Archive

These materials were developed in the "Methodological Innovations in Computational Support" stream of the Qualitative Innovations in CAQDAS (QUIC) project, funded by the National Centre for Research Methods (NCRM) (2008-2011). They have now been superseded by new releases of the CAQDAS packages, but are available here for those using older versions of the CAQDAS packages showcased. 

Analysing survey data

These pages provide comparative information about using selected CAQDAS packages to analyse open-ended questions to survey data. 

Analysing audio-visual data 

These pages provide information about preparing and analysing audio-visual data in selected CAQDAS packages.

Integrating geographical data

These pages provide discussion and support for integrating geographical data and analyses using selected CAQDAS packages.

About these resources

Qualitative innovations in CAQDAS (QUIC) explored technological and methodological developments in qualitative software and provided additional training and capacity building opportunities to fill identified gaps in support for software users. We evaluated the suitability of different qualitative packages in these respects and derived exemplars, teaching datasets, and self-learning materials from each mini-research project. 

Methodological Innovations in Computational Support

In this stream of QUIC's work, we used data generated from the substantive areas of environmental risk and crime and social disorder QUIC to focus on three key areas of development in computational qualitative social science methodology:

Full integration of quantitative and qualitative data in mixed-methods research

The data integration stream evaluated and documented procedures for CAQDAS-based methodological integration by:

  • Employing selected qualitative software packages to conduct secondary analysis of qualitative data on the social factors in response to natural environmental risk arising from climate change.
  • Comparing findings from these procedures to the statistical analysis of the quantitative data in these datasets. QSR NVivo, MAXQDA and ATLAS.ti variously provide means of importing quantitative data and linking with qualitative datasets, converting qualitative codes into quantitative variables and allowing their export to statistical packages.
  • We also included the hybrid software suite that includes QDA Miner which starts from a different epistemological starting points, as it offers traditional CAQDAS functions which can be used alongside enhanced quantitative approaches to the analysis of large datasets (e.g. multidimensional scaling, heatmaps, dendrograms, proximity plots). Such tools answer a wider range of research needs, often associated with policy research, public/media/academic discourse, or analysis of Internet and e-mail data.

Systematic analysis of multi-stream visual data (e.g. access grid data)

The second QUIC research project related to multi-stream visual data. Social science increasingly uses visual data, and a new networked video conferencing technology called 'access grid' will allow people at many locations to participate in 'virtual fieldwork' or teaching sessions convened by a host site.

The project aimed to refine and document procedures developed in the previous two years for the use of the access grid in primary data collection and advanced pedagogy. It built on an ESRC e-social science project that delivered the world's first 'virtual fieldwork' via the access grid, and on an institution-funded pilot project delivering advanced software training via the access grid. Thus, the project aim was to document how to analyse AG multi-stream visual data using CAQDAS, and deliver training via AG.

The substantive test-bed application was to conduct virtual fieldwork involving staff of the Environment Agency and/or National Probation Service.

Convergence of geographical information systems (GIS) technology with qualitative software

The geo-referencing project applied and evaluated CAQDAS tools that offer GIS-type functionality, via geo-referencing a crime risk assessment methodology which explores the social environmental risk arising from crime/disorder. Geo-referencing qualitative software will enable users to add a spatial dimension to qualitative data analysis.

Currently users of GIS and of CAQDAS do not much intersect, yet the gains in being able to code, annotate and analytically manipulate visual representations of physical space with CAQDAS functionality are attractive. Using environmental scan methodology developed to support police/community crime audits, this stream will evaluate the affordances of GIS-type CAQDAS functionality and develop an exemplar study for the TCB component of the node's work.

 

Feedback

We always welcome feedback concerning the relevance and usefulness of our resources. Many of the materials we provide are the direct result of repeated requests from students and qualitative researchers so if you have downloaded any of the materials above please email us with your comments.