by Judith Davidson
Judith Davidson is an Associate Professor in the Research Methods and Program Evaluation Ph.D. Program of the Graduate School of Education, University of Massachusetts Lowell. She is a founding member of the ICQI Digital Tools Special Interest Group. She is currently working on a book about complex qualitative research teams, which she is writing in NVivo!
Qualitative researchers increasingly find themselves working as members of a complex research team. Multiple members, multiple disciplines, geographically dispersed—these are just some of the forms of diversity that we face in our research endeavors. Many of these research teams employ Qualitative Data Analysis Software (QDAS).
While there are many reasons to use QDAS in complex team research, the one I wish to talk about here is support of transparency: making clear how results were reached or showing proof of the process of interpretation that indicates the conclusions are believable. Transparency has long been held up as a virtuous and important notion in qualitative research, but as with many things in qualitative research, many of our descriptions relate to individually conducted research, not team-based research projects. Moreover, our considerations of transparency have not yet made much sense of qualitative research conducted with QDAS.
As part of the 2016 ICQI Digital Tools strand and a panel examining issues related to QDAS use with complex teams, I presented a paper titled “Qualitative Data Analysis Software Practices in Complex Qualitative Research Teams: Troubling the Assumptions about Transparency (and Portability)” (Davidson, Thompson, and Harris, under review) that sought to get at some of the issues that arise at the nexus of complex teams, qualitative research, QDAS, and transparency.
Our paper applied Jackson’s notion of transparency-in-motion (Jackson, 2014) to the methodological process of a complex team project in which we had been engaged, Building a Prevention Framework to Address Teen “Sexting” Behaviors, or the ‘Sexting Project’ (Harris et al; Davidson, 2014). Jackson’s ideas were derived from a study of ‘lone ranger’ researchers, doctoral students using QDAS in their own, individual research work. In contrast, the goal of our paper was to demonstrate how Jackson’s descriptive categories of transparency-in-motion (triage, show, and reflect) are enacted by real teams working with real world restrictions that teams often face in trying to use QDAS. In the article, we follow the development of one finding from the Sexting Project, the continuum of sexting, to show how QDAS use wove in and out of the stages of triage, show, and reflect as this term evolved for the research team (Davidson, 2011).
The Sexting Study was conducted by a multi-disciplinary team located at three institutions of higher education in three regions of the United States. Focus group data about views of teen sexting was collected from three separate audiences at these locations; teens, teen caregivers, and those who worked with and for teens. It was one of the first qualitative research studies conducted on the topic of sexting. All data collected for the study was organized in an NVivo database maintained by the lead site.
The following table gives a quick and dirty overview of the discussion from the paper.
|Sub-categories of Jackson’s notion of Transparency-in-motion (2014)||Applications from the Sexting Project (Harris, et al, 2013), illustrating the malleable relationship of transparency and QDAS|
|Triage: Emphasize, Sort, Classify||In NVivo, Davidson and Thompson coded focus group responses to “Why do youth sext?” Noticed differences in regard to relationship, peer group, and gender.|
|Show: Share, Illustrate, Hold-up||In full team meetings, Davidson and Thompson used NVivo to examine the responses to this question and to dig down into the differences noted.|
|Reflect: Examine Content, Negotiate Meaning||Full group reflects and develops the notion of “the continuum of sexting”. Davidson and Thompson return to recode the responses in NVivo as points on this continuum: Mutual Interest; Self Interest; Intent to Harm|
Analysis of our process demonstrated that NVivo fulfilled possibilities for triage-in-motion (triage, show, and reflect) through deep individual analysis with the tool and broader episodic analysis with the full research team. Despite differential access to NVivo by team members (only lead team had a site license), the tool was able to offer all researchers better opportunities for working with the data and visualizing relationships within the data. Despite these restrictive circumstances, the QDAS tool could play this role, because there was senior leadership knowledgeable and experienced in the use of the tool who could support full group opportunities to use and think with it.
These findings indicate Jackson’s notion of transparency-in-motion has relevance to both individual researchers and research teams. Using the key criteria of triage, show, and reflect, researchers were able to manage the use of QDAS as they continuously worked toward transparency-in-motion under less than ideal conditions. Discussions of transparency have long been prominent in qualitative research, but we suggest that in today’s post-modern/post-structural world transparency-in-motion may be a more useful perspective for qualitative researchers to adopt.
Davidson, J., Thompson, S., Harris, A., (under review). Qualitative Data Analysis Software Practices in Complex Qualitative Research Teams: Troubling the Assumptions about Transparency (and Portability).
Harris, A., Davidson, J., Letourneau, E., Paternite, C., Miofshky, K.T. (September 2013. Building a Prevention Framework to Address Teen “Sexting” Behaviors. (189 pgs). Washington DC: U.S. Dept. of Justice Office of Juvenile Justice & Delinquency Prevention.
Jackson, K. (2014). Qualitative Data Analysis Software, Visualizations, and Transparency: Toward an Understanding of Transparency in Motion. Paper presented at the Computer Assisted Qualitative Data Analysis conference, May 3, 2014. Surrey, England.
Points of view or opinions in this document are those of the author and do not necessarily represent the official position or policies of the U.S. Department of Justice, which funded the project.