be as high quality as possible.
As well as time, resource considerations need to cover funding, equipment available for data collection and analysis, availability of places to conduct the study, availability of participants and expertise. Here, we briefly discuss some of these issues, while avoiding stating the obvious (variants on the theme of “don’t plan to use resources that you don’t have or can’t acquire!”).
Where a study takes place can shape that study significantly. Studies that take place within the context of work, home or other natural setting are sometimes referred to as “situated” or “in the wild” (e.g., Rogers, 2012). Studies that take place in more controlled settings include laboratory studies (e.g., involving think-aloud protocol) and some interview studies. There are also intermediate points, such as the use of simulation labs, or the use of spaces that are similar to the work setting, where participants have access to some, but not all, features of the natural work setting. Observational studies most commonly take place “in the wild,” where the “wild” may be a workplace, the home, or some other location where the technology of interest is used. Interview studies may take place in the “wild” or in another place that is comfortable for participants, and quiet enough to record and to ensure appropriate privacy and safety for both participant and interviewer. Of course, there are also study types where researcher and participant are at a distance from each other, such as diary studies and remote interviews.
Tools for data recording include notes, audio recording, still camera, video camera and screen capture software. All of these can be useful, depending on the situations and purpose for which data is being gathered.
Hand-written or typed notes can be most effective in noisy environments, or where there are sensitivities about any other form of recording. Care needs to be taken that the act of note-taking does not disrupt the interaction. For example, if particular actions are noted in an observation session, participants may be aware of every time a note is taken, and hence self-conscious about the activity that is provoking the note-taking (Blandford et al., 2015a).
Audio recording is often most suitable for interviews and focus groups. If you are working on your own it might be difficult to follow and facilitate the interview and note down all the important points otherwise. Audio recording and transcription is also needed where the details of specific words and phrases people use are important. Audio recordings are preferable to note-taking particularly when the study is exploratory and there is a chance that information that might be overlooked early on turns out to be important later, or if the data is rich enough to support multiple analyses. For example, Rajkomar et al. (2015) originally gathered data on people’s situated use of home haemodialysis technology in order to test and extend the DiCoT approach (Furniss and Blandford, 2006) to analysing a system in terms of Distributed Cognition (DCog: Hollan et al., 2000). Within the initial interview plan, we intentionally also addressed questions of basic usability and how people stay safe on home haemodialysis (Rajkomar et al., 2014). Another unanticipated theme within the data was how people cope with managing their own dialysis at home including, but not limited to, how they troubleshoot when the technology goes wrong (Blandford et al., 2015b). It would not have been possible for us to do this follow-up Thematic Analysis without full audio transcriptions of the interviews.
Still photographs of activities performed and equipment/technology used provide a permanent record to support analysis and for illustrative purposes in reports. This can be particularly useful when the equipment has been adapted by users, or for recording where technology was used or how it was configured. For example, Figure 2.4 shows a series of photos of glucometers used in a hospital that supported analysis of the system in terms of DCog (Furniss et al., 2015).
Figure 2.4: Glucometer use in a hospital. The same device is shown stand-alone (left), as part of a blood glucose testing kit (middle) and as part of a broader blood glucose testing system (right).
Video recording can be valuable for capturing the details of an interaction, but can be intrusive. Recording video can be particularly useful for capturing micro-interactions and interaction that involves the use of equipment or technology in a particular physical space (e.g., in a family car—see Cycil et al., 2014) or involves multiple users interacting with technology (see Marshall et al., 2011).
Screen capture software can give a valuable record of user interactions with desktop systems. For capturing rarely performed interactions, or interactions over an extended time period (e.g., how a document is written over a period of days or weeks), it may be possible to ask participants to record their own screens or to take screenshots (e.g., Karlson et al., 2010).
Particular qualitative methods may require specialist equipment for data gathering. Examples include the use of cultural probes (Gaver and Dunne, 1999), which involve participants receiving a set of tools such as cameras, notebooks, pens and sticky notes with which to record their experiences, or engaging participants in keeping video diaries. Other specialist tools may sometimes add value; for example, eye gaze tracking, motion capture or activity tracking may