This research employs qualitative methods to explore and triangulate user responses to visualisations, as opposed to empirical methods, such as preferential studies or measures of efficiency, which are commonly used in HCI testing. These evaluative methods are not likely to answer the questions defined above on the nature of visualisation, and are empirical in nature. As seen in the previous chapter, there are many examples of quantitative analysis of visualisations (see 2.2 on page 30), but they do not allow the non-expert user to describe their own experience with the visualisations, their own reality. Qualitative methods were employed in contrast with existing published research, so that the user’s real experience with the work is recorded. These methods were developed based on John Zimmerman’s [226] Research Through Design model for practice-based research in the field of Human-Computer Interaction (HCI) and Lincoln and Guba’s highly influential book, Naturalistic
Inquiry [124].
3.2.1 Research Through Design
Zimmerman’s model of research through design [226], defines the process and evaluation used to develop the interactive artwork. Research through design requires a novel integration of theory, technology, user need and context. The design process is then evaluated against four criteria: process, invention, relevance, and extensibility. Research through design, can be contrasted to research for design (developing new methods of designing) or research on design (research into current practices and processes of designers). The interactive artwork created for this research was called 18S rDNA. It is named after a gene that is present in all eukaryotes (most cell-based life forms) that scientists can use to distinguish between organisms present in soil samples.
Reflecting on the development of 18S rDNA allows the processes to be developed and expressed in a way that is extensible and useful to visualisation designers. The processes used to develop the installation are then expressed, moving from tacit to explicit knowledge. Because of this, the methods can then be used to develop a final installation. This will allow the whole process discovered to be tested, communicated, and made extensible to the design community. The detailed discussion of the design of 18S rDNA will take place in chapter 5.
3.2. QUALITATIVE RESEARCH METHODS 63
3.2.2 Naturalistic Inquiry
Lincoln and Guba’s model of naturalistic inquiry defines the characteristics of postpositivist qualitative research [124, pp. 39-43], though not all are useful for a research through design method. The following characteristics established by Lincoln and Guba informed this research:
Use humans as the primary data-gathering instrument. Rather than relying on instruments, the preferable method of collecting data is through human interaction. The inquirer and the subject are capable of grasping meaning of interactions in the text context, whereas instruments are not.
Use tacit knowledge The nuances of the realities of each subject in the observed context is exposed through tacit knowledge. Some of the interaction between the subject and observer only occurs at this level. In addition to knowledge expressible in language, tacit knowledge more fairly mirrors the values of the investigator.
Use qualitative methods, rather than quantitative Qualitative methods are more adaptable to dif- ferent contexts and realities of the subject than quantitative methods.
Inductive data analysis, rather than deductive Inductive analysis of data is more likely to identify multiple realities experienced by different subjects. Generally inductive analysis infers general laws from specific circumstances; deductive analysis infers particular circumstances from a general law.
Emergent Research Design Since qualitative research is largely unpredictable, research design should emerge from the inquiry process. The inquiry should be a function of the interactions between the inquirer and the subjects, and their responses to the context.
Negotiate Outcomes The inquirer should allow the source of the data (in this case, test parti- cipants) to negotiate the outcomes. Any specific working hypotheses that might apply are best veri- fied by the participants involved in the testing. Participants who nominated that they were willing to be contacted were sent an email with an outline of research that is presented in section §4.4 for review. No users chose to respond to the request for feedback on the research.
Interpret data ideographically, rather than nomothetical Data should be interpreted as specific facts in terms of the particulars of the case, rather than in terms of law-like generalisations.
Set boundaries to the inquiry on the basis of the emergent focus of the research As the research design emerges, the focus of research potentially shifting, the boundaries of the research should be similarly flexible. This allows multiple realities, the experience of the subjects and interaction with the inquirer, to guide and focus the research.
Establishing trustworthyness Establishing trustworthiness is done by establishing credibility, transfer-
ability, dependability and confirmability [124, Chapter 11]. In this research, credibility is established using a
variety of methods Lincoln and Guba propose. Persistent observation is used to render the inquirer open to multiple influences. As well as this, data was triangulated from different sources, using multiple meth- ods to establish a reliable result. Peer debriefing was undertaken with a disinterested colleague, which helps the inquirer stay accountable and rational, can remind them of the “bigger picture”, and provide the opportunity for catharsis. Referential adequacy was established through the use of multiple recording methods, and negative case analysis allowed results to influence the evolution of the research, reframing the experiment. Transferability, necessary since it is impossible to establish external validity in qual- itative research, is established through thorough descriptions of the research methods. Dependability is established through credibility, in the same way that there is no scientific validity without reliab- ility. Confirmability is established by the use of triangulation of data, and reflexive collections of raw data, data reduction and reconstructions and process notes.