Quantitative and qualitative research design

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There are a number of fundamental issues that need to be addressed equally by quantitative and qualitative research designs. The amount of data to be collected – the sample size – will be directly related to the explanatory power of the analysis.

For quantitative research designs, sample size is based on an estimate of the overall population from which the data are selected. In addition, more advanced inferential statistical tests will require a specific minimum amount of data in order to deliver results. In general, quantitative research tends to work with relatively large overall sample sizes. However, the information contained at each data point tends to be very rudimentary. In contrast, for qualitative research designs, sample sizes can be far more compact. There is usually no straightforward technical means of calculating how large the sample ought to be, with adequate size usually being determined against the convention adopted within a particular research tradition. However, the amount of information contained can be enormous and very detailed. In Art History, the sample might be determined by actual output of a particular painter, lithographer or sculptor; if prolific, the sample might be based on a specific theme.

In a quantitative design, it is essential to define variables (i.e. the things to be measured or estimated) that will be used to organize the data. Variables are typically constructed on the basis of prior theories taken from the literature. In this way, the majority of quantitative research designs are deductive in their approach – they seek to gather data to test hypotheses that formulated from existing theoretical propositions. In the majority of qualitative designs, the approach taken is inductive, rather than deductive. Here is it important to have clearly formulated relevant research questions and to ensure that these questions are adequately translated into the data collection process. For instance, if interviews are required, then a schedule of suitably crafted questions must be prepared.But it is certainly expected that the themes and issues that emerge in the research process are not known entirely at the start.

A common research design is to gather a wide range of data about a single research site. Case study designs involve the intensive study of a particular museum, monument type, organization, social media platform, etc. Case study designs are popular because they offer the possibility of formulating a range of research questions, and the data that result can be used to draw a fairly detailed account of the research site.

Sometimes it is not possible to negotiate the kind of extensive levels of access that are required for either ethnographic or case study designs. For example, a compact or limited qualitative research design might seek to simply interview key informants without collecting any other kind of data. This kind of narrow slice through a research problem is usually referred to as a cross-sectional design. It involves the collection of a number of data points at more or less the same time. Cross-sectional designs are useful because they enable internal comparisons to be made between the data points (i.e. we can compare what the different key informants say). But they are limited by the fact that the data have no real temporal dimension. So, for example, if we were to return to these same respondents in a year’s time, we might find that their accounts had changed somewhat.

A properly comparative design goes beyond internal comparisons and actively seeks to explore the same kind of phenomenon in two or more settings. This kind of design is potentially very powerful because it allows us to correlate or contrast our findings beyond one setting. Comparing two or more instances of the same phenomenon is also very useful in clarifying the features of each. In particular looking at similarities and differences may alert us to things we have overlooked in one of the settings. However, comparative designs offer severe logistical challenges. Not only are they more time and resource intensive, they also need considerable care to be taken to ensure that the comparison itself is meaningful.

However you design your research project, you will need to demonstrate clearly how your approach, methodology and methods specifically will help you to answer the research question(s) and objectives that you have set for your doctoral research.