Instrumentation rigor and bias management are major challenges for qualitative researchers employing interviewing as a data generation method in their studies. A usual procedure for testing the quality of an interview protocol and for identifying potential researcher biases is the pilot study in which investigators try out their proposed methods to see if the planned procedures perform as envisioned by the researcher. Sometimes piloting is not practical or possible so an "interviewing the investigator" technique can serve as a useful first step to create interview protocols that help to generate the information proposed and to assess potential researcher biases especially if the investigator has a strong affinity for the participants being studied or is a member of the population itself.

In the first of a series of “how-to” essays on conducting qualitative data analysis, Ron Chenail points out the challenges of determining units to analyze qualitatively when dealing with text. He acknowledges that although we may read a document word-by-word or line-by-line, we need to adjust our focus when processing the text for purposes of conducting qualitative data analysis so we concentrate on meaningful, undivided entities or wholes as our units of analysis.

Instrumentation rigor and bias management are major challenges for qualitative researchers employing interviewing as a data generation method in their studies. A usual procedure for testing the quality of an interview protocol and for identifying potential researcher biases is the pilot study in which investigators try out their proposed methods to see if the planned procedures perform as envisioned by the researcher. Sometimes piloting is not practical or possible so an "interviewing the investigator" technique can serve as a useful first step to create interview protocols that help to generate the information proposed and to assess potential researcher biases especially if the investigator has a strong affinity for the participants being studied or is a member of the population itself.

After all the data have been collected and the analysis has been completed, the next major task for qualitative researchers is to re-present the study in the form of a paper or a lecture. The challenge of converting mounds of data and analysis can be quite overwhelming even for the experienced researcher. To help you with your efforts at presenting qualitative research in your papers and in your talks, I ask you to consider the following ideas: Openness, Data as Star, Juxtaposition, and Data Presentation Strategies.

This paper reports on the first stage of a meta-study conducted by the authors on primary research published during the last thirty years that focused on discovering the experiences of students learning qualitative research. The authors carried out a meta-analysis of the findings of students’ experiences learning qualitative research included in twenty-five published articles. Using constructivist grounded theory to analyze the experience of those seeking to learn qualitative research, including factors that appear to support or interfere with their learning experiences, the authors identified three key dimensions of qualitative research students’ learning experiences—affective, cognitive, and experiential. Based on this analysis, the authors developed a grounded theory of qualitative research education. This theory suggests that students’ learning experiences will be enhanced through the implementation of an inductive approach to qualitative research education that incorporates experiential learning early in the learning experience. This paper reports these findings, presents this grounded theory of inductive qualitative research education, and discusses the implications of the findings of this meta-analysis for those teaching and researching qualitative research.