Using Criteria of Significance to Make Sense of Data: Implications for Qualitative Research

Abstract

For many qualitative researchers, the task of dealing with huge amounts of data can be overwhelming. In many qualitative research methodologies, procedures for making sense of large amounts of data are often intentionally unclear and open to interpretation due to the wide range of variability of data and research context. This can be problematic for novice and experienced researchers alike as they consider what parts of their data to feature, exemplify and draw conclusions from. This article puts forth a construct that makes explicit the logics of two researchers using what they label as “criteria of significance” to make sense of their qualitative data. The Criteria of Significance (CoS) serves as a defensible set of criteria by which data is given increased or decreased value regarding its use in the final analysis and conclusions drawn from a study. This paper examines two qualitative studies (Hirschkorn, 2008; Morrison, 2018) and explores how CoS was used to differentiate the data used in their findings.