![]() ![]() These studies have been mainly descriptive or comparative, with sometimes contradictory outcomes. ![]() In recent years, researchers have begun to publish more thorough descriptions of how they are using software to support their analysis. Whether software is used or not, the researcher remains in charge of decisions around how to handle, analyse and interpret the data. We agree with the view of Lewins and Silver (2007) that far from imposing a particular analytic structure or approach to the data, CAQDAS tools afford a variety of functions and features which can be intentionally used (or ignored) by the researcher based on their analytic needs. Visit Web Resource 7.3 to read more about the debates around the use of software for qualitative research. This is in part because grounded theory as a methodology was popularized at around the same time as the initial CAQDAS packages were (Davidson and Di Gregorio, 2011). Over the years there has been a persistent, but mistaken, perception that CAQDAS most easily, or only, supports one methodology, namely grounded theory (Lonikila, 1995), and one analytic method, namely coding – see Coffey, Holbrook and Atkinson (1996) and the response by Lee and Fielding (1996). Given the variety of approaches to analysis it is not particularly surprising that the idea of using computers to support analysis would generate debate. Visit Web Resource 7.2 to explore the University of Surrey's CAQDAS networking project.Įven though CAQDAS packages were initially developed by qualitative researchers and were updated regularly based on user feedback (only later becoming commercial products), there has historically been scepticism and resistance towards the use of computers for data analysis (Davidson and Di Gregorio, 2011). Because the choice of research methodology and specific data analysis methods are beyond the scope of this book, we refer you to Saldana (2013), Grbich (2013), Gibson and Brown (2009) and Gibbs (2007) for helpful overviews of qualitative data analysis methods. Other qualitative research methodologies include, but are not limited to, life history or biographical research, discourse analysis, conversation analysis and ethnomethodology, action research, critical/feminist approaches, action research and visual or semiotic methodologies. Ideally, data analysis methods are to be grounded in particular methodologies, such as the five introduced by Creswell (2013): narrative, phenomenology, grounded theory, ethnography and case study. Saldana (2013) discussed 25 first-cycle coding methods and six second-cycle coding methods for qualitative analysis. Tesch (1990), one of the earliest scholars to discuss data analysis software, identified 26 approaches to qualitative research and illustrated how they could be supported by software programs. There are many different approaches to data analysis. Whether you're a novice or expert social researcher, this book will inspire you to think creatively about how to approach your research project and get the most out of the huge range of tools available to you. On the companion website, you'll find lots of additional resources including video tutorials and activities. The book also considers important ethical issues surrounding the use of various technologies in each chapter. The text shows you how to select and use technology tools to: engage in reflexivity collaborate with other researchers and stakeholders manage your project do your literature review generate and manage your data transcribe and analyse textual, audio and visual data and represent and share your findings. It addresses the use of a variety of tools (many of which may already be familiar to you) to support every phase of the research process, providing practical case studies taken from real world research. Digital Tools for Qualitative Research shows how the research process in its entirety can be supported by technology tools in ways that can save time and add robustness and depth to qualitative work.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |