After completing the data collection phase of a mixed-methods or qualitative project, researchers are often faced with a vast amount of data, and a single, sometimes overwhelming question: How do I make meaning out of all of this?

Gibson’s researchers were excited about a recent opportunity to help 18 doctoral and postdoctoral students at Southern Methodist University (SMU) answer this question. Various project teams in the Simmons School of Education and Human Development were about to embark on the analytic phase of their own research projects, all including large amounts of interview, observational, and/or focus group data. Some of these students and staff also needed to understand how to incorporate quantitative data points into their qualitative analyses.

In response to their specific needs, we designed a one-day workshop to a) provide training in the conceptual framework and core fundamentals of qualitative analysis, b) provide an introductory training on software tools that can facilitate these analyses, and c) demonstrate how to leverage the power of mixed-methods data when both quantitative and qualitative data are available. We also allowed for small-group worktime, so that researchers could immediately begin to apply what they learned during the training to their actual research projects, while our researchers were available to assist, guide, and support these efforts.

The day-long training was composed of four parts:

Part I: Beginning with the End in Mind: What Does a Fully Coded and Analyzed Qualitative Dataset Look Like?

We reviewed a fully coded and analyzed qualitative dataset with the workshop participants, highlighting how a study’s research questions must drive the design and execution of the coding and analysis phases. This demonstration also provided an opportunity to illustrate some of the power of the analytic software.

Part II: Qualitative Analysis Fundamentals

We next provided a mini-lecture on qualitative fundamentals, including coding styles, lumping versus splitting, mutually exclusive versus overlapping codes, and inter-rater reliability, among other core concepts.

Part III: Working through an NVivo Sample

Using NVivo analytic software, we then demonstrated how to apply a coding structure to qualitative data, we reviewed various coding options, discussed how to modify the coding structure, demonstrated auto-coding and discussed its strengths/weaknesses, and sampled various queries and built-in analytic tools that allow the research team to begin to detect emerging patterns in the data.

Part IV: Small Group Work: Applying the Workshop to Project Needs

During the final phase of the workshop, participants had the opportunity to work in small groups using their own real-world qualitative data. Gibson researchers were available to the research teams to help them apply what they had learned to their own projects, to answer questions, and to provide additional guidance on topics that may not have been covered during the training.

Making meaning out of data is at the core of every research project. Whether those data are numbers in a spreadsheet or sentences in an interview transcript, our team of researchers can help provide training, guidance, and support as you grapple with the complex issues that arise in your own research project. Contact our Director of Research, Dr. Amie Rapaport, if you would like to learn more about how our research team can help.