Qualitative research is increasingly accepted both inside and outside of academia. According to research software scholar Fielding (2012), this development is partly due to the greater distribution of qualitative data analysis (QDA) software. However, while a growing number of researchers seem to integrate QDA software into their professional work, this tendency is not necessarily reflected in undergraduate methods education. If QDA software training is provided in undergraduate classes, it is often disconnected from methods education and happens within a short time period. Consequently, software trainers and instructors mostly focus on mechanical tasks within the program. (Carvajal, 2002)

Instruction on a basic technical level does not reflect the challenging interplay between tool and method (Schmieder, 2009; 2013 forthcoming): In software-based workflows, the practical steps – guided by the analytic method – manifest in the digital workspace. In abbreviated software training it is not possible to convey that the use of software in qualitative research is fundamentally a methodological process. The research methods shape how the software features are used, and the affordances and restrictions of both method and tool need to be balanced. In one of the few empiric studies on QDA software use, Fielding & Lee (1998, p. 77) observe that “whether or not the computer does distance researchers from data, it challenges researchers to be clear about their assumptions.” If software use stimulates such methodological reflection, it can serve a powerful teaching tool.

Macgowan & Beaulaurie (2005, as cited in Parmeggiani, 2008, p. 98) report that “the use of data analysis software in group work courses gives students concrete examples and experiences”. Similarly, Walsh (2003) observes that adding a QDA software lab to her undergraduate methods class made students more playful in their analytic procedures. Software can also be introduced as a professional writing and data organization tool, e.g. when students document and annotate what they learn in a methods class. (Walsh, 2003) If combined with a class research project, software use becomes an authentic, meaningful task.

Using a professional tool in a professional context gives undergraduate learners the chance to take on the role of a professional, which is a powerful motivational factor for learning (cf. Gee 2004).

Many novices believe that QDA software use was a specific method, or would constitute as methodological procedure (Carvajal, 2002). Without QDA software instruction going beyond mechanical tasks, this preconception might be harder to defeat. In practice, this very notion manifests in a phenomenon that software developer Richards (2002) calls the coding fetish (cf. also Tagg, 2010): Because coding is easy to do with QDA software, and generally taught in the brief software classes, (methodologically) inexperienced users may tend to resort to mechanical coding, rather than utilizing the software in order to put their method into practice.

Good QDA software provides a variable set of tools for annotating, organizing, and displaying data. By transferring methodologically grounded strategies into a software workspace, research methods manifest in the form of procedural elements. Using software, researchers create a digital workspace for analysis. Thus, software poses a design challenge: For example, a possible task for undergraduate students could consist in creating a workspace that captures the main steps of several methodological procedures by utilizing the tools provided by the software.

Integrating QDA software into undergraduate methods instruction may seem challenging because another topic is added to already tightly packed syllabi. However, this tool should not be viewed as yet another challenge, but rather as chance to nurture methodological reflection in novices and to provide students with the experience of analysis as a process of decisions.

References

Carvajal, D. (2002). The artisan’s tools. Critical issues when teaching and learning CAQDAS. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 3(2). Retrieved from: http://www.qualitative-research.net/fqs/fqseng.htm
Fielding, N.G. & Lee, R.M. (1998). Computer analysis and qualitative research. London: Sage.
Fielding, N.G. (2012). The diverse worlds and research practices of qualitative software. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 13(2), 13. Retrieved from: http://nbn-resolving.de/urn:nbn:de:0114-fqs1202124
Gee, J.P. (2004). Situated language & learning: A critique on traditional schooling. London: Routledge.
Johnston, L. (2006). Software and method: Reflections on teaching and using QSR NVivo in doctoral research. International Journal Social Research Methodology, 9(5), 379–391.
Macgowan M.J. & Beaulaurie R.L. (2005). Using qualitative data analysis software in teaching about group work practice. Journal of Teaching in Social Work, 25(1/2), 45–56.
Parmeggiani, P. (2008). Teaching different research methods through the use of video analysis software for media students: A case study. International Journal of Multiple Research Approaches, 2, 94–104.
Richards, L. (2002). Qualitative computing – a methods revolution? International Journal Social Research Methodology, 5(2), 263-276.
Schmieder, C. (2009): Technik der Legitimation – Legitimation der Technik. Eine qualitative Studie zur Verwendung von MAXqda in qualitativem Forschen. Retrieved from: http://www.freidok.uni-freiburg.de/volltexte/7082/
Schmieder, C. (2013, forthcoming). QDA-Software und Qualitative Methodik. In J. Kruse, Einführung in rekonstruktive Interviewforschung. Munich: Fink.
Tagg, C. (2010). Reflecting on the impact of qualitative software on teaching. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 12(1), 27. Retrieved at: http://nbnresolving.de/urn:nbn:de:0114-fqs1101277
Walsh, M. (2003). Teaching qualitative analysis using QSR NVivo. The Qualitative Report,8(2). Retrieved from http://www.nova.edu/ssss/QR/qr8-2/walsh.pdf

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