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Emergent design involves data collection and analysis procedures that can evolve over the course of a research project in response to what is learned in the earlier parts of the study. In particular, if the research questions and goals change in response to new information and insights, then the research design may need to change accordingly. This flexible approach to data collection and analysis allows for ongoing changes in the research design as a function of both what has been learned so far and the further goals of the study. Within the broader framework of qualitative research, emergent design procedures are closely associated with the broad goal of induction because success in generating theories and hypotheses often depends on a flexible use of research methods.

An emphasis on emergent design marks an important difference between most approaches to qualitative research and those to quantitative research. In particular, quantitative research is typically based on a fixed set of stages, starting with research design decisions that specify a set of predetermined data collection procedures that must be completed before data analysis can begin. Thus, survey research cannot redefine its sample or change its questionnaires midstream, and experimental interventions are equivalently locked into a set of design decisions that cannot be altered during data collection or analysis. In contrast to this “linear” set of well-defined stages, the emergent design approach in qualitative research is often summarized as a circular process. This means that new data are continually being analyzed as they are collected, so that both the research procedures and questions can be adjusted in an iterative fashion in response to what is being learned in the field. Ethnography is a useful illustration of this process because the ongoing analysis of fieldnotes leads to a shifting interpretation of both which issues are relatively well understood and which issues require further observations, so that ethnographers make design decisions—on an almost daily basis—about how to pursue their emerging interpretations.

Despite the importance of emergence in qualitative research, it would not be prudent to overstate the dominance of emergent design. Even the most flexible qualitative study begins with some ideas about what to observe, where to find sources for those data, and how to collect the relevant information. The prior ideas and beliefs that researchers bring to the field are sometimes known as “sensitizing concepts.” Hence, no research design can be fully or completely emergent; instead, emergent design allows for an ongoing reassessment of how to conduct the research based on what has been learned from prior data collection and analysis.

Emergent Aspects of Data Analysis

In comparison with the role of emergent design in data collection, issues related to the emergent aspects of data analysis typically receive more attention due to the heavy reliance on emergent procedures in nearly every form of qualitative analysis (with the notable exception of forms of content analysis that are based on predefined codebooks). In particular, many forms of qualitative analysis move from an initial stage of relatively descriptive or open coding to the creation of a broader set of emergent themes and concepts that then become the basic elements in the process of theory creation. This process of abstraction by moving from raw data to theorized conclusions is a central aspect of the link between emergent procedures and induction. Because the connection between emergence and induction is widely discussed within the literature on qualitative analysis, most of this entry concentrates on issues related to data collection, where emergence receives less explicit attention. There is, however, at least one aspect of analysis and emergence that deserves more attention.

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