Qualitative research designs data collection

The most common methods of data collection in qualitative research designs are interviews, observations, and document analysis. 

The third most common method for collecting data in qualitative research designs is known as document analysis. While the thoughts, words, and actions of research subjects are essential, generating thick description requires a complete description of the context in which these dioughts and words are formed and actions take place. Course syllabi, copies of lab experiments, copies of student evaluation forms, and copies of research proposals are typical examples of documents gathered to analyze in a qualitative research design. 

Just as chemists make regular entries in their lab notebooks about procedures, data, and emerging hypotheses, so too do qualitative researchers. Qualitative research designs rely heavily on accurate and methodical recordkeeping. Fieldnotes are created for each data collection opportunity and typically include the following (21) ... 

Empirical evaluation methods involve actual or designated users. The methods can be relatively informal, such as observing people while they explore a prototype, or they can be quite formal and systematic, such as a tightly controlled laboratory study of performance times and errors or a comprehensive survey of many users [941, 943]. Independent of this differentiation, in general, qualitative and quantitative methods of both data collection and data analysis can be distinguished. While quantitative research focuses on how to operationalize or quantify the attributes to be measured, qualitative research interprets verbal or non-numerical data [563]. 

Dependability concerns the quality of the inquiry process while confirmability addresses the quality of the inquiry product, i.e., the data, interpretations and recommendations. A common mechanism to address both of these trustworthiness criteria is to employ a qualitative data audit in the research design. An audit trail can simultaneously address both the dependability and the confirmability of a research study. A dependability audit reviews the methodological decisions made in the inquiry, while the confirmability audit examines the findings of the inquiry to confirm that the researcher s interpretations are grounded in both the theoretical framework and in the data collected. 

An important aspect of mixed method designs is the priority of the quantitative and qualitative approach. In other words, does one research approach have a dominant priority over the other or are they of equal priority The emphasis of either approach is dictated by the intent of the researcher and the goals of the study. In a practical sense, the first type of data collection usually has the dominant priority. For example, in the Mulford and Robinson... 

Sequential explanatory designs can use factor analysis— the grouping of quantitative data into factors or categories— to convert quantitative data into themes. This transformation is used to guide subsequent qualitative data collection, analysis, and interpretation. It may provide areas for researchers to explore in greater depth with participants in the qualitative phase of the study. 

Concurrent mixed methods procedures are those in which the researcher converges or merges quantitative and qualitative data in order to provide a comprehensive analysis of the research problem. In this design, the investigator collects both forms of data at the same time and then integrates the information in the interpretation of the overall results. Also, in this design, the researcher may embed one smaller form of data within another larger data collection in order to analyze different types of questions. 

We employ the guidelines of [18] to conduct the case study. A case study is the most appropriate research methodology for this setting, as its primary objective is exploratory, with a flexible design, and collecting qualitative (instead of quantitative) data. Concretely, the case study encompasses the following steps ... 

In the implementation step, researchers must decide whether the data is to be collected sequentially or concurrently. There should be a clear rationale for choosing a specific strategy that is tied to the overall goal of the study. For example, in a sequential design where the qualitative data are collected and analyzed first, the emergent understandings may be explored with a wider audience in a second quantitative phase. That was the implementation approach used in the Mulford and Robinson study (2) described above. The qualitative phase took place first and was used to develop the survey implemented in the quantitative phase of the study. 

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